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+++ b/notebooks/Ensembling.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VERSION = 33\n",
+    "\n",
+    "FOCAL_LOSS = 0\n",
+    "CLOUD_SINGLE = True\n",
+    "MIXUP = False\n",
+    "NO_BLACK_LOSS = True\n",
+    "DATA_SMALL = False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if VERSION in [31,32]:\n",
+    "    TRAIN_ON_STAGE_1 = False\n",
+    "else:\n",
+    "    TRAIN_ON_STAGE_1 = True\n",
+    "\n",
+    "if VERSION in [32,34,36]:\n",
+    "    WEIGHTED = True\n",
+    "else:\n",
+    "    WEIGHTED = False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%run ./Code.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if VERSION in [31,32]:\n",
+    "    # old features, no stage2 training\n",
+    "    train_md, test_md = loadMetadata()\n",
+    "elif VERSION in [33,34]:\n",
+    "    # old features, with stage2 training\n",
+    "    train_md, test_md = loadMetadata3()\n",
+    "elif VERSION in [35,36]:\n",
+    "    # new features\n",
+    "    train_md, test_md = loadMetadata2()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# OOF"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 14\n",
+      "DataSet 7 valid size 7232 fold 0\n",
+      "dataset valid: 7232 loader valid: 226\n",
+      "loading model model.b3.f0.d7.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.039 time per batch: 0.221\n",
+      "Batch 100 device: cuda time passed: 19.674 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.256 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 36.735 time per batch: 0.184\n",
+      "ver 34, iter 0, fold 0, val ll: 0.0629, cor: 0.8425, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.369 time per batch: 0.227\n",
+      "Batch 100 device: cuda time passed: 19.874 time per batch: 0.199\n",
+      "Batch 150 device: cuda time passed: 28.322 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 36.820 time per batch: 0.184\n",
+      "ver 34, iter 1, fold 0, val ll: 0.0633, cor: 0.8416, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.085 time per batch: 0.222\n",
+      "Batch 100 device: cuda time passed: 19.790 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.354 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 36.403 time per batch: 0.182\n",
+      "ver 34, iter 2, fold 0, val ll: 0.0630, cor: 0.8423, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.630 time per batch: 0.233\n",
+      "Batch 100 device: cuda time passed: 20.129 time per batch: 0.201\n",
+      "Batch 150 device: cuda time passed: 28.720 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 36.561 time per batch: 0.183\n",
+      "ver 34, iter 3, fold 0, val ll: 0.0631, cor: 0.8421, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.798 time per batch: 0.216\n",
+      "Batch 100 device: cuda time passed: 20.275 time per batch: 0.203\n",
+      "Batch 150 device: cuda time passed: 28.541 time per batch: 0.190\n",
+      "Batch 200 device: cuda time passed: 36.693 time per batch: 0.183\n",
+      "ver 34, iter 4, fold 0, val ll: 0.0630, cor: 0.8427, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.537 time per batch: 0.231\n",
+      "Batch 100 device: cuda time passed: 20.034 time per batch: 0.200\n",
+      "Batch 150 device: cuda time passed: 29.120 time per batch: 0.194\n",
+      "Batch 200 device: cuda time passed: 37.470 time per batch: 0.187\n",
+      "ver 34, iter 5, fold 0, val ll: 0.0631, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.616 time per batch: 0.232\n",
+      "Batch 100 device: cuda time passed: 20.549 time per batch: 0.205\n",
+      "Batch 150 device: cuda time passed: 28.847 time per batch: 0.192\n",
+      "Batch 200 device: cuda time passed: 37.005 time per batch: 0.185\n",
+      "ver 34, iter 6, fold 0, val ll: 0.0632, cor: 0.8420, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.390 time per batch: 0.228\n",
+      "Batch 100 device: cuda time passed: 19.692 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.482 time per batch: 0.190\n",
+      "Batch 200 device: cuda time passed: 37.211 time per batch: 0.186\n",
+      "ver 34, iter 7, fold 0, val ll: 0.0632, cor: 0.8418, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.109 time per batch: 0.222\n",
+      "Batch 100 device: cuda time passed: 19.665 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 27.973 time per batch: 0.186\n",
+      "Batch 200 device: cuda time passed: 36.279 time per batch: 0.181\n",
+      "ver 34, iter 8, fold 0, val ll: 0.0631, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.182 time per batch: 0.224\n",
+      "Batch 100 device: cuda time passed: 20.280 time per batch: 0.203\n",
+      "Batch 150 device: cuda time passed: 28.800 time per batch: 0.192\n",
+      "Batch 200 device: cuda time passed: 37.683 time per batch: 0.188\n",
+      "ver 34, iter 9, fold 0, val ll: 0.0632, cor: 0.8418, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.546 time per batch: 0.231\n",
+      "Batch 100 device: cuda time passed: 19.935 time per batch: 0.199\n",
+      "Batch 150 device: cuda time passed: 28.393 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 37.353 time per batch: 0.187\n",
+      "ver 34, iter 10, fold 0, val ll: 0.0631, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.706 time per batch: 0.234\n",
+      "Batch 100 device: cuda time passed: 20.097 time per batch: 0.201\n",
+      "Batch 150 device: cuda time passed: 28.629 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 36.971 time per batch: 0.185\n",
+      "ver 34, iter 11, fold 0, val ll: 0.0632, cor: 0.8416, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.344 time per batch: 0.227\n",
+      "Batch 100 device: cuda time passed: 20.333 time per batch: 0.203\n",
+      "Batch 150 device: cuda time passed: 28.633 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 36.853 time per batch: 0.184\n",
+      "ver 34, iter 12, fold 0, val ll: 0.0632, cor: 0.8418, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.884 time per batch: 0.218\n",
+      "Batch 100 device: cuda time passed: 19.948 time per batch: 0.199\n",
+      "Batch 150 device: cuda time passed: 28.653 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 37.139 time per batch: 0.186\n",
+      "ver 34, iter 13, fold 0, val ll: 0.0632, cor: 0.8422, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.232 time per batch: 0.225\n",
+      "Batch 100 device: cuda time passed: 19.680 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.180 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 36.829 time per batch: 0.184\n",
+      "ver 34, iter 14, fold 0, val ll: 0.0631, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.134 time per batch: 0.223\n",
+      "Batch 100 device: cuda time passed: 19.750 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.254 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 37.052 time per batch: 0.185\n",
+      "ver 34, iter 15, fold 0, val ll: 0.0632, cor: 0.8419, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.076 time per batch: 0.222\n",
+      "Batch 100 device: cuda time passed: 19.921 time per batch: 0.199\n",
+      "Batch 150 device: cuda time passed: 28.521 time per batch: 0.190\n",
+      "Batch 200 device: cuda time passed: 36.744 time per batch: 0.184\n",
+      "ver 34, iter 16, fold 0, val ll: 0.0633, cor: 0.8417, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.846 time per batch: 0.217\n",
+      "Batch 100 device: cuda time passed: 20.198 time per batch: 0.202\n",
+      "Batch 150 device: cuda time passed: 28.638 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 36.762 time per batch: 0.184\n",
+      "ver 34, iter 17, fold 0, val ll: 0.0631, cor: 0.8423, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.145 time per batch: 0.223\n",
+      "Batch 100 device: cuda time passed: 19.770 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.000 time per batch: 0.187\n",
+      "Batch 200 device: cuda time passed: 36.639 time per batch: 0.183\n",
+      "ver 34, iter 18, fold 0, val ll: 0.0631, cor: 0.8418, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.940 time per batch: 0.219\n",
+      "Batch 100 device: cuda time passed: 19.199 time per batch: 0.192\n",
+      "Batch 150 device: cuda time passed: 27.382 time per batch: 0.183\n",
+      "Batch 200 device: cuda time passed: 35.991 time per batch: 0.180\n",
+      "ver 34, iter 19, fold 0, val ll: 0.0633, cor: 0.8418, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.303 time per batch: 0.226\n",
+      "Batch 100 device: cuda time passed: 20.052 time per batch: 0.201\n",
+      "Batch 150 device: cuda time passed: 28.800 time per batch: 0.192\n",
+      "Batch 200 device: cuda time passed: 37.209 time per batch: 0.186\n",
+      "ver 34, iter 20, fold 0, val ll: 0.0631, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.012 time per batch: 0.220\n",
+      "Batch 100 device: cuda time passed: 19.801 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.285 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 36.655 time per batch: 0.183\n",
+      "ver 34, iter 21, fold 0, val ll: 0.0631, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.588 time per batch: 0.232\n",
+      "Batch 100 device: cuda time passed: 19.972 time per batch: 0.200\n",
+      "Batch 150 device: cuda time passed: 28.349 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 36.708 time per batch: 0.184\n",
+      "ver 34, iter 22, fold 0, val ll: 0.0632, cor: 0.8421, auc: 0.9880\n",
+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 50 device: cuda time passed: 11.373 time per batch: 0.227\n",
+      "Batch 100 device: cuda time passed: 19.848 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.645 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 37.166 time per batch: 0.186\n",
+      "ver 34, iter 23, fold 0, val ll: 0.0631, cor: 0.8424, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.732 time per batch: 0.235\n",
+      "Batch 100 device: cuda time passed: 20.379 time per batch: 0.204\n",
+      "Batch 150 device: cuda time passed: 28.964 time per batch: 0.193\n",
+      "Batch 200 device: cuda time passed: 37.185 time per batch: 0.186\n",
+      "ver 34, iter 24, fold 0, val ll: 0.0632, cor: 0.8421, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.942 time per batch: 0.219\n",
+      "Batch 100 device: cuda time passed: 19.584 time per batch: 0.196\n",
+      "Batch 150 device: cuda time passed: 27.962 time per batch: 0.186\n",
+      "Batch 200 device: cuda time passed: 36.295 time per batch: 0.181\n",
+      "ver 34, iter 25, fold 0, val ll: 0.0631, cor: 0.8421, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.547 time per batch: 0.231\n",
+      "Batch 100 device: cuda time passed: 19.793 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.204 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 36.624 time per batch: 0.183\n",
+      "ver 34, iter 26, fold 0, val ll: 0.0630, cor: 0.8426, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.957 time per batch: 0.219\n",
+      "Batch 100 device: cuda time passed: 18.892 time per batch: 0.189\n",
+      "Batch 150 device: cuda time passed: 27.679 time per batch: 0.185\n",
+      "Batch 200 device: cuda time passed: 36.440 time per batch: 0.182\n",
+      "ver 34, iter 27, fold 0, val ll: 0.0630, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.715 time per batch: 0.214\n",
+      "Batch 100 device: cuda time passed: 19.980 time per batch: 0.200\n",
+      "Batch 150 device: cuda time passed: 28.835 time per batch: 0.192\n",
+      "Batch 200 device: cuda time passed: 37.150 time per batch: 0.186\n",
+      "ver 34, iter 28, fold 0, val ll: 0.0633, cor: 0.8417, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.384 time per batch: 0.228\n",
+      "Batch 100 device: cuda time passed: 19.805 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.613 time per batch: 0.191\n",
+      "Batch 200 device: cuda time passed: 37.061 time per batch: 0.185\n",
+      "ver 34, iter 29, fold 0, val ll: 0.0631, cor: 0.8421, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.388 time per batch: 0.228\n",
+      "Batch 100 device: cuda time passed: 19.790 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.816 time per batch: 0.192\n",
+      "Batch 200 device: cuda time passed: 36.974 time per batch: 0.185\n",
+      "ver 34, iter 30, fold 0, val ll: 0.0633, cor: 0.8417, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.891 time per batch: 0.218\n",
+      "Batch 100 device: cuda time passed: 19.773 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 28.208 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 36.513 time per batch: 0.183\n",
+      "ver 34, iter 31, fold 0, val ll: 0.0632, cor: 0.8419, auc: 0.9880\n",
+      "total running time 1743.487956047058\n",
+      "total time 1744.0221991539001\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 30\n",
+      "DataSet 7 valid size 7328 fold 1\n",
+      "dataset valid: 7328 loader valid: 229\n",
+      "loading model model.b3.f1.d7.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.726 time per batch: 0.235\n",
+      "Batch 100 device: cuda time passed: 20.041 time per batch: 0.200\n",
+      "Batch 150 device: cuda time passed: 28.446 time per batch: 0.190\n",
+      "Batch 200 device: cuda time passed: 37.606 time per batch: 0.188\n",
+      "ver 34, iter 0, fold 1, val ll: 0.0641, cor: 0.8352, auc: 0.9876\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.401 time per batch: 0.228\n",
+      "Batch 100 device: cuda time passed: 19.701 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.377 time per batch: 0.189\n",
+      "Batch 200 device: cuda time passed: 37.516 time per batch: 0.188\n",
+      "ver 34, iter 1, fold 1, val ll: 0.0644, cor: 0.8346, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.045 time per batch: 0.221\n",
+      "Batch 100 device: cuda time passed: 19.526 time per batch: 0.195\n",
+      "Batch 150 device: cuda time passed: 28.070 time per batch: 0.187\n",
+      "Batch 200 device: cuda time passed: 36.553 time per batch: 0.183\n",
+      "ver 34, iter 2, fold 1, val ll: 0.0645, cor: 0.8347, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.522 time per batch: 0.230\n",
+      "Batch 100 device: cuda time passed: 20.039 time per batch: 0.200\n",
+      "Batch 150 device: cuda time passed: 28.182 time per batch: 0.188\n",
+      "Batch 200 device: cuda time passed: 36.515 time per batch: 0.183\n",
+      "ver 34, iter 3, fold 1, val ll: 0.0643, cor: 0.8352, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.412 time per batch: 0.228\n",
+      "Batch 100 device: cuda time passed: 19.794 time per batch: 0.198\n",
+      "Batch 150 device: cuda time passed: 27.859 time per batch: 0.186\n",
+      "Batch 200 device: cuda time passed: 35.826 time per batch: 0.179\n",
+      "ver 34, iter 4, fold 1, val ll: 0.0644, cor: 0.8346, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.184 time per batch: 0.224\n",
+      "Batch 100 device: cuda time passed: 19.415 time per batch: 0.194\n",
+      "Batch 150 device: cuda time passed: 27.791 time per batch: 0.185\n",
+      "Batch 200 device: cuda time passed: 36.132 time per batch: 0.181\n",
+      "ver 34, iter 5, fold 1, val ll: 0.0642, cor: 0.8355, auc: 0.9876\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.913 time per batch: 0.218\n",
+      "Batch 100 device: cuda time passed: 20.135 time per batch: 0.201\n",
+      "Batch 150 device: cuda time passed: 28.498 time per batch: 0.190\n",
+      "Batch 200 device: cuda time passed: 36.584 time per batch: 0.183\n",
+      "ver 34, iter 6, fold 1, val ll: 0.0644, cor: 0.8350, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.169 time per batch: 0.223\n",
+      "Batch 100 device: cuda time passed: 19.419 time per batch: 0.194\n",
+      "Batch 150 device: cuda time passed: 27.835 time per batch: 0.186\n",
+      "Batch 200 device: cuda time passed: 36.749 time per batch: 0.184\n",
+      "ver 34, iter 7, fold 1, val ll: 0.0644, cor: 0.8346, auc: 0.9876\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.093 time per batch: 0.222\n",
+      "Batch 100 device: cuda time passed: 19.735 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 27.976 time per batch: 0.187\n",
+      "Batch 200 device: cuda time passed: 36.522 time per batch: 0.183\n",
+      "ver 34, iter 8, fold 1, val ll: 0.0643, cor: 0.8351, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.886 time per batch: 0.218\n",
+      "Batch 100 device: cuda time passed: 19.310 time per batch: 0.193\n",
+      "Batch 150 device: cuda time passed: 27.555 time per batch: 0.184\n",
+      "Batch 200 device: cuda time passed: 35.897 time per batch: 0.179\n",
+      "ver 34, iter 9, fold 1, val ll: 0.0640, cor: 0.8360, auc: 0.9876\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.190 time per batch: 0.224\n",
+      "Batch 100 device: cuda time passed: 19.659 time per batch: 0.197\n",
+      "Batch 150 device: cuda time passed: 28.059 time per batch: 0.187\n",
+      "Batch 200 device: cuda time passed: 36.597 time per batch: 0.183\n",
+      "ver 34, iter 10, fold 1, val ll: 0.0645, cor: 0.8345, auc: 0.9875\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.462 time per batch: 0.229\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 13, fold 1, val ll: 0.0642, cor: 0.8353, auc: 0.9876\n",
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+      "ver 34, iter 31, fold 1, val ll: 0.0645, cor: 0.8347, auc: 0.9875\n",
+      "total running time 1752.2469551563263\n",
+      "total time 3496.7637753486633\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 4\n",
+      "DataSet 7 valid size 7232 fold 2\n",
+      "dataset valid: 7232 loader valid: 226\n",
+      "loading model model.b3.f2.d7.v34\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 0, fold 2, val ll: 0.0603, cor: 0.8423, auc: 0.9893\n",
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+      "ver 34, iter 1, fold 2, val ll: 0.0601, cor: 0.8425, auc: 0.9894\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 200 device: cuda time passed: 35.943 time per batch: 0.180\n",
+      "ver 34, iter 4, fold 2, val ll: 0.0602, cor: 0.8425, auc: 0.9893\n",
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+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 50 device: cuda time passed: 10.998 time per batch: 0.220\n",
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+      "ver 34, iter 28, fold 2, val ll: 0.0602, cor: 0.8424, auc: 0.9894\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 2, val ll: 0.0603, cor: 0.8420, auc: 0.9893\n",
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+      "ver 34, iter 30, fold 2, val ll: 0.0602, cor: 0.8424, auc: 0.9894\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 31, fold 2, val ll: 0.0600, cor: 0.8430, auc: 0.9894\n",
+      "total running time 1731.3292746543884\n",
+      "total time 5228.603754520416\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 14\n",
+      "DataSet 9 valid size 7232 fold 0\n",
+      "dataset valid: 7232 loader valid: 226\n",
+      "loading model model.b3.f0.d9.v34\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 0, fold 0, val ll: 0.0632, cor: 0.8416, auc: 0.9881\n",
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+      "ver 34, iter 1, fold 0, val ll: 0.0629, cor: 0.8419, auc: 0.9883\n",
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+      "ver 34, iter 2, fold 0, val ll: 0.0633, cor: 0.8414, auc: 0.9880\n",
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+      "ver 34, iter 3, fold 0, val ll: 0.0631, cor: 0.8417, auc: 0.9881\n",
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+      "ver 34, iter 4, fold 0, val ll: 0.0634, cor: 0.8412, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 5, fold 0, val ll: 0.0632, cor: 0.8414, auc: 0.9881\n",
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+      "ver 34, iter 6, fold 0, val ll: 0.0634, cor: 0.8411, auc: 0.9881\n",
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+      "ver 34, iter 7, fold 0, val ll: 0.0631, cor: 0.8418, auc: 0.9882\n",
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+      "ver 34, iter 16, fold 0, val ll: 0.0631, cor: 0.8418, auc: 0.9882\n",
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+      "ver 34, iter 17, fold 0, val ll: 0.0631, cor: 0.8416, auc: 0.9882\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 18, fold 0, val ll: 0.0632, cor: 0.8414, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 19, fold 0, val ll: 0.0632, cor: 0.8415, auc: 0.9882\n",
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+      "ver 34, iter 20, fold 0, val ll: 0.0634, cor: 0.8413, auc: 0.9880\n",
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+      "ver 34, iter 21, fold 0, val ll: 0.0630, cor: 0.8421, auc: 0.9881\n",
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+      "ver 34, iter 24, fold 0, val ll: 0.0634, cor: 0.8412, auc: 0.9880\n",
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+      "ver 34, iter 29, fold 0, val ll: 0.0630, cor: 0.8420, auc: 0.9881\n",
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+      "ver 34, iter 30, fold 0, val ll: 0.0632, cor: 0.8416, auc: 0.9881\n",
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+      "ver 34, iter 31, fold 0, val ll: 0.0631, cor: 0.8417, auc: 0.9881\n",
+      "total running time 1487.4923713207245\n",
+      "total time 6716.580273866653\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 30\n",
+      "DataSet 9 valid size 7328 fold 1\n",
+      "dataset valid: 7328 loader valid: 229\n",
+      "loading model model.b3.f1.d9.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.601 time per batch: 0.232\n",
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+      "ver 34, iter 0, fold 1, val ll: 0.0633, cor: 0.8388, auc: 0.9879\n",
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+      "ver 34, iter 1, fold 1, val ll: 0.0634, cor: 0.8387, auc: 0.9879\n",
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+      "ver 34, iter 2, fold 1, val ll: 0.0634, cor: 0.8388, auc: 0.9879\n",
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+      "ver 34, iter 3, fold 1, val ll: 0.0634, cor: 0.8386, auc: 0.9879\n",
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+      "ver 34, iter 4, fold 1, val ll: 0.0632, cor: 0.8390, auc: 0.9879\n",
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+      "ver 34, iter 5, fold 1, val ll: 0.0632, cor: 0.8389, auc: 0.9879\n",
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+      "ver 34, iter 6, fold 1, val ll: 0.0631, cor: 0.8393, auc: 0.9880\n",
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+      "ver 34, iter 7, fold 1, val ll: 0.0634, cor: 0.8385, auc: 0.9879\n",
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+      "ver 34, iter 8, fold 1, val ll: 0.0633, cor: 0.8388, auc: 0.9879\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 200 device: cuda time passed: 36.950 time per batch: 0.185\n",
+      "ver 34, iter 9, fold 1, val ll: 0.0630, cor: 0.8392, auc: 0.9880\n",
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+      "ver 34, iter 10, fold 1, val ll: 0.0634, cor: 0.8387, auc: 0.9878\n",
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+      "ver 34, iter 28, fold 1, val ll: 0.0632, cor: 0.8392, auc: 0.9879\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 1, val ll: 0.0632, cor: 0.8390, auc: 0.9879\n",
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+      "ver 34, iter 30, fold 1, val ll: 0.0633, cor: 0.8389, auc: 0.9879\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.090 time per batch: 0.222\n",
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+      "ver 34, iter 31, fold 1, val ll: 0.0633, cor: 0.8388, auc: 0.9879\n",
+      "total running time 1502.9731421470642\n",
+      "total time 8220.030895471573\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 4\n",
+      "DataSet 9 valid size 7232 fold 2\n",
+      "dataset valid: 7232 loader valid: 226\n",
+      "loading model model.b3.f2.d9.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.523 time per batch: 0.230\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 150 device: cuda time passed: 28.448 time per batch: 0.190\n",
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+      "ver 34, iter 0, fold 2, val ll: 0.0604, cor: 0.8411, auc: 0.9892\n",
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+      "ver 34, iter 1, fold 2, val ll: 0.0603, cor: 0.8412, auc: 0.9893\n",
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+      "ver 34, iter 2, fold 2, val ll: 0.0603, cor: 0.8413, auc: 0.9892\n",
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+      "ver 34, iter 3, fold 2, val ll: 0.0605, cor: 0.8407, auc: 0.9892\n",
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+      "ver 34, iter 4, fold 2, val ll: 0.0604, cor: 0.8411, auc: 0.9891\n",
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+      "ver 34, iter 8, fold 2, val ll: 0.0602, cor: 0.8415, auc: 0.9892\n",
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+      "ver 34, iter 9, fold 2, val ll: 0.0604, cor: 0.8412, auc: 0.9892\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 23, fold 2, val ll: 0.0603, cor: 0.8414, auc: 0.9892\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 28, fold 2, val ll: 0.0604, cor: 0.8409, auc: 0.9892\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 10.969 time per batch: 0.219\n",
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+      "ver 34, iter 29, fold 2, val ll: 0.0602, cor: 0.8415, auc: 0.9893\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 30, fold 2, val ll: 0.0603, cor: 0.8411, auc: 0.9893\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 11.159 time per batch: 0.223\n",
+      "Batch 100 device: cuda time passed: 19.845 time per batch: 0.198\n",
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+      "Batch 200 device: cuda time passed: 36.092 time per batch: 0.180\n",
+      "ver 34, iter 31, fold 2, val ll: 0.0603, cor: 0.8414, auc: 0.9893\n",
+      "total running time 1486.592945575714\n",
+      "total time 9707.101170063019\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 9\n",
+      "DataSet 11 valid size 4384 fold 0\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f0.d11.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.940 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.756 time per batch: 0.148\n",
+      "ver 34, iter 0, fold 0, val ll: 0.0609, cor: 0.8452, auc: 0.9888\n",
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+      "ver 34, iter 1, fold 0, val ll: 0.0607, cor: 0.8453, auc: 0.9889\n",
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+      "ver 34, iter 2, fold 0, val ll: 0.0608, cor: 0.8452, auc: 0.9889\n",
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+      "ver 34, iter 3, fold 0, val ll: 0.0609, cor: 0.8449, auc: 0.9889\n",
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+      "ver 34, iter 4, fold 0, val ll: 0.0608, cor: 0.8455, auc: 0.9889\n",
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+      "ver 34, iter 5, fold 0, val ll: 0.0608, cor: 0.8449, auc: 0.9889\n",
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+      "ver 34, iter 6, fold 0, val ll: 0.0609, cor: 0.8451, auc: 0.9887\n",
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+      "ver 34, iter 8, fold 0, val ll: 0.0608, cor: 0.8456, auc: 0.9888\n",
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+      "ver 34, iter 9, fold 0, val ll: 0.0608, cor: 0.8453, auc: 0.9889\n",
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+      "ver 34, iter 10, fold 0, val ll: 0.0610, cor: 0.8450, auc: 0.9887\n",
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+      "ver 34, iter 11, fold 0, val ll: 0.0608, cor: 0.8451, auc: 0.9889\n",
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+      "ver 34, iter 12, fold 0, val ll: 0.0609, cor: 0.8449, auc: 0.9888\n",
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+      "ver 34, iter 13, fold 0, val ll: 0.0610, cor: 0.8450, auc: 0.9888\n",
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+      "ver 34, iter 15, fold 0, val ll: 0.0610, cor: 0.8448, auc: 0.9888\n",
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+      "ver 34, iter 16, fold 0, val ll: 0.0608, cor: 0.8450, auc: 0.9888\n",
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+      "ver 34, iter 17, fold 0, val ll: 0.0608, cor: 0.8455, auc: 0.9887\n",
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+      "ver 34, iter 18, fold 0, val ll: 0.0609, cor: 0.8449, auc: 0.9889\n",
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+      "ver 34, iter 19, fold 0, val ll: 0.0606, cor: 0.8454, auc: 0.9890\n",
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+      "ver 34, iter 20, fold 0, val ll: 0.0608, cor: 0.8449, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 21, fold 0, val ll: 0.0608, cor: 0.8451, auc: 0.9888\n",
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+      "ver 34, iter 22, fold 0, val ll: 0.0606, cor: 0.8459, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.943 time per batch: 0.159\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 100 device: cuda time passed: 14.021 time per batch: 0.140\n",
+      "ver 34, iter 23, fold 0, val ll: 0.0608, cor: 0.8453, auc: 0.9889\n",
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+      "ver 34, iter 25, fold 0, val ll: 0.0608, cor: 0.8452, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 26, fold 0, val ll: 0.0608, cor: 0.8451, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.599 time per batch: 0.146\n",
+      "ver 34, iter 27, fold 0, val ll: 0.0609, cor: 0.8450, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.639 time per batch: 0.146\n",
+      "ver 34, iter 28, fold 0, val ll: 0.0610, cor: 0.8450, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.980 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 14.528 time per batch: 0.145\n",
+      "ver 34, iter 29, fold 0, val ll: 0.0609, cor: 0.8450, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.133 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.503 time per batch: 0.145\n",
+      "ver 34, iter 30, fold 0, val ll: 0.0607, cor: 0.8453, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.069 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.106 time per batch: 0.141\n",
+      "ver 34, iter 31, fold 0, val ll: 0.0609, cor: 0.8450, auc: 0.9888\n",
+      "total running time 741.6375591754913\n",
+      "total time 10448.977521657944\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 12\n",
+      "DataSet 11 valid size 4288 fold 1\n",
+      "dataset valid: 4288 loader valid: 134\n",
+      "loading model model.b3.f1.d11.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.855 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 13.890 time per batch: 0.139\n",
+      "ver 34, iter 0, fold 1, val ll: 0.0597, cor: 0.8468, auc: 0.9897\n",
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+      "ver 34, iter 1, fold 1, val ll: 0.0598, cor: 0.8465, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 1, val ll: 0.0597, cor: 0.8467, auc: 0.9898\n",
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+      "ver 34, iter 3, fold 1, val ll: 0.0596, cor: 0.8468, auc: 0.9899\n",
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+      "ver 34, iter 4, fold 1, val ll: 0.0597, cor: 0.8469, auc: 0.9898\n",
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+      "ver 34, iter 5, fold 1, val ll: 0.0597, cor: 0.8468, auc: 0.9897\n",
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+      "ver 34, iter 6, fold 1, val ll: 0.0598, cor: 0.8463, auc: 0.9896\n",
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+      "ver 34, iter 8, fold 1, val ll: 0.0599, cor: 0.8462, auc: 0.9897\n",
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+      "ver 34, iter 9, fold 1, val ll: 0.0594, cor: 0.8476, auc: 0.9898\n",
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+      "ver 34, iter 10, fold 1, val ll: 0.0597, cor: 0.8466, auc: 0.9898\n",
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+      "ver 34, iter 18, fold 1, val ll: 0.0597, cor: 0.8469, auc: 0.9897\n",
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+      "ver 34, iter 19, fold 1, val ll: 0.0596, cor: 0.8471, auc: 0.9897\n",
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+      "ver 34, iter 20, fold 1, val ll: 0.0598, cor: 0.8462, auc: 0.9897\n",
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+      "ver 34, iter 21, fold 1, val ll: 0.0598, cor: 0.8464, auc: 0.9897\n",
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+      "ver 34, iter 23, fold 1, val ll: 0.0597, cor: 0.8470, auc: 0.9897\n",
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+      "ver 34, iter 24, fold 1, val ll: 0.0595, cor: 0.8471, auc: 0.9899\n",
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+      "ver 34, iter 25, fold 1, val ll: 0.0597, cor: 0.8466, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 13.988 time per batch: 0.140\n",
+      "ver 34, iter 26, fold 1, val ll: 0.0596, cor: 0.8471, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.249 time per batch: 0.142\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 27, fold 1, val ll: 0.0599, cor: 0.8462, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.806 time per batch: 0.156\n",
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+      "ver 34, iter 28, fold 1, val ll: 0.0598, cor: 0.8464, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.158 time per batch: 0.163\n",
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+      "ver 34, iter 29, fold 1, val ll: 0.0598, cor: 0.8465, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.615 time per batch: 0.172\n",
+      "Batch 100 device: cuda time passed: 14.820 time per batch: 0.148\n",
+      "ver 34, iter 30, fold 1, val ll: 0.0594, cor: 0.8474, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.738 time per batch: 0.175\n",
+      "Batch 100 device: cuda time passed: 15.174 time per batch: 0.152\n",
+      "ver 34, iter 31, fold 1, val ll: 0.0595, cor: 0.8472, auc: 0.9898\n",
+      "total running time 721.0183691978455\n",
+      "total time 11170.231662034988\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 27\n",
+      "DataSet 11 valid size 4416 fold 2\n",
+      "dataset valid: 4416 loader valid: 138\n",
+      "loading model model.b3.f2.d11.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.321 time per batch: 0.166\n",
+      "Batch 100 device: cuda time passed: 14.535 time per batch: 0.145\n",
+      "ver 34, iter 0, fold 2, val ll: 0.0598, cor: 0.8435, auc: 0.9894\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 1, fold 2, val ll: 0.0597, cor: 0.8432, auc: 0.9895\n",
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+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 31, fold 2, val ll: 0.0599, cor: 0.8432, auc: 0.9894\n",
+      "total running time 752.1568894386292\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "total time 11922.615085601807\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 11 valid size 4352 fold 3\n",
+      "dataset valid: 4352 loader valid: 136\n",
+      "loading model model.b3.f3.d11.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.425 time per batch: 0.168\n",
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+      "ver 34, iter 0, fold 3, val ll: 0.0630, cor: 0.8408, auc: 0.9887\n",
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+      "ver 34, iter 1, fold 3, val ll: 0.0631, cor: 0.8410, auc: 0.9886\n",
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+      "ver 34, iter 2, fold 3, val ll: 0.0632, cor: 0.8404, auc: 0.9887\n",
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+      "ver 34, iter 3, fold 3, val ll: 0.0629, cor: 0.8410, auc: 0.9887\n",
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+      "ver 34, iter 4, fold 3, val ll: 0.0629, cor: 0.8410, auc: 0.9888\n",
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+      "ver 34, iter 5, fold 3, val ll: 0.0627, cor: 0.8414, auc: 0.9888\n",
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+      "ver 34, iter 6, fold 3, val ll: 0.0631, cor: 0.8411, auc: 0.9887\n",
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+      "ver 34, iter 7, fold 3, val ll: 0.0627, cor: 0.8417, auc: 0.9888\n",
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+      "ver 34, iter 8, fold 3, val ll: 0.0631, cor: 0.8408, auc: 0.9886\n",
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+      "ver 34, iter 9, fold 3, val ll: 0.0630, cor: 0.8409, auc: 0.9886\n",
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+      "ver 34, iter 10, fold 3, val ll: 0.0631, cor: 0.8406, auc: 0.9886\n",
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+      "ver 34, iter 11, fold 3, val ll: 0.0628, cor: 0.8411, auc: 0.9888\n",
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+      "ver 34, iter 13, fold 3, val ll: 0.0630, cor: 0.8407, auc: 0.9887\n",
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+      "ver 34, iter 14, fold 3, val ll: 0.0629, cor: 0.8410, auc: 0.9888\n",
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+      "ver 34, iter 15, fold 3, val ll: 0.0632, cor: 0.8404, auc: 0.9886\n",
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+      "ver 34, iter 18, fold 3, val ll: 0.0630, cor: 0.8410, auc: 0.9886\n",
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+      "ver 34, iter 23, fold 3, val ll: 0.0631, cor: 0.8409, auc: 0.9885\n",
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+      "ver 34, iter 25, fold 3, val ll: 0.0630, cor: 0.8410, auc: 0.9887\n",
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+      "ver 34, iter 26, fold 3, val ll: 0.0629, cor: 0.8409, auc: 0.9887\n",
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+      "ver 34, iter 27, fold 3, val ll: 0.0631, cor: 0.8409, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 28, fold 3, val ll: 0.0629, cor: 0.8409, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 3, val ll: 0.0630, cor: 0.8409, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.833 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 13.972 time per batch: 0.140\n",
+      "ver 34, iter 30, fold 3, val ll: 0.0632, cor: 0.8405, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.679 time per batch: 0.174\n",
+      "Batch 100 device: cuda time passed: 14.658 time per batch: 0.147\n",
+      "ver 34, iter 31, fold 3, val ll: 0.0629, cor: 0.8412, auc: 0.9887\n",
+      "total running time 734.1475803852081\n",
+      "total time 12656.995476007462\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 11 valid size 4384 fold 4\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f4.d11.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.537 time per batch: 0.151\n",
+      "Batch 100 device: cuda time passed: 14.791 time per batch: 0.148\n",
+      "ver 34, iter 0, fold 4, val ll: 0.0621, cor: 0.8422, auc: 0.9883\n",
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+      "ver 34, iter 1, fold 4, val ll: 0.0621, cor: 0.8425, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 4, val ll: 0.0621, cor: 0.8424, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.949 time per batch: 0.159\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 100 device: cuda time passed: 14.614 time per batch: 0.146\n",
+      "ver 34, iter 3, fold 4, val ll: 0.0621, cor: 0.8423, auc: 0.9882\n",
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+      "ver 34, iter 4, fold 4, val ll: 0.0621, cor: 0.8424, auc: 0.9883\n",
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+      "ver 34, iter 5, fold 4, val ll: 0.0622, cor: 0.8423, auc: 0.9881\n",
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+      "ver 34, iter 6, fold 4, val ll: 0.0621, cor: 0.8422, auc: 0.9882\n",
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+      "ver 34, iter 9, fold 4, val ll: 0.0623, cor: 0.8420, auc: 0.9881\n",
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+      "ver 34, iter 14, fold 4, val ll: 0.0620, cor: 0.8421, auc: 0.9884\n",
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+      "ver 34, iter 24, fold 4, val ll: 0.0621, cor: 0.8421, auc: 0.9883\n",
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+      "ver 34, iter 25, fold 4, val ll: 0.0621, cor: 0.8424, auc: 0.9882\n",
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+      "ver 34, iter 26, fold 4, val ll: 0.0621, cor: 0.8422, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 27, fold 4, val ll: 0.0620, cor: 0.8426, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 28, fold 4, val ll: 0.0621, cor: 0.8424, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 4, val ll: 0.0620, cor: 0.8427, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.845 time per batch: 0.148\n",
+      "ver 34, iter 30, fold 4, val ll: 0.0620, cor: 0.8426, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.285 time per batch: 0.166\n",
+      "Batch 100 device: cuda time passed: 14.113 time per batch: 0.141\n",
+      "ver 34, iter 31, fold 4, val ll: 0.0621, cor: 0.8423, auc: 0.9882\n",
+      "total running time 742.8772552013397\n",
+      "total time 13400.111248254776\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 9\n",
+      "DataSet 12 valid size 4384 fold 0\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f0.d12.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.200 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.845 time per batch: 0.148\n",
+      "ver 34, iter 0, fold 0, val ll: 0.0608, cor: 0.8451, auc: 0.9887\n",
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+      "ver 34, iter 1, fold 0, val ll: 0.0610, cor: 0.8443, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 0, val ll: 0.0609, cor: 0.8442, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 3, fold 0, val ll: 0.0608, cor: 0.8449, auc: 0.9888\n",
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+      "ver 34, iter 4, fold 0, val ll: 0.0608, cor: 0.8444, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 5, fold 0, val ll: 0.0608, cor: 0.8446, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 6, fold 0, val ll: 0.0611, cor: 0.8444, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.206 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.944 time per batch: 0.149\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 7, fold 0, val ll: 0.0609, cor: 0.8444, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 8, fold 0, val ll: 0.0611, cor: 0.8444, auc: 0.9886\n",
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+      "ver 34, iter 9, fold 0, val ll: 0.0610, cor: 0.8446, auc: 0.9888\n",
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+      "ver 34, iter 10, fold 0, val ll: 0.0610, cor: 0.8447, auc: 0.9887\n",
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+      "ver 34, iter 11, fold 0, val ll: 0.0611, cor: 0.8444, auc: 0.9887\n",
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+      "ver 34, iter 12, fold 0, val ll: 0.0609, cor: 0.8446, auc: 0.9888\n",
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+      "ver 34, iter 13, fold 0, val ll: 0.0608, cor: 0.8447, auc: 0.9888\n",
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+      "ver 34, iter 14, fold 0, val ll: 0.0609, cor: 0.8445, auc: 0.9888\n",
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+      "ver 34, iter 15, fold 0, val ll: 0.0610, cor: 0.8446, auc: 0.9887\n",
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+      "ver 34, iter 16, fold 0, val ll: 0.0609, cor: 0.8448, auc: 0.9887\n",
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+      "ver 34, iter 17, fold 0, val ll: 0.0610, cor: 0.8442, auc: 0.9887\n",
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+      "ver 34, iter 18, fold 0, val ll: 0.0608, cor: 0.8448, auc: 0.9888\n",
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+      "ver 34, iter 19, fold 0, val ll: 0.0609, cor: 0.8445, auc: 0.9888\n",
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+      "ver 34, iter 20, fold 0, val ll: 0.0611, cor: 0.8443, auc: 0.9886\n",
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+      "ver 34, iter 21, fold 0, val ll: 0.0609, cor: 0.8446, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 22, fold 0, val ll: 0.0610, cor: 0.8447, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 23, fold 0, val ll: 0.0610, cor: 0.8445, auc: 0.9888\n",
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+      "ver 34, iter 24, fold 0, val ll: 0.0612, cor: 0.8440, auc: 0.9887\n",
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+      "ver 34, iter 25, fold 0, val ll: 0.0608, cor: 0.8451, auc: 0.9888\n",
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+      "ver 34, iter 26, fold 0, val ll: 0.0608, cor: 0.8449, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.919 time per batch: 0.158\n",
+      "Batch 100 device: cuda time passed: 14.240 time per batch: 0.142\n",
+      "ver 34, iter 27, fold 0, val ll: 0.0607, cor: 0.8450, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.292 time per batch: 0.146\n",
+      "Batch 100 device: cuda time passed: 14.701 time per batch: 0.147\n",
+      "ver 34, iter 28, fold 0, val ll: 0.0608, cor: 0.8449, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 13.886 time per batch: 0.139\n",
+      "ver 34, iter 29, fold 0, val ll: 0.0609, cor: 0.8444, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.837 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.618 time per batch: 0.146\n",
+      "ver 34, iter 30, fold 0, val ll: 0.0609, cor: 0.8448, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.908 time per batch: 0.158\n",
+      "Batch 100 device: cuda time passed: 14.168 time per batch: 0.142\n",
+      "ver 34, iter 31, fold 0, val ll: 0.0609, cor: 0.8445, auc: 0.9888\n",
+      "total running time 743.3103971481323\n",
+      "total time 14143.665662765503\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 12\n",
+      "DataSet 12 valid size 4288 fold 1\n",
+      "dataset valid: 4288 loader valid: 134\n",
+      "loading model model.b3.f1.d12.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.167 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.378 time per batch: 0.144\n",
+      "ver 34, iter 0, fold 1, val ll: 0.0597, cor: 0.8453, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 1, fold 1, val ll: 0.0594, cor: 0.8461, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 1, val ll: 0.0597, cor: 0.8455, auc: 0.9897\n",
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+      "ver 34, iter 3, fold 1, val ll: 0.0595, cor: 0.8458, auc: 0.9897\n",
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+      "ver 34, iter 4, fold 1, val ll: 0.0597, cor: 0.8456, auc: 0.9897\n",
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+      "ver 34, iter 5, fold 1, val ll: 0.0597, cor: 0.8454, auc: 0.9898\n",
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+      "ver 34, iter 6, fold 1, val ll: 0.0596, cor: 0.8457, auc: 0.9897\n",
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+      "ver 34, iter 7, fold 1, val ll: 0.0597, cor: 0.8454, auc: 0.9897\n",
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+      "ver 34, iter 8, fold 1, val ll: 0.0597, cor: 0.8454, auc: 0.9897\n",
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+      "ver 34, iter 9, fold 1, val ll: 0.0598, cor: 0.8453, auc: 0.9897\n",
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+      "ver 34, iter 10, fold 1, val ll: 0.0596, cor: 0.8456, auc: 0.9897\n",
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+      "ver 34, iter 11, fold 1, val ll: 0.0595, cor: 0.8461, auc: 0.9898\n",
+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 50 device: cuda time passed: 8.393 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 14.742 time per batch: 0.147\n",
+      "ver 34, iter 12, fold 1, val ll: 0.0595, cor: 0.8458, auc: 0.9898\n",
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+      "ver 34, iter 14, fold 1, val ll: 0.0594, cor: 0.8458, auc: 0.9898\n",
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+      "ver 34, iter 15, fold 1, val ll: 0.0596, cor: 0.8456, auc: 0.9897\n",
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+      "ver 34, iter 16, fold 1, val ll: 0.0596, cor: 0.8457, auc: 0.9898\n",
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+      "ver 34, iter 17, fold 1, val ll: 0.0595, cor: 0.8459, auc: 0.9897\n",
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+      "ver 34, iter 25, fold 1, val ll: 0.0593, cor: 0.8464, auc: 0.9898\n",
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+      "ver 34, iter 26, fold 1, val ll: 0.0597, cor: 0.8456, auc: 0.9897\n",
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+      "ver 34, iter 27, fold 1, val ll: 0.0592, cor: 0.8466, auc: 0.9899\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 28, fold 1, val ll: 0.0595, cor: 0.8456, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 1, val ll: 0.0595, cor: 0.8462, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 30, fold 1, val ll: 0.0597, cor: 0.8455, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.218 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.506 time per batch: 0.145\n",
+      "ver 34, iter 31, fold 1, val ll: 0.0595, cor: 0.8458, auc: 0.9898\n",
+      "total running time 723.6225900650024\n",
+      "total time 14867.529915571213\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 27\n",
+      "DataSet 12 valid size 4416 fold 2\n",
+      "dataset valid: 4416 loader valid: 138\n",
+      "loading model model.b3.f2.d12.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.349 time per batch: 0.167\n",
+      "Batch 100 device: cuda time passed: 14.921 time per batch: 0.149\n",
+      "ver 34, iter 0, fold 2, val ll: 0.0605, cor: 0.8428, auc: 0.9889\n",
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+      "ver 34, iter 1, fold 2, val ll: 0.0600, cor: 0.8438, auc: 0.9891\n",
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+      "ver 34, iter 2, fold 2, val ll: 0.0603, cor: 0.8434, auc: 0.9890\n",
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+      "ver 34, iter 3, fold 2, val ll: 0.0601, cor: 0.8436, auc: 0.9891\n",
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+      "ver 34, iter 4, fold 2, val ll: 0.0604, cor: 0.8432, auc: 0.9888\n",
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+      "ver 34, iter 5, fold 2, val ll: 0.0603, cor: 0.8434, auc: 0.9890\n",
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+      "ver 34, iter 6, fold 2, val ll: 0.0600, cor: 0.8438, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 7, fold 2, val ll: 0.0603, cor: 0.8434, auc: 0.9889\n",
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+      "ver 34, iter 8, fold 2, val ll: 0.0600, cor: 0.8439, auc: 0.9890\n",
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+      "ver 34, iter 9, fold 2, val ll: 0.0602, cor: 0.8433, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 10, fold 2, val ll: 0.0604, cor: 0.8427, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 11, fold 2, val ll: 0.0603, cor: 0.8435, auc: 0.9889\n",
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+      "ver 34, iter 12, fold 2, val ll: 0.0603, cor: 0.8434, auc: 0.9890\n",
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+      "ver 34, iter 13, fold 2, val ll: 0.0602, cor: 0.8432, auc: 0.9891\n",
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+      "ver 34, iter 14, fold 2, val ll: 0.0604, cor: 0.8429, auc: 0.9889\n",
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+      "ver 34, iter 15, fold 2, val ll: 0.0603, cor: 0.8435, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.264 time per batch: 0.165\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 100 device: cuda time passed: 15.089 time per batch: 0.151\n",
+      "ver 34, iter 16, fold 2, val ll: 0.0605, cor: 0.8425, auc: 0.9890\n",
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+      "ver 34, iter 17, fold 2, val ll: 0.0603, cor: 0.8430, auc: 0.9890\n",
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+      "ver 34, iter 18, fold 2, val ll: 0.0604, cor: 0.8428, auc: 0.9889\n",
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+      "ver 34, iter 19, fold 2, val ll: 0.0603, cor: 0.8435, auc: 0.9889\n",
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+      "ver 34, iter 20, fold 2, val ll: 0.0602, cor: 0.8432, auc: 0.9891\n",
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+      "ver 34, iter 21, fold 2, val ll: 0.0603, cor: 0.8429, auc: 0.9889\n",
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+      "ver 34, iter 22, fold 2, val ll: 0.0601, cor: 0.8436, auc: 0.9891\n",
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+      "ver 34, iter 23, fold 2, val ll: 0.0599, cor: 0.8439, auc: 0.9892\n",
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+      "ver 34, iter 24, fold 2, val ll: 0.0604, cor: 0.8428, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 25, fold 2, val ll: 0.0605, cor: 0.8427, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 26, fold 2, val ll: 0.0600, cor: 0.8438, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 27, fold 2, val ll: 0.0604, cor: 0.8430, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.776 time per batch: 0.148\n",
+      "ver 34, iter 28, fold 2, val ll: 0.0604, cor: 0.8432, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.776 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 14.609 time per batch: 0.146\n",
+      "ver 34, iter 29, fold 2, val ll: 0.0602, cor: 0.8436, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.443 time per batch: 0.169\n",
+      "Batch 100 device: cuda time passed: 15.589 time per batch: 0.156\n",
+      "ver 34, iter 30, fold 2, val ll: 0.0600, cor: 0.8438, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.807 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 14.568 time per batch: 0.146\n",
+      "ver 34, iter 31, fold 2, val ll: 0.0603, cor: 0.8431, auc: 0.9889\n",
+      "total running time 756.8606667518616\n",
+      "total time 15624.633174657822\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 12 valid size 4352 fold 3\n",
+      "dataset valid: 4352 loader valid: 136\n",
+      "loading model model.b3.f3.d12.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.148 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.303 time per batch: 0.143\n",
+      "ver 34, iter 0, fold 3, val ll: 0.0624, cor: 0.8412, auc: 0.9887\n",
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+      "ver 34, iter 1, fold 3, val ll: 0.0628, cor: 0.8402, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 3, val ll: 0.0627, cor: 0.8401, auc: 0.9887\n",
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+      "ver 34, iter 3, fold 3, val ll: 0.0629, cor: 0.8401, auc: 0.9885\n",
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+      "ver 34, iter 4, fold 3, val ll: 0.0626, cor: 0.8405, auc: 0.9887\n",
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+      "ver 34, iter 5, fold 3, val ll: 0.0627, cor: 0.8406, auc: 0.9886\n",
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+      "ver 34, iter 6, fold 3, val ll: 0.0627, cor: 0.8400, auc: 0.9886\n",
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+      "ver 34, iter 7, fold 3, val ll: 0.0628, cor: 0.8399, auc: 0.9887\n",
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+      "ver 34, iter 9, fold 3, val ll: 0.0625, cor: 0.8410, auc: 0.9887\n",
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+      "ver 34, iter 10, fold 3, val ll: 0.0626, cor: 0.8407, auc: 0.9887\n",
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+      "ver 34, iter 11, fold 3, val ll: 0.0629, cor: 0.8402, auc: 0.9885\n",
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+      "ver 34, iter 16, fold 3, val ll: 0.0625, cor: 0.8409, auc: 0.9887\n",
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+      "ver 34, iter 17, fold 3, val ll: 0.0628, cor: 0.8407, auc: 0.9885\n",
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+      "ver 34, iter 18, fold 3, val ll: 0.0625, cor: 0.8409, auc: 0.9887\n",
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+      "ver 34, iter 19, fold 3, val ll: 0.0628, cor: 0.8401, auc: 0.9887\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 20, fold 3, val ll: 0.0627, cor: 0.8404, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 21, fold 3, val ll: 0.0628, cor: 0.8402, auc: 0.9887\n",
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+      "ver 34, iter 22, fold 3, val ll: 0.0627, cor: 0.8403, auc: 0.9887\n",
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+      "ver 34, iter 23, fold 3, val ll: 0.0627, cor: 0.8403, auc: 0.9888\n",
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+      "ver 34, iter 24, fold 3, val ll: 0.0623, cor: 0.8408, auc: 0.9888\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.826 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 15.779 time per batch: 0.158\n",
+      "ver 34, iter 25, fold 3, val ll: 0.0627, cor: 0.8404, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 26, fold 3, val ll: 0.0627, cor: 0.8404, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 27, fold 3, val ll: 0.0627, cor: 0.8403, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.072 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.356 time per batch: 0.144\n",
+      "ver 34, iter 28, fold 3, val ll: 0.0627, cor: 0.8403, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 29, fold 3, val ll: 0.0627, cor: 0.8403, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.732 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.896 time per batch: 0.149\n",
+      "ver 34, iter 30, fold 3, val ll: 0.0626, cor: 0.8407, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.028 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.561 time per batch: 0.146\n",
+      "ver 34, iter 31, fold 3, val ll: 0.0625, cor: 0.8406, auc: 0.9888\n",
+      "total running time 748.939469575882\n",
+      "total time 16373.82175731659\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 12 valid size 4384 fold 4\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f4.d12.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.040 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 15.289 time per batch: 0.153\n",
+      "ver 34, iter 0, fold 4, val ll: 0.0611, cor: 0.8442, auc: 0.9884\n",
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+      "ver 34, iter 1, fold 4, val ll: 0.0613, cor: 0.8441, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 4, val ll: 0.0614, cor: 0.8440, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 3, fold 4, val ll: 0.0613, cor: 0.8439, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 4, fold 4, val ll: 0.0613, cor: 0.8437, auc: 0.9883\n",
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+      "ver 34, iter 5, fold 4, val ll: 0.0612, cor: 0.8440, auc: 0.9883\n",
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+      "ver 34, iter 6, fold 4, val ll: 0.0611, cor: 0.8442, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 7, fold 4, val ll: 0.0612, cor: 0.8443, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 8, fold 4, val ll: 0.0612, cor: 0.8443, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 9, fold 4, val ll: 0.0612, cor: 0.8440, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 10, fold 4, val ll: 0.0613, cor: 0.8441, auc: 0.9883\n",
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+      "ver 34, iter 11, fold 4, val ll: 0.0614, cor: 0.8436, auc: 0.9884\n",
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+      "ver 34, iter 12, fold 4, val ll: 0.0612, cor: 0.8447, auc: 0.9883\n",
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+      "ver 34, iter 13, fold 4, val ll: 0.0610, cor: 0.8446, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 14, fold 4, val ll: 0.0613, cor: 0.8438, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 15, fold 4, val ll: 0.0613, cor: 0.8442, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 16, fold 4, val ll: 0.0614, cor: 0.8439, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.542 time per batch: 0.171\n",
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+      "ver 34, iter 17, fold 4, val ll: 0.0611, cor: 0.8443, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 18, fold 4, val ll: 0.0613, cor: 0.8440, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.154 time per batch: 0.142\n",
+      "ver 34, iter 19, fold 4, val ll: 0.0612, cor: 0.8442, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 20, fold 4, val ll: 0.0610, cor: 0.8451, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 21, fold 4, val ll: 0.0613, cor: 0.8443, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 22, fold 4, val ll: 0.0613, cor: 0.8443, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 23, fold 4, val ll: 0.0613, cor: 0.8440, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.428 time per batch: 0.169\n",
+      "Batch 100 device: cuda time passed: 14.389 time per batch: 0.144\n",
+      "ver 34, iter 24, fold 4, val ll: 0.0612, cor: 0.8442, auc: 0.9884\n",
+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 50 device: cuda time passed: 8.386 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 14.843 time per batch: 0.148\n",
+      "ver 34, iter 25, fold 4, val ll: 0.0610, cor: 0.8443, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.176 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.860 time per batch: 0.149\n",
+      "ver 34, iter 26, fold 4, val ll: 0.0614, cor: 0.8437, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.796 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 14.797 time per batch: 0.148\n",
+      "ver 34, iter 27, fold 4, val ll: 0.0611, cor: 0.8441, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.082 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 14.366 time per batch: 0.144\n",
+      "ver 34, iter 28, fold 4, val ll: 0.0611, cor: 0.8444, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.765 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.102 time per batch: 0.141\n",
+      "ver 34, iter 29, fold 4, val ll: 0.0613, cor: 0.8439, auc: 0.9884\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.825 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.505 time per batch: 0.145\n",
+      "ver 34, iter 30, fold 4, val ll: 0.0612, cor: 0.8438, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.774 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.729 time per batch: 0.147\n",
+      "ver 34, iter 31, fold 4, val ll: 0.0612, cor: 0.8444, auc: 0.9884\n",
+      "total running time 753.5520458221436\n",
+      "total time 17127.620171546936\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 9\n",
+      "DataSet 13 valid size 4384 fold 0\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f0.d13.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.140 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.948 time per batch: 0.149\n",
+      "ver 34, iter 0, fold 0, val ll: 0.0607, cor: 0.8444, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 1, fold 0, val ll: 0.0609, cor: 0.8441, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 0, val ll: 0.0609, cor: 0.8436, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 3, fold 0, val ll: 0.0607, cor: 0.8445, auc: 0.9890\n",
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+      "ver 34, iter 4, fold 0, val ll: 0.0609, cor: 0.8440, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 5, fold 0, val ll: 0.0609, cor: 0.8441, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.989 time per batch: 0.150\n",
+      "ver 34, iter 6, fold 0, val ll: 0.0607, cor: 0.8443, auc: 0.9891\n",
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+      "ver 34, iter 7, fold 0, val ll: 0.0606, cor: 0.8448, auc: 0.9890\n",
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+      "ver 34, iter 8, fold 0, val ll: 0.0607, cor: 0.8443, auc: 0.9891\n",
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+      "ver 34, iter 9, fold 0, val ll: 0.0609, cor: 0.8439, auc: 0.9889\n",
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+      "ver 34, iter 10, fold 0, val ll: 0.0608, cor: 0.8439, auc: 0.9890\n",
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+      "ver 34, iter 11, fold 0, val ll: 0.0610, cor: 0.8437, auc: 0.9889\n",
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+      "ver 34, iter 16, fold 0, val ll: 0.0607, cor: 0.8443, auc: 0.9890\n",
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+      "ver 34, iter 17, fold 0, val ll: 0.0608, cor: 0.8442, auc: 0.9890\n",
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+      "ver 34, iter 18, fold 0, val ll: 0.0610, cor: 0.8434, auc: 0.9890\n",
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+      "ver 34, iter 20, fold 0, val ll: 0.0608, cor: 0.8441, auc: 0.9890\n",
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+      "ver 34, iter 21, fold 0, val ll: 0.0609, cor: 0.8440, auc: 0.9890\n",
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+      "ver 34, iter 22, fold 0, val ll: 0.0609, cor: 0.8440, auc: 0.9889\n",
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+      "ver 34, iter 23, fold 0, val ll: 0.0608, cor: 0.8442, auc: 0.9890\n",
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+      "ver 34, iter 24, fold 0, val ll: 0.0609, cor: 0.8443, auc: 0.9889\n",
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+      "ver 34, iter 25, fold 0, val ll: 0.0606, cor: 0.8443, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 26, fold 0, val ll: 0.0608, cor: 0.8440, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.166 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.509 time per batch: 0.145\n",
+      "ver 34, iter 27, fold 0, val ll: 0.0606, cor: 0.8443, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.502 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 14.728 time per batch: 0.147\n",
+      "ver 34, iter 28, fold 0, val ll: 0.0608, cor: 0.8443, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.983 time per batch: 0.160\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 100 device: cuda time passed: 14.007 time per batch: 0.140\n",
+      "ver 34, iter 29, fold 0, val ll: 0.0608, cor: 0.8444, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.859 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.598 time per batch: 0.146\n",
+      "ver 34, iter 30, fold 0, val ll: 0.0610, cor: 0.8436, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.346 time per batch: 0.167\n",
+      "Batch 100 device: cuda time passed: 14.582 time per batch: 0.146\n",
+      "ver 34, iter 31, fold 0, val ll: 0.0610, cor: 0.8437, auc: 0.9889\n",
+      "total running time 753.0968706607819\n",
+      "total time 17880.959055662155\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 12\n",
+      "DataSet 13 valid size 4288 fold 1\n",
+      "dataset valid: 4288 loader valid: 134\n",
+      "loading model model.b3.f1.d13.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.968 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.655 time per batch: 0.147\n",
+      "ver 34, iter 0, fold 1, val ll: 0.0600, cor: 0.8442, auc: 0.9897\n",
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+      "ver 34, iter 1, fold 1, val ll: 0.0597, cor: 0.8452, auc: 0.9897\n",
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+      "ver 34, iter 2, fold 1, val ll: 0.0599, cor: 0.8446, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 3, fold 1, val ll: 0.0598, cor: 0.8447, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 4, fold 1, val ll: 0.0599, cor: 0.8447, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 5, fold 1, val ll: 0.0598, cor: 0.8449, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 6, fold 1, val ll: 0.0600, cor: 0.8445, auc: 0.9897\n",
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+      "ver 34, iter 7, fold 1, val ll: 0.0600, cor: 0.8443, auc: 0.9896\n",
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+      "ver 34, iter 8, fold 1, val ll: 0.0599, cor: 0.8448, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 9, fold 1, val ll: 0.0599, cor: 0.8450, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 10, fold 1, val ll: 0.0600, cor: 0.8444, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.838 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.042 time per batch: 0.140\n",
+      "ver 34, iter 11, fold 1, val ll: 0.0601, cor: 0.8445, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.105 time per batch: 0.162\n",
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+      "ver 34, iter 12, fold 1, val ll: 0.0598, cor: 0.8448, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.542 time per batch: 0.151\n",
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+      "ver 34, iter 13, fold 1, val ll: 0.0600, cor: 0.8439, auc: 0.9897\n",
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+      "ver 34, iter 14, fold 1, val ll: 0.0599, cor: 0.8448, auc: 0.9897\n",
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+      "ver 34, iter 15, fold 1, val ll: 0.0597, cor: 0.8452, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 16, fold 1, val ll: 0.0598, cor: 0.8451, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 17, fold 1, val ll: 0.0600, cor: 0.8447, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.483 time per batch: 0.150\n",
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+      "ver 34, iter 18, fold 1, val ll: 0.0597, cor: 0.8449, auc: 0.9898\n",
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+      "ver 34, iter 19, fold 1, val ll: 0.0598, cor: 0.8447, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 20, fold 1, val ll: 0.0599, cor: 0.8447, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 21, fold 1, val ll: 0.0599, cor: 0.8447, auc: 0.9897\n",
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+      "ver 34, iter 22, fold 1, val ll: 0.0598, cor: 0.8450, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 23, fold 1, val ll: 0.0598, cor: 0.8451, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 24, fold 1, val ll: 0.0598, cor: 0.8448, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 25, fold 1, val ll: 0.0599, cor: 0.8446, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.575 time per batch: 0.171\n",
+      "Batch 100 device: cuda time passed: 15.369 time per batch: 0.154\n",
+      "ver 34, iter 26, fold 1, val ll: 0.0600, cor: 0.8445, auc: 0.9896\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.869 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.553 time per batch: 0.146\n",
+      "ver 34, iter 27, fold 1, val ll: 0.0598, cor: 0.8447, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.820 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 13.851 time per batch: 0.139\n",
+      "ver 34, iter 28, fold 1, val ll: 0.0599, cor: 0.8447, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.923 time per batch: 0.158\n",
+      "Batch 100 device: cuda time passed: 14.560 time per batch: 0.146\n",
+      "ver 34, iter 29, fold 1, val ll: 0.0598, cor: 0.8449, auc: 0.9898\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.738 time per batch: 0.175\n",
+      "Batch 100 device: cuda time passed: 14.646 time per batch: 0.146\n",
+      "ver 34, iter 30, fold 1, val ll: 0.0600, cor: 0.8442, auc: 0.9897\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.081 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 14.355 time per batch: 0.144\n",
+      "ver 34, iter 31, fold 1, val ll: 0.0598, cor: 0.8446, auc: 0.9897\n",
+      "total running time 734.7177088260651\n",
+      "total time 18615.920258760452\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 27\n",
+      "DataSet 13 valid size 4416 fold 2\n",
+      "dataset valid: 4416 loader valid: 138\n",
+      "loading model model.b3.f2.d13.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.169 time per batch: 0.163\n",
+      "Batch 100 device: cuda time passed: 14.845 time per batch: 0.148\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ver 34, iter 0, fold 2, val ll: 0.0602, cor: 0.8434, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.255 time per batch: 0.165\n",
+      "Batch 100 device: cuda time passed: 14.489 time per batch: 0.145\n",
+      "ver 34, iter 1, fold 2, val ll: 0.0601, cor: 0.8435, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 2, fold 2, val ll: 0.0602, cor: 0.8432, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 3, fold 2, val ll: 0.0601, cor: 0.8439, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.998 time per batch: 0.160\n",
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+      "ver 34, iter 4, fold 2, val ll: 0.0602, cor: 0.8431, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.098 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 15.145 time per batch: 0.151\n",
+      "ver 34, iter 5, fold 2, val ll: 0.0603, cor: 0.8429, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 15.346 time per batch: 0.153\n",
+      "ver 34, iter 6, fold 2, val ll: 0.0600, cor: 0.8437, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 7, fold 2, val ll: 0.0601, cor: 0.8434, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.288 time per batch: 0.166\n",
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+      "ver 34, iter 8, fold 2, val ll: 0.0600, cor: 0.8437, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.228 time per batch: 0.165\n",
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+      "ver 34, iter 9, fold 2, val ll: 0.0601, cor: 0.8434, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.901 time per batch: 0.158\n",
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+      "ver 34, iter 10, fold 2, val ll: 0.0601, cor: 0.8440, auc: 0.9890\n",
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+      "ver 34, iter 11, fold 2, val ll: 0.0602, cor: 0.8433, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 12, fold 2, val ll: 0.0603, cor: 0.8430, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 13, fold 2, val ll: 0.0600, cor: 0.8437, auc: 0.9891\n",
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+      "Batch 50 device: cuda time passed: 8.678 time per batch: 0.174\n",
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+      "ver 34, iter 14, fold 2, val ll: 0.0599, cor: 0.8439, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.440 time per batch: 0.169\n",
+      "Batch 100 device: cuda time passed: 14.694 time per batch: 0.147\n",
+      "ver 34, iter 15, fold 2, val ll: 0.0601, cor: 0.8438, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.452 time per batch: 0.149\n",
+      "Batch 100 device: cuda time passed: 14.976 time per batch: 0.150\n",
+      "ver 34, iter 16, fold 2, val ll: 0.0603, cor: 0.8432, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.036 time per batch: 0.161\n",
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+      "ver 34, iter 17, fold 2, val ll: 0.0600, cor: 0.8440, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
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+      "ver 34, iter 18, fold 2, val ll: 0.0600, cor: 0.8437, auc: 0.9891\n",
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+      "ver 34, iter 19, fold 2, val ll: 0.0601, cor: 0.8436, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.992 time per batch: 0.160\n",
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+      "ver 34, iter 20, fold 2, val ll: 0.0602, cor: 0.8431, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.981 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 14.312 time per batch: 0.143\n",
+      "ver 34, iter 21, fold 2, val ll: 0.0602, cor: 0.8433, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.863 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.493 time per batch: 0.145\n",
+      "ver 34, iter 22, fold 2, val ll: 0.0601, cor: 0.8436, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
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+      "Batch 100 device: cuda time passed: 14.578 time per batch: 0.146\n",
+      "ver 34, iter 23, fold 2, val ll: 0.0602, cor: 0.8434, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.230 time per batch: 0.165\n",
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+      "ver 34, iter 24, fold 2, val ll: 0.0602, cor: 0.8431, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.489 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 14.700 time per batch: 0.147\n",
+      "ver 34, iter 25, fold 2, val ll: 0.0601, cor: 0.8434, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.810 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 14.881 time per batch: 0.149\n",
+      "ver 34, iter 26, fold 2, val ll: 0.0601, cor: 0.8438, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.647 time per batch: 0.173\n",
+      "Batch 100 device: cuda time passed: 14.903 time per batch: 0.149\n",
+      "ver 34, iter 27, fold 2, val ll: 0.0602, cor: 0.8434, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.024 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 15.108 time per batch: 0.151\n",
+      "ver 34, iter 28, fold 2, val ll: 0.0601, cor: 0.8436, auc: 0.9891\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.179 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 15.084 time per batch: 0.151\n",
+      "ver 34, iter 29, fold 2, val ll: 0.0603, cor: 0.8433, auc: 0.9889\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.489 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 15.248 time per batch: 0.152\n",
+      "ver 34, iter 30, fold 2, val ll: 0.0602, cor: 0.8435, auc: 0.9890\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.780 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 14.653 time per batch: 0.147\n",
+      "ver 34, iter 31, fold 2, val ll: 0.0602, cor: 0.8432, auc: 0.9890\n",
+      "total running time 759.7050180435181\n",
+      "total time 19375.86375927925\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 13 valid size 4352 fold 3\n",
+      "dataset valid: 4352 loader valid: 136\n",
+      "loading model model.b3.f3.d13.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.209 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.432 time per batch: 0.144\n",
+      "ver 34, iter 0, fold 3, val ll: 0.0629, cor: 0.8398, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.060 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.405 time per batch: 0.144\n",
+      "ver 34, iter 1, fold 3, val ll: 0.0631, cor: 0.8396, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.998 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 14.574 time per batch: 0.146\n",
+      "ver 34, iter 2, fold 3, val ll: 0.0632, cor: 0.8388, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.088 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 14.750 time per batch: 0.148\n",
+      "ver 34, iter 3, fold 3, val ll: 0.0630, cor: 0.8399, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.872 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 15.131 time per batch: 0.151\n",
+      "ver 34, iter 4, fold 3, val ll: 0.0629, cor: 0.8396, auc: 0.9887\n",
+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 50 device: cuda time passed: 7.764 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.443 time per batch: 0.144\n",
+      "ver 34, iter 5, fold 3, val ll: 0.0630, cor: 0.8392, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.046 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.542 time per batch: 0.145\n",
+      "ver 34, iter 6, fold 3, val ll: 0.0630, cor: 0.8400, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.369 time per batch: 0.167\n",
+      "Batch 100 device: cuda time passed: 14.797 time per batch: 0.148\n",
+      "ver 34, iter 7, fold 3, val ll: 0.0629, cor: 0.8397, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.385 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 15.082 time per batch: 0.151\n",
+      "ver 34, iter 8, fold 3, val ll: 0.0630, cor: 0.8396, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.233 time per batch: 0.165\n",
+      "Batch 100 device: cuda time passed: 14.812 time per batch: 0.148\n",
+      "ver 34, iter 9, fold 3, val ll: 0.0630, cor: 0.8392, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.719 time per batch: 0.174\n",
+      "Batch 100 device: cuda time passed: 15.227 time per batch: 0.152\n",
+      "ver 34, iter 10, fold 3, val ll: 0.0631, cor: 0.8393, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.403 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 14.953 time per batch: 0.150\n",
+      "ver 34, iter 11, fold 3, val ll: 0.0630, cor: 0.8396, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.628 time per batch: 0.153\n",
+      "Batch 100 device: cuda time passed: 15.699 time per batch: 0.157\n",
+      "ver 34, iter 12, fold 3, val ll: 0.0632, cor: 0.8390, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.949 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.760 time per batch: 0.148\n",
+      "ver 34, iter 13, fold 3, val ll: 0.0630, cor: 0.8398, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.102 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 14.558 time per batch: 0.146\n",
+      "ver 34, iter 14, fold 3, val ll: 0.0631, cor: 0.8389, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.056 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.553 time per batch: 0.146\n",
+      "ver 34, iter 15, fold 3, val ll: 0.0633, cor: 0.8389, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.476 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 14.739 time per batch: 0.147\n",
+      "ver 34, iter 16, fold 3, val ll: 0.0630, cor: 0.8395, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.207 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.548 time per batch: 0.145\n",
+      "ver 34, iter 17, fold 3, val ll: 0.0632, cor: 0.8392, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.305 time per batch: 0.166\n",
+      "Batch 100 device: cuda time passed: 14.417 time per batch: 0.144\n",
+      "ver 34, iter 18, fold 3, val ll: 0.0630, cor: 0.8397, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.726 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 15.397 time per batch: 0.154\n",
+      "ver 34, iter 19, fold 3, val ll: 0.0630, cor: 0.8398, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.974 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.515 time per batch: 0.145\n",
+      "ver 34, iter 20, fold 3, val ll: 0.0634, cor: 0.8385, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.898 time per batch: 0.158\n",
+      "Batch 100 device: cuda time passed: 14.685 time per batch: 0.147\n",
+      "ver 34, iter 21, fold 3, val ll: 0.0629, cor: 0.8399, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.814 time per batch: 0.156\n",
+      "Batch 100 device: cuda time passed: 15.322 time per batch: 0.153\n",
+      "ver 34, iter 22, fold 3, val ll: 0.0631, cor: 0.8392, auc: 0.9885\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.499 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 15.189 time per batch: 0.152\n",
+      "ver 34, iter 23, fold 3, val ll: 0.0630, cor: 0.8397, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.627 time per batch: 0.153\n",
+      "Batch 100 device: cuda time passed: 14.563 time per batch: 0.146\n",
+      "ver 34, iter 24, fold 3, val ll: 0.0630, cor: 0.8396, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.223 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.639 time per batch: 0.146\n",
+      "ver 34, iter 25, fold 3, val ll: 0.0630, cor: 0.8394, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.255 time per batch: 0.165\n",
+      "Batch 100 device: cuda time passed: 14.365 time per batch: 0.144\n",
+      "ver 34, iter 26, fold 3, val ll: 0.0629, cor: 0.8395, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.287 time per batch: 0.166\n",
+      "Batch 100 device: cuda time passed: 14.326 time per batch: 0.143\n",
+      "ver 34, iter 27, fold 3, val ll: 0.0631, cor: 0.8390, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.750 time per batch: 0.175\n",
+      "Batch 100 device: cuda time passed: 14.716 time per batch: 0.147\n",
+      "ver 34, iter 28, fold 3, val ll: 0.0630, cor: 0.8395, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.832 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.454 time per batch: 0.145\n",
+      "ver 34, iter 29, fold 3, val ll: 0.0629, cor: 0.8397, auc: 0.9887\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.247 time per batch: 0.165\n",
+      "Batch 100 device: cuda time passed: 14.407 time per batch: 0.144\n",
+      "ver 34, iter 30, fold 3, val ll: 0.0630, cor: 0.8393, auc: 0.9886\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.728 time per batch: 0.175\n",
+      "Batch 100 device: cuda time passed: 14.980 time per batch: 0.150\n",
+      "ver 34, iter 31, fold 3, val ll: 0.0634, cor: 0.8388, auc: 0.9884\n",
+      "total running time 748.6304786205292\n",
+      "total time 20124.740348815918\n",
+      "completed epochs: 3 iters starting now: 32\n",
+      "adding dummy serieses 16\n",
+      "DataSet 13 valid size 4384 fold 4\n",
+      "dataset valid: 4384 loader valid: 137\n",
+      "loading model model.b3.f4.d13.v34\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.680 time per batch: 0.154\n",
+      "Batch 100 device: cuda time passed: 14.974 time per batch: 0.150\n",
+      "ver 34, iter 0, fold 4, val ll: 0.0616, cor: 0.8422, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.849 time per batch: 0.177\n",
+      "Batch 100 device: cuda time passed: 15.070 time per batch: 0.151\n",
+      "ver 34, iter 1, fold 4, val ll: 0.0618, cor: 0.8420, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.719 time per batch: 0.154\n",
+      "Batch 100 device: cuda time passed: 14.696 time per batch: 0.147\n",
+      "ver 34, iter 2, fold 4, val ll: 0.0618, cor: 0.8423, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.469 time per batch: 0.169\n",
+      "Batch 100 device: cuda time passed: 14.909 time per batch: 0.149\n",
+      "ver 34, iter 3, fold 4, val ll: 0.0618, cor: 0.8418, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.626 time per batch: 0.153\n",
+      "Batch 100 device: cuda time passed: 14.660 time per batch: 0.147\n",
+      "ver 34, iter 4, fold 4, val ll: 0.0618, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.404 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 14.750 time per batch: 0.147\n",
+      "ver 34, iter 5, fold 4, val ll: 0.0619, cor: 0.8417, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.219 time per batch: 0.164\n",
+      "Batch 100 device: cuda time passed: 14.164 time per batch: 0.142\n",
+      "ver 34, iter 6, fold 4, val ll: 0.0616, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.061 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.689 time per batch: 0.147\n",
+      "ver 34, iter 7, fold 4, val ll: 0.0617, cor: 0.8423, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.938 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.192 time per batch: 0.142\n",
+      "ver 34, iter 8, fold 4, val ll: 0.0617, cor: 0.8421, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.663 time per batch: 0.173\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Batch 100 device: cuda time passed: 14.850 time per batch: 0.149\n",
+      "ver 34, iter 9, fold 4, val ll: 0.0618, cor: 0.8418, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.651 time per batch: 0.173\n",
+      "Batch 100 device: cuda time passed: 14.415 time per batch: 0.144\n",
+      "ver 34, iter 10, fold 4, val ll: 0.0617, cor: 0.8423, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.635 time per batch: 0.153\n",
+      "Batch 100 device: cuda time passed: 15.063 time per batch: 0.151\n",
+      "ver 34, iter 11, fold 4, val ll: 0.0617, cor: 0.8423, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.388 time per batch: 0.168\n",
+      "Batch 100 device: cuda time passed: 14.779 time per batch: 0.148\n",
+      "ver 34, iter 12, fold 4, val ll: 0.0618, cor: 0.8418, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.871 time per batch: 0.157\n",
+      "Batch 100 device: cuda time passed: 14.803 time per batch: 0.148\n",
+      "ver 34, iter 13, fold 4, val ll: 0.0617, cor: 0.8418, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.072 time per batch: 0.161\n",
+      "Batch 100 device: cuda time passed: 14.433 time per batch: 0.144\n",
+      "ver 34, iter 14, fold 4, val ll: 0.0618, cor: 0.8419, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.584 time per batch: 0.172\n",
+      "Batch 100 device: cuda time passed: 15.084 time per batch: 0.151\n",
+      "ver 34, iter 15, fold 4, val ll: 0.0618, cor: 0.8421, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.715 time per batch: 0.154\n",
+      "Batch 100 device: cuda time passed: 15.169 time per batch: 0.152\n",
+      "ver 34, iter 16, fold 4, val ll: 0.0618, cor: 0.8420, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.982 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 15.258 time per batch: 0.153\n",
+      "ver 34, iter 17, fold 4, val ll: 0.0614, cor: 0.8429, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.944 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.644 time per batch: 0.146\n",
+      "ver 34, iter 18, fold 4, val ll: 0.0620, cor: 0.8415, auc: 0.9879\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.880 time per batch: 0.158\n",
+      "Batch 100 device: cuda time passed: 14.599 time per batch: 0.146\n",
+      "ver 34, iter 19, fold 4, val ll: 0.0618, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.238 time per batch: 0.165\n",
+      "Batch 100 device: cuda time passed: 14.637 time per batch: 0.146\n",
+      "ver 34, iter 20, fold 4, val ll: 0.0617, cor: 0.8419, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.506 time per batch: 0.170\n",
+      "Batch 100 device: cuda time passed: 14.624 time per batch: 0.146\n",
+      "ver 34, iter 21, fold 4, val ll: 0.0617, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.764 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.605 time per batch: 0.146\n",
+      "ver 34, iter 22, fold 4, val ll: 0.0617, cor: 0.8422, auc: 0.9882\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.726 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.446 time per batch: 0.144\n",
+      "ver 34, iter 23, fold 4, val ll: 0.0617, cor: 0.8422, auc: 0.9881\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.077 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 14.366 time per batch: 0.144\n",
+      "ver 34, iter 24, fold 4, val ll: 0.0621, cor: 0.8415, auc: 0.9879\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.973 time per batch: 0.159\n",
+      "Batch 100 device: cuda time passed: 14.194 time per batch: 0.142\n",
+      "ver 34, iter 25, fold 4, val ll: 0.0617, cor: 0.8420, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.393 time per batch: 0.148\n",
+      "Batch 100 device: cuda time passed: 15.218 time per batch: 0.152\n",
+      "ver 34, iter 26, fold 4, val ll: 0.0615, cor: 0.8427, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.723 time per batch: 0.174\n",
+      "Batch 100 device: cuda time passed: 15.348 time per batch: 0.153\n",
+      "ver 34, iter 27, fold 4, val ll: 0.0617, cor: 0.8418, auc: 0.9883\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 7.751 time per batch: 0.155\n",
+      "Batch 100 device: cuda time passed: 14.291 time per batch: 0.143\n",
+      "ver 34, iter 28, fold 4, val ll: 0.0619, cor: 0.8419, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.019 time per batch: 0.160\n",
+      "Batch 100 device: cuda time passed: 15.011 time per batch: 0.150\n",
+      "ver 34, iter 29, fold 4, val ll: 0.0620, cor: 0.8414, auc: 0.9879\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.106 time per batch: 0.162\n",
+      "Batch 100 device: cuda time passed: 15.439 time per batch: 0.154\n",
+      "ver 34, iter 30, fold 4, val ll: 0.0618, cor: 0.8419, auc: 0.9880\n",
+      "setFeats, augmentation -1\n",
+      "Batch 50 device: cuda time passed: 8.527 time per batch: 0.171\n",
+      "Batch 100 device: cuda time passed: 15.187 time per batch: 0.152\n",
+      "ver 34, iter 31, fold 4, val ll: 0.0619, cor: 0.8414, auc: 0.9881\n",
+      "total running time 749.8348104953766\n",
+      "total time 20874.81984090805\n"
+     ]
+    }
+   ],
+   "source": [
+    "stg = time.time()\n",
+    "for ds in (my_datasets3 + my_datasets5):\n",
+    "    folds = getNFolds(ds)\n",
+    "    for fold in range(folds):\n",
+    "        #pp = pickle.load(open(PATH_DISK/'ensemble/oof_d{}_f{}_v{}'.format(ds, fold, VERSION),'rb'))\n",
+    "        predictions = oof_one(num_iter=32, bs=32, fold=fold, dataset=ds)\n",
+    "        #predictions = np.concatenate([pp,predictions],axis=0)\n",
+    "        pickle.dump(predictions, open(PATH_DISK/'ensemble/oof_d{}_f{}_v{}'.format(ds, fold, VERSION),'wb'))\n",
+    "        print('total time', time.time() - stg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#range(6,13) x8\n",
+    "#5113.189187049866\n",
+    "#20878.715314388275"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.231111111111111"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#total running time 1201.68962931633\n",
+    "#total time 15020.348212480545"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_all = getPredsOOF(aug=32,datasets=my_datasets3,datasets5=my_datasets5,ver=33)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_all = getPredsOOF(aug=32,datasets=my_datasets3,datasets5=my_datasets5,ver=34)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(5, 32, 752797, 6)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_all.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#preds_all2 = getPredsOOF(aug=32,datasets=[],datasets5=[14],ver=35)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "#preds_all2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#preds_all = np.concatenate([preds_all, preds_all2], axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.14302406, 0.00424933, 0.04813841, 0.03484004, 0.04746119,\n",
+       "       0.06259691])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# weighted \n",
+    "# [0.15059251, 0.00462303, 0.05034504, 0.03602126, 0.04910235, 0.06661193]\n",
+    "\n",
+    "# non-weighted\n",
+    "# [0.14268919, 0.00409448, 0.04815497, 0.03553187, 0.04749233, 0.06196157]\n",
+    "\n",
+    "# non-weighted stage2\n",
+    "# [0.14302406, 0.00424933, 0.04813841, 0.03484004, 0.04746119, 0.06259691]\n",
+    "\n",
+    "# weighted stage2\n",
+    "# [0.14172827, 0.00397889, 0.04794982, 0.0350942 , 0.04717257, 0.06180147]\n",
+    "\n",
+    "preds_all.mean((0,1,2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_y = [\n",
+    "    #'model_Densenet201_3_version_classifier_splits_fullhead_resmodel_pool2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    #'model_Densenet161_3_version_classifier_splits_fullhead_resmodel_pool2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    'model_Densenet169_3_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    'model_se_resnext101_32x4d_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    'model_se_resnet101_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl'\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_y5 = [\n",
+    "    'model_se_resnext101_32x4d_version_new_splits_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    'model_se_resnet101_version_new_splits_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    'model_se_resnet101_version_new_splits_focal_fullhead_resmodel_pool2_stage2_3_type_OOF_pred_split_{}.pkl',\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "adding yuval_idx\n",
+      "adding yuval_idx\n"
+     ]
+    }
+   ],
+   "source": [
+    "preds_y = getYuvalOOF(train_md=train_md, names=names_y, names5=names_y5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.14321291, 0.00391866, 0.04807696, 0.03472973, 0.04762993,\n",
+       "       0.06291145])"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_y.mean((0,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(6, 752797, 6)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_y.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_all = np.concatenate([preds_all.mean(1), preds_y], axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del preds_y"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(11, 752797, 6)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_all.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Elimination"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getMaskedLoss(preds_all, mask, weighted):\n",
+    "    \n",
+    "    loss = ((- train_md[all_ich].values * np.log(preds_all[mask].mean(0)) \\\n",
+    "            - (1 - train_md[all_ich].values) * np.log(1 - preds_all[mask].mean(0)))*class_weights)\n",
+    "    \n",
+    "    if weighted:\n",
+    "        loss = (loss * np.expand_dims(train_md['weights'].values,axis=1)).mean()\n",
+    "    else:\n",
+    "        loss = loss.mean()\n",
+    "    return loss\n",
+    "\n",
+    "def produceDSMask(weighted):\n",
+    "    \n",
+    "    N = len(preds_all)\n",
+    "    ds_mask = np.ones(N, dtype=bool)\n",
+    "    best_loss = getMaskedLoss(preds_all, ds_mask, weighted)\n",
+    "\n",
+    "    for i in range(N):\n",
+    "        worst_k = -1\n",
+    "        worst_loss = best_loss\n",
+    "        print('starting iter',i,'loss',best_loss,'eliminated',(~ds_mask).sum())\n",
+    "        for k in range(N):\n",
+    "            mask2 = ds_mask.copy()\n",
+    "            mask2[k] = False\n",
+    "            loss = getMaskedLoss(preds_all, mask2, weighted)\n",
+    "            if loss < worst_loss:\n",
+    "                worst_loss = loss\n",
+    "                worst_k = k\n",
+    "        if worst_k >= 0:\n",
+    "            print('eliminating',worst_k,'new loss',worst_loss)\n",
+    "            ds_mask[worst_k] = False\n",
+    "            best_loss = worst_loss\n",
+    "        else:\n",
+    "            break\n",
+    "    \n",
+    "    print('removed', np.where(~ds_mask)[0])\n",
+    "    \n",
+    "    return ds_mask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "starting iter 0 loss 0.057515051687738426 eliminated 0\n",
+      "eliminating 1 new loss 0.057490836031309125\n",
+      "starting iter 1 loss 0.057490836031309125 eliminated 1\n",
+      "removed [1]\n",
+      "\n",
+      "starting iter 0 loss 0.05434281856430104 eliminated 0\n",
+      "eliminating 1 new loss 0.05431221808734583\n",
+      "starting iter 1 loss 0.05431221808734583 eliminated 1\n",
+      "eliminating 4 new loss 0.054308387316921135\n",
+      "starting iter 2 loss 0.054308387316921135 eliminated 2\n",
+      "eliminating 5 new loss 0.054305186238067175\n",
+      "starting iter 3 loss 0.054305186238067175 eliminated 3\n",
+      "removed [1 4 5]\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds_mask1 = produceDSMask(False)\n",
+    "print('')\n",
+    "ds_mask2 = produceDSMask(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_mask = ds_mask1 | ds_mask2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ True, False,  True,  True,  True,  True,  True,  True,  True,\n",
+       "        True,  True])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_mask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_all = preds_all[ds_mask]\n",
+    "my_len = ds_mask[:my_len].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "my_len"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## OOF analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "any                  [0.099 0.096 0.096 0.096 0.1   0.099 0.098 0.097 0.097 0.097]\n",
+      "epidural             [0.017 0.015 0.016 0.016 0.016 0.015 0.015 0.015 0.015 0.015]\n",
+      "intraparenchymal     [0.043 0.041 0.042 0.042 0.043 0.041 0.042 0.041 0.041 0.041]\n",
+      "intraventricular     [0.026 0.025 0.025 0.025 0.026 0.025 0.025 0.025 0.025 0.025]\n",
+      "subarachnoid         [0.066 0.064 0.064 0.064 0.066 0.064 0.064 0.064 0.063 0.063]\n",
+      "subdural             [0.081 0.079 0.079 0.079 0.08  0.079 0.079 0.079 0.078 0.078]\n"
+     ]
+    }
+   ],
+   "source": [
+    "np.set_printoptions(precision=3)\n",
+    "\n",
+    "loss = (- train_md[all_ich].values * np.log(preds_all) \\\n",
+    "        - (1 - train_md[all_ich].values) * np.log(1 - preds_all)).mean(1)\n",
+    "for k in range(6):\n",
+    "    print('{:20s} {}'.format(all_ich[k],loss[:,k]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0.142 0.143 0.143 0.143 0.143 0.145 0.144 0.142 0.142 0.143]\n",
+      " [0.004 0.005 0.004 0.004 0.003 0.004 0.004 0.004 0.004 0.004]\n",
+      " [0.048 0.048 0.048 0.048 0.048 0.048 0.049 0.048 0.048 0.048]\n",
+      " [0.035 0.035 0.035 0.035 0.035 0.034 0.035 0.035 0.035 0.035]\n",
+      " [0.047 0.047 0.047 0.048 0.048 0.049 0.047 0.047 0.047 0.048]\n",
+      " [0.062 0.062 0.063 0.063 0.063 0.065 0.064 0.062 0.062 0.063]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(preds_all.mean(1).transpose())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f82b89bfc10>]"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "zz = preds_all.mean(0)[:,0]\n",
+    "\n",
+    "train_md['prob'] = zz\n",
+    "\n",
+    "plt.plot(train_md[['prob','pos_idx']].groupby('pos_idx').mean())\n",
+    "plt.plot([0,60],[0,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0934667744853716"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "log_loss(train_md['any'],train_md['prob'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0, 5)"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#zz = preds_all.mean(1)[0,:,0]\n",
+    "k=0\n",
+    "zz = preds_all.mean(0)[:,k]\n",
+    "#zz = preds_all[0,0,:,k]\n",
+    "#zz = scalePreds(zz,power=1.3)\n",
+    "\n",
+    "\n",
+    "plt.figure(figsize=(16, 7))\n",
+    "a = plt.hist(zz - train_md[all_ich[k]],bins=100,alpha=0.5,density=True)\n",
+    "b = 0.5*(a[1][1:] + a[1][:-1])\n",
+    "plt.plot(b,-7*np.log(1-abs(b))*a[0])\n",
+    "plt.ylim([0,5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 [3.57e-05 6.13e-05 9.31e-05 1.79e-03 9.95e-01 9.98e-01 9.99e-01]\n",
+      "1 [7.12e-06 9.84e-06 1.44e-05 9.54e-05 8.47e-02 4.76e-01 8.64e-01]\n",
+      "2 [1.66e-05 2.25e-05 3.18e-05 3.06e-04 9.82e-01 9.94e-01 9.97e-01]\n",
+      "3 [8.39e-06 1.13e-05 1.72e-05 1.02e-04 9.76e-01 9.92e-01 9.95e-01]\n",
+      "4 [2.32e-05 3.56e-05 5.27e-05 4.59e-04 9.57e-01 9.92e-01 9.96e-01]\n",
+      "5 [2.51e-05 4.16e-05 6.20e-05 9.25e-04 9.68e-01 9.93e-01 9.96e-01]\n"
+     ]
+    }
+   ],
+   "source": [
+    "np.set_printoptions(precision=2)\n",
+    "zz = preds_all.mean(0)\n",
+    "for k in range(6):\n",
+    "    print(k,np.quantile(zz[:,k],[0.0001,0.001,0.01,0.5,0.99,0.999,0.9999]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Bounding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 752797, 6)"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_all.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.057490836031309125\n"
+     ]
+    }
+   ],
+   "source": [
+    "loss = ((- train_md[all_ich].values * np.log(preds_all.mean(0)) \\\n",
+    "        - (1 - train_md[all_ich].values) * np.log(1 - preds_all.mean(0)))*class_weights).mean()\n",
+    "print(loss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "initial score 0.057490836031309125\n",
+      "any too low inconsistencies\n",
+      "1 class: 0.004179878506423379\n",
+      "2 class: 0.025429033325053103\n",
+      "3 class: 0.012410782720972586\n",
+      "4 class: 0.033147714456885455\n",
+      "5 class: 0.09211925658577279\n",
+      "total 0.14343999776832267\n",
+      "any too low corrected score 0.05748886375218989\n",
+      "any too high inconsistencies\n",
+      "total 0.24964844440134593\n",
+      "any too high corrected score 0.0574848864789516\n"
+     ]
+    }
+   ],
+   "source": [
+    "preds_all = predBounding(preds_all, target=train_md[all_ich].values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0574848864789516\n"
+     ]
+    }
+   ],
+   "source": [
+    "loss = ((- train_md[all_ich].values * np.log(preds_all.mean(0)) \\\n",
+    "        - (1 - train_md[all_ich].values) * np.log(1 - preds_all.mean(0)))*class_weights).mean()\n",
+    "print(loss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Models behavior per groups"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 0: 452096  84109 [0.0744 0.0723 0.0724 0.0725 0.0742 0.0729 0.073  0.072  0.0718 0.0718]\n",
+      " 1: 300701  37123 [0.0418 0.0406 0.0404 0.0408 0.0425 0.0415 0.0417 0.041  0.0405 0.0406]\n"
+     ]
+    }
+   ],
+   "source": [
+    "np.set_printoptions(precision=4)\n",
+    "for col in ['PxlMin_zero']:\n",
+    "    for i in train_md[col].unique():\n",
+    "        res = ((- train_md[all_ich].values * np.log(preds_all) - (1 - train_md[all_ich].values) \\\n",
+    "                * np.log(1 - preds_all)) * class_weights)[:,(train_md[col] == i)].mean((1,2))\n",
+    "        sz = (train_md[col] == i).sum()\n",
+    "        sz_test = (test_md[col] == i).sum()\n",
+    "        print('{:2d}: {:6d} {:6d} {}'.format(i,sz,sz_test,res))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Inference"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "completed epochs: 13\n",
+      "loading model model.b13.f0.d14.v35\n",
+      "adding dummy serieses 2\n",
+      "DataSet 14 test size 3520 fold 0\n",
+      "dataset test: 3520 loader test: 110 anum: 0\n",
+      "setFeats, augmentation -1\n"
+     ]
+    },
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: '/mnt/edisk/running/features/se_resnet101_5n/test2/test.f0.a0'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-84-de854db3530e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      8\u001b[0m         \u001b[0mpreds2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0manum\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m             \u001b[0mpredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minference_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfold\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0manum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0manum\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdataset\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m             \u001b[0mpreds2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m         \u001b[0mpreds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpreds2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-82-5f73bc7ddaa9>\u001b[0m in \u001b[0;36minference_one\u001b[0;34m(dataset, bs, add_seed, fold, anum)\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'dataset test:'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtst_ds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'loader test:'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloader_tst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'anum:'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0manum\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m     \u001b[0mtst_ds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetFeats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0manum\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m     \u001b[0mloc_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtst_ds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetadata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-82-44e0138eb17e>\u001b[0m in \u001b[0;36msetFeats\u001b[0;34m(self, anum, epoch)\u001b[0m\n\u001b[1;32m     81\u001b[0m                                    getAPathFeats('test', self.metadata.test.sum(), self.test_mask)] ,axis=0)\n\u001b[1;32m     82\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 83\u001b[0;31m                 \u001b[0mfeats\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetAPathFeats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m13\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'valid'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mTRAIN_ON_STAGE_1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-82-44e0138eb17e>\u001b[0m in \u001b[0;36mgetAPathFeats\u001b[0;34m(mode, sz, mask)\u001b[0m\n\u001b[1;32m     62\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mgetAPathFeats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m             \u001b[0mmax_a\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'test'\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m             \u001b[0mfeats2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetAPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0man\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0man\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     65\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m                 \u001b[0mfeats2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfeats2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-82-44e0138eb17e>\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     62\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mgetAPathFeats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m             \u001b[0mmax_a\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'test'\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m             \u001b[0mfeats2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetAPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0man\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0man\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     65\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m                 \u001b[0mfeats2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfeats2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/mnt/edisk/running/features/se_resnet101_5n/test2/test.f0.a0'"
+     ]
+    }
+   ],
+   "source": [
+    "stg = time.time()\n",
+    "\n",
+    "#for ds in (my_datasets3 + my_datasets5):\n",
+    "for ds in [14]:\n",
+    "    folds = getNFolds(ds)\n",
+    "    preds = []\n",
+    "    for fold in range(folds):\n",
+    "        preds2 = []\n",
+    "        for anum in range(32):\n",
+    "            predictions = inference_one(fold = fold, anum = anum, bs=bs, dataset=ds)\n",
+    "            preds2.append(predictions)\n",
+    "        preds.append(np.stack(preds2))\n",
+    "    preds = np.stack(preds)\n",
+    "    print('total time', time.time() - stg)\n",
+    "    \n",
+    "    pickle.dump(preds, open(PATH_DISK/'preds_d{}_v{}'.format(ds, VERSION),'wb'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#11221.892060995102"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#total time 1466.092379808426 5x8\n",
+    "#total time 5399.404406309128 5x32"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Files transfer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Copying file:///home/zahar_chikishev/running/oof_d6_f0_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d6_f1_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d6_f2_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d7_f0_v20 [Content-Type=application/octet-stream]...\n",
+      "- [4 files][164.5 MiB/164.5 MiB]                                                \n",
+      "==> NOTE: You are performing a sequence of gsutil operations that may\n",
+      "run significantly faster if you instead use gsutil -m cp ... Please\n",
+      "see the -m section under \"gsutil help options\" for further information\n",
+      "about when gsutil -m can be advantageous.\n",
+      "\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d7_f1_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d7_f2_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d8_f0_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d8_f1_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d8_f2_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d9_f0_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d9_f1_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/oof_d9_f2_v20 [Content-Type=application/octet-stream]...\n",
+      "| [12 files][493.8 MiB/493.8 MiB]   35.9 MiB/s                                  \n",
+      "Operation completed over 12 objects/493.8 MiB.                                   \n"
+     ]
+    }
+   ],
+   "source": [
+    "!gsutil cp /home/zahar_chikishev/running/oof* gs://rsna-hemorrhage/results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Copying file:///home/zahar_chikishev/running/preds_d6_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/preds_d7_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/preds_d8_v20 [Content-Type=application/octet-stream]...\n",
+      "Copying file:///home/zahar_chikishev/running/preds_d9_v20 [Content-Type=application/octet-stream]...\n",
+      "\\ [4 files][172.6 MiB/172.6 MiB]                                                \n",
+      "Operation completed over 4 objects/172.6 MiB.                                    \n"
+     ]
+    }
+   ],
+   "source": [
+    "!gsutil cp /home/zahar_chikishev/running/preds* gs://rsna-hemorrhage/results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gsutil -m cp gs://rsna-hemorrhage/results/* C:\\StudioProjects\\Hemorrhage\\running\\ensemble"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gsutil -m cp gs://rsna-hemorrhage/yuvals/model_Densenet161_3_version_classifier_splits_fullhead_resmodel_type_OOF_pred_split_* ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gsutil -m cp gs://rsna-hemorrhage/yuvals/model_*_version_classifier_splits_fullhead_resmodel_type_OOF_pred_split_* ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gsutil -m cp gs://rsna-hemorrhage/yuvals/model_Densenet161_3_version_classifier_splits_fullhead_resmodel_type_test_pred_ensamble_split_* ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gsutil cp gs://rsna-hemorrhage/yuvals/OOF_validation_image_ids.pkl .\n",
+    "!gsutil cp gs://rsna-hemorrhage/yuvals/ensemble_test_image_ids.pkl ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!rm /home/zahar_chikishev/running/*v53"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/zahar_chikishev/running/preds_se_resnext101_32x4d_v53\r\n",
+      "/home/zahar_chikishev/running/stats.f0.v53\r\n",
+      "/home/zahar_chikishev/running/stats.f1.v53\r\n",
+      "/home/zahar_chikishev/running/stats.f2.v53\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /home/zahar_chikishev/running/*v53"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/zahar_chikishev/running/oof_Densenet161_f0_v72\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet161_f1_v72\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet161_f2_v72\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet169_f0_v73\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet169_f1_v73\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet169_f2_v73\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet201_f0_v74\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet201_f1_v74\r\n",
+      "/home/zahar_chikishev/running/oof_Densenet201_f2_v74\r\n",
+      "/home/zahar_chikishev/running/oof_se_resnext101_32x4d_f0_v75\r\n",
+      "/home/zahar_chikishev/running/oof_se_resnext101_32x4d_f1_v75\r\n",
+      "/home/zahar_chikishev/running/oof_se_resnext101_32x4d_f2_v75\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /home/zahar_chikishev/running/oof*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/zahar_chikishev/running/preds_Densenet161_v72\r\n",
+      "/home/zahar_chikishev/running/preds_Densenet169_v73\r\n",
+      "/home/zahar_chikishev/running/preds_Densenet201_v74\r\n",
+      "/home/zahar_chikishev/running/preds_se_resnext101_32x4d_v75\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /home/zahar_chikishev/running/preds*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ensembling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 752797, 6)"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds_all.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8298f99450>]"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#dd = pd.DataFrame(preds_all.mean(1)[4], columns=all_ich)\n",
+    "dd = pd.DataFrame(preds_all.mean(0), columns=all_ich)\n",
+    "\n",
+    "k=5\n",
+    "plt.plot([0,100],[0,1])\n",
+    "plt.plot(train_md[[all_ich[k]]].groupby(pd.cut(dd[all_ich[k]],np.arange(101)/100)).mean().values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8298d8b790>]"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "k = 0\n",
+    "dd = pd.DataFrame((preds_all.mean(0)), columns=all_ich)\n",
+    "vals = (train_md[all_ich[k]]*train_md['weights']).groupby(pd.cut(dd[all_ich[k]],np.arange(101)/100)).mean()/ \\\n",
+    "    train_md['weights'].groupby(pd.cut(dd[all_ich[k]],np.arange(101)/100)).mean()\n",
+    "\n",
+    "#dd = pd.DataFrame(preds_all.mean(1)[4], columns=all_ich)\n",
+    "\n",
+    "plt.plot([0,100],[0,1])\n",
+    "plt.plot(vals.values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.05430755335203294\n"
+     ]
+    }
+   ],
+   "source": [
+    "res = np.zeros(6)\n",
+    "for k in range(6):\n",
+    "    res[k] = log_loss(train_md[all_ich[k]], preds_all.mean(0)[:,k], eps=1e-7, labels=[0,1], \\\n",
+    "                      sample_weight=train_md.weights)\n",
+    "print((res*class_weights).mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.05507244939620463\n"
+     ]
+    }
+   ],
+   "source": [
+    "res = np.zeros(6)\n",
+    "for k in range(6):\n",
+    "    res[k] = log_loss(train_md[all_ich[k]], preds_all.mean(0)[:,k]**(0.9), eps=1e-7, labels=[0,1], \\\n",
+    "                      sample_weight=train_md.weights)\n",
+    "print((res*class_weights).mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%run ./Code.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stats_fn = PATH_DISK/'ensemble'/'stats.v{}'.format(VERSION)\n",
+    "if stats_fn.is_file():\n",
+    "    stats_fn.unlink()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "starting fold 0 target 0\n",
+      "my_len 4\n",
+      "obj  0.08727681341480276\n",
+      "obj  0.08727680961247067\n",
+      "obj  0.08727681635930583\n",
+      "obj  0.08727683790936251\n",
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+      "obj  0.0872790250770156\n",
+      "obj  0.08728207769630063\n",
+      "obj  0.08730524551710207\n",
+      "obj  0.08741163374725006\n",
+      "obj  0.08737828492011111\n",
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+      "obj  0.08727743735897546\n",
+      "obj  0.08727694643886197\n",
+      "obj  0.08727683642000757\n",
+      "obj  0.08727680763252753\n",
+      "obj  0.08727680110920166\n",
+      "obj  0.0872767999865726\n",
+      "model [0.5022 0.4978] sum 0.9999676813453886\n",
+      "my_len 4\n",
+      "v34 f0 t0: original ll 0.0935/0.0886, ensemble ll 0.0935/0.0886\n",
+      "running time 3.408698320388794\n",
+      "starting fold 0 target 1\n",
+      "my_len 4\n",
+      "obj  0.012081623796648948\n",
+      "obj  0.012064844467400441\n",
+      "obj  0.012069603621018268\n",
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+      "obj  0.012071291095892334\n",
+      "obj  0.012059318504672595\n",
+      "obj  0.012042443367714269\n",
+      "obj  0.012035341615015361\n",
+      "obj  0.012028032305076937\n",
+      "obj  0.01202777543489789\n",
+      "obj  0.012027740476985575\n",
+      "model [0.2831 0.6969] sum 0.9800013450345408\n",
+      "my_len 4\n",
+      "v34 f0 t1: original ll 0.0150/0.0139, ensemble ll 0.0149/0.0138\n",
+      "running time 2.795881509780884\n",
+      "starting fold 0 target 2\n",
+      "my_len 4\n",
+      "obj  0.03643239100707699\n",
+      "obj  0.03645343904689349\n",
+      "obj  0.0364534366143448\n",
+      "obj  0.036453513478217306\n",
+      "obj  0.036453516366294375\n",
+      "obj  0.03645341604099942\n",
+      "obj  0.03645330420145025\n",
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+      "obj  0.036450097188809066\n",
+      "obj  0.03641199892754806\n",
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+      "obj  0.03637281406397558\n",
+      "obj  0.036372806451137295\n",
+      "obj  0.03637272605629483\n",
+      "model [0.2802 0.7198] sum 0.9999991225720998\n",
+      "my_len 4\n",
+      "v34 f0 t2: original ll 0.0415/0.0392, ensemble ll 0.0415/0.0392\n",
+      "running time 2.8015294075012207\n",
+      "starting fold 0 target 3\n",
+      "my_len 4\n",
+      "obj  0.022513923350337257\n",
+      "obj  0.022514823788354697\n",
+      "obj  0.02251479174800453\n",
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+      "obj  0.022514807377993946\n",
+      "obj  0.022514793548033103\n",
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+      "obj  0.0225148540628997\n",
+      "obj  0.02251532492335685\n",
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+      "obj  0.02246025802669623\n",
+      "model [0.2562 0.7438] sum 0.9999997939535652\n",
+      "my_len 4\n",
+      "v34 f0 t3: original ll 0.0243/0.0239, ensemble ll 0.0243/0.0239\n",
+      "running time 2.816469669342041\n",
+      "starting fold 0 target 4\n",
+      "my_len 4\n",
+      "obj  0.05866908744304866\n",
+      "obj  0.058655421224092855\n",
+      "obj  0.05865799778032658\n",
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+      "obj  0.058666700956343514\n",
+      "obj  0.05866190108829274\n",
+      "obj  0.05867066520315169\n",
+      "obj  0.058622009226577926\n",
+      "obj  0.05857392212815765\n",
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+      "obj  0.05854793797715716\n",
+      "obj  0.0585477836014417\n",
+      "obj  0.05854778093821152\n",
+      "obj  0.05854778093568046\n",
+      "model [0.1849 0.8112] sum 0.9961132357622775\n",
+      "my_len 4\n",
+      "v34 f0 t4: original ll 0.0617/0.0596, ensemble ll 0.0617/0.0596\n",
+      "running time 2.985300064086914\n",
+      "starting fold 0 target 5\n",
+      "my_len 4\n",
+      "obj  0.07111888085217989\n",
+      "obj  0.07109943900079979\n",
+      "obj  0.07109626046895302\n",
+      "obj  0.07109808791436022\n",
+      "obj  0.07111092588847316\n",
+      "obj  0.0710957678702807\n",
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+      "obj  0.07109280184395775\n",
+      "obj  0.07107889783936418\n",
+      "obj  0.07107915998501899\n",
+      "obj  0.07106262999212018\n",
+      "obj  0.07106191775845142\n",
+      "obj  0.07106191688882099\n",
+      "model [0.3466 0.6453] sum 0.9918766105998069\n",
+      "my_len 4\n",
+      "v34 f0 t5: original ll 0.0789/0.0757, ensemble ll 0.0789/0.0757\n",
+      "running time 2.694082736968994\n",
+      "starting fold 1 target 0\n",
+      "my_len 4\n",
+      "obj  0.086462634155086\n",
+      "obj  0.08646150298320077\n",
+      "obj  0.0864614802906338\n",
+      "obj  0.08646149569706231\n",
+      "obj  0.08646172873837056\n",
+      "obj  0.08646289351196788\n",
+      "obj  0.08646556301640597\n",
+      "obj  0.08648759494216639\n",
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+      "obj  0.08657377479849461\n",
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+      "obj  0.08644958080609667\n",
+      "obj  0.08644661615687646\n",
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+      "obj  0.08644566400280582\n",
+      "obj  0.08644565114567859\n",
+      "model [0.5941 0.4059] sum 0.9999997875126851\n",
+      "my_len 4\n",
+      "v34 f1 t0: original ll 0.0964/0.0902, ensemble ll 0.0965/0.0902\n",
+      "running time 3.123203992843628\n",
+      "starting fold 1 target 1\n",
+      "my_len 4\n",
+      "obj  0.013554873239082691\n",
+      "obj  0.013536021601660043\n",
+      "obj  0.013540780340295681\n",
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+      "obj  0.013564699748967186\n",
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+      "obj  0.013547296797121735\n",
+      "obj  0.01354698457004907\n",
+      "obj  0.01350746236715416\n",
+      "obj  0.013447856802878057\n",
+      "obj  0.013419140435866268\n",
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+      "obj  0.013410353069281782\n",
+      "obj  0.013410352471037947\n",
+      "obj  0.013410330155687895\n",
+      "model [0.1071 0.8929] sum 0.9999981188620239\n",
+      "my_len 4\n",
+      "v34 f1 t1: original ll 0.0128/0.0110, ensemble ll 0.0129/0.0111\n",
+      "running time 3.057985782623291\n",
+      "starting fold 1 target 2\n",
+      "my_len 4\n",
+      "obj  0.03700983338270924\n",
+      "obj  0.03700942511496985\n",
+      "obj  0.03700941857757188\n",
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+      "obj  0.036984237597943385\n",
+      "obj  0.036983631845849435\n",
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+      "obj  0.036983397111147245\n",
+      "model [0.351 0.649] sum 0.9999845409128088\n",
+      "my_len 4\n",
+      "v34 f1 t2: original ll 0.0401/0.0381, ensemble ll 0.0400/0.0380\n",
+      "running time 3.355295419692993\n",
+      "starting fold 1 target 3\n",
+      "my_len 4\n",
+      "obj  0.023432825312353096\n",
+      "obj  0.023430311446247156\n",
+      "obj  0.023430223179945912\n",
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+      "model [0.3264 0.6736] sum 0.9999998723930892\n",
+      "my_len 4\n",
+      "v34 f1 t3: original ll 0.0233/0.0221, ensemble ll 0.0233/0.0220\n",
+      "running time 2.9708051681518555\n",
+      "starting fold 1 target 4\n",
+      "my_len 4\n",
+      "obj  0.05876162822408629\n",
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+      "model [0.2072 0.7928] sum 0.9999997236086989\n",
+      "my_len 4\n",
+      "v34 f1 t4: original ll 0.0632/0.0594, ensemble ll 0.0632/0.0594\n",
+      "running time 2.8280203342437744\n",
+      "starting fold 1 target 5\n",
+      "my_len 4\n",
+      "obj  0.07183112972231193\n",
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+      "model [0.3481 0.6455] sum 0.9935939570813068\n",
+      "my_len 4\n",
+      "v34 f1 t5: original ll 0.0780/0.0742, ensemble ll 0.0780/0.0742\n",
+      "running time 2.8228495121002197\n",
+      "starting fold 2 target 0\n",
+      "my_len 4\n",
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+      "model [0.5579 0.4421] sum 0.9999993467855719\n",
+      "my_len 4\n",
+      "v34 f2 t0: original ll 0.0905/0.0844, ensemble ll 0.0905/0.0844\n",
+      "running time 2.990800380706787\n",
+      "starting fold 2 target 1\n",
+      "my_len 4\n",
+      "obj  0.012436140247391692\n",
+      "obj  0.012426658871830904\n",
+      "obj  0.012428926899146497\n",
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+      "model [0.1901 0.7899] sum 0.9800025514053641\n",
+      "my_len 4\n",
+      "v34 f2 t1: original ll 0.0150/0.0132, ensemble ll 0.0149/0.0131\n",
+      "running time 2.79952335357666\n",
+      "starting fold 2 target 2\n",
+      "my_len 4\n",
+      "obj  0.03864261774481127\n",
+      "obj  0.03864184039486668\n",
+      "obj  0.038641796041188246\n",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "model [0.3423 0.6557] sum 0.998008898781132\n",
+      "my_len 4\n",
+      "v34 f2 t2: original ll 0.0370/0.0348, ensemble ll 0.0369/0.0348\n",
+      "running time 3.07651686668396\n",
+      "starting fold 2 target 3\n",
+      "my_len 4\n",
+      "obj  0.022995224518522383\n",
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+      "my_len 4\n",
+      "v34 f2 t3: original ll 0.0236/0.0230, ensemble ll 0.0235/0.0229\n",
+      "running time 3.2023861408233643\n",
+      "starting fold 2 target 4\n",
+      "my_len 4\n",
+      "obj  0.05949662701641982\n",
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+      "model [0.3094 0.6888] sum 0.9982120655965214\n",
+      "my_len 4\n",
+      "v34 f2 t4: original ll 0.0608/0.0579, ensemble ll 0.0606/0.0578\n",
+      "running time 3.11377215385437\n",
+      "starting fold 2 target 5\n",
+      "my_len 4\n",
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+      "obj  0.07493779709805286\n",
+      "obj  0.0749435731885866\n",
+      "obj  0.0749166852814284\n",
+      "obj  0.07490477996495228\n",
+      "obj  0.0749038705129651\n",
+      "obj  0.07490382029340723\n",
+      "obj  0.07490381954831983\n",
+      "obj  0.07490381954523084\n",
+      "model [0.3463 0.6515] sum 0.9977752843293807\n",
+      "my_len 4\n",
+      "v34 f2 t5: original ll 0.0719/0.0680, ensemble ll 0.0718/0.0680\n",
+      "running time 3.083256244659424\n",
+      "total running time 54.07902908325195\n"
+     ]
+    }
+   ],
+   "source": [
+    "stg = time.time()\n",
+    "for fold in range(3):\n",
+    "    for target in range(6):\n",
+    "        train_ensemble(train_md, preds_all, fold=fold, target=target, weighted=True)\n",
+    "print('total running time', time.time() - stg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "starting fold 0 target 0\n",
+      "my_len 4\n",
+      "obj  0.0933852150101332\n",
+      "obj  0.09338046248442476\n",
+      "obj  0.09338029486041102\n",
+      "obj  0.09338035972731744\n",
+      "obj  0.0933811143108087\n",
+      "obj  0.09338210596694844\n",
+      "obj  0.09338474272802534\n",
+      "obj  0.09340376645538785\n",
+      "obj  0.0934854721225016\n",
+      "obj  0.09345651504702965\n",
+      "obj  0.09338703775747244\n",
+      "obj  0.09338029268632698\n",
+      "obj  0.09337958969300378\n",
+      "obj  0.09337955385335427\n",
+      "obj  0.0933795535198863\n",
+      "model [0.5182 0.4808] sum 0.9989492472281913\n",
+      "my_len 4\n",
+      "v33 f0 t0: original ll 0.0935/0.0887, ensemble ll 0.0935/0.0887\n",
+      "running time 3.2507238388061523\n",
+      "starting fold 0 target 1\n",
+      "my_len 4\n",
+      "obj  0.013897395265353997\n",
+      "obj  0.013881880847430866\n",
+      "obj  0.013885991780512735\n",
+      "obj  0.013876246790549903\n",
+      "obj  0.013881127990830817\n",
+      "obj  0.013894008184175567\n",
+      "obj  0.013882457611996777\n",
+      "obj  0.013884478813005323\n",
+      "obj  0.013863346223612806\n",
+      "obj  0.01383540008841151\n",
+      "obj  0.013825250237213925\n",
+      "obj  0.013818474145475493\n",
+      "obj  0.01381843625969093\n",
+      "obj  0.013818436182581805\n",
+      "obj  0.013818405670253893\n",
+      "model [0.2427 0.7373] sum 0.9800015590878185\n",
+      "my_len 4\n",
+      "v33 f0 t1: original ll 0.0149/0.0138, ensemble ll 0.0148/0.0137\n",
+      "running time 3.0066232681274414\n",
+      "starting fold 0 target 2\n",
+      "my_len 4\n",
+      "obj  0.03855627126313789\n",
+      "obj  0.03856925253658012\n",
+      "obj  0.03856923323281781\n",
+      "obj  0.03856931508023857\n",
+      "obj  0.038569302973706525\n",
+      "obj  0.03856915496260997\n",
+      "obj  0.03856899304326355\n",
+      "obj  0.03856816332340819\n",
+      "obj  0.0385645791222383\n",
+      "obj  0.03852293886610801\n",
+      "obj  0.03849000992229287\n",
+      "obj  0.038489241766752426\n",
+      "obj  0.038489236663254565\n",
+      "obj  0.038489183204291004\n",
+      "model [0.2783 0.7217] sum 0.9999990774048544\n",
+      "my_len 4\n",
+      "v33 f0 t2: original ll 0.0415/0.0392, ensemble ll 0.0415/0.0393\n",
+      "running time 2.8931853771209717\n",
+      "starting fold 0 target 3\n",
+      "my_len 4\n",
+      "obj  0.023471819011950737\n",
+      "obj  0.02346308538936012\n",
+      "obj  0.02346306370142104\n",
+      "obj  0.023463096870067094\n",
+      "obj  0.023463084589733965\n",
+      "obj  0.023463085675027997\n",
+      "obj  0.023463090035115736\n",
+      "obj  0.02346320596213014\n",
+      "obj  0.02346382293862838\n",
+      "obj  0.02348155081080937\n",
+      "obj  0.02343353697215318\n",
+      "obj  0.023433088692115203\n",
+      "obj  0.02343308800612711\n",
+      "obj  0.023433059211329016\n",
+      "model [0.306 0.694] sum 0.9999997220069807\n",
+      "my_len 4\n",
+      "v33 f0 t3: original ll 0.0243/0.0239, ensemble ll 0.0243/0.0239\n",
+      "running time 2.9580657482147217\n",
+      "starting fold 0 target 4\n",
+      "my_len 4\n",
+      "obj  0.06201436184726342\n",
+      "obj  0.061994016197883355\n",
+      "obj  0.061996952747678406\n",
+      "obj  0.061997831217601926\n",
+      "obj  0.06201332307115508\n",
+      "obj  0.06200539452619764\n",
+      "obj  0.061997782770088716\n",
+      "obj  0.061999809977407665\n",
+      "obj  0.061946341140497775\n",
+      "obj  0.06189433265221826\n",
+      "obj  0.06187496883012553\n",
+      "obj  0.06187358174569984\n",
+      "obj  0.061873550371914346\n",
+      "obj  0.06187354965251176\n",
+      "obj  0.06187354965195954\n",
+      "model [0.1759 0.8163] sum 0.9922753054062554\n",
+      "my_len 4\n",
+      "v33 f0 t4: original ll 0.0617/0.0596, ensemble ll 0.0617/0.0596\n",
+      "running time 3.1102256774902344\n",
+      "starting fold 0 target 5\n",
+      "my_len 4\n",
+      "obj  0.07485970317009938\n",
+      "obj  0.07484302022808972\n",
+      "obj  0.07484070942818977\n",
+      "obj  0.07484219496860454\n",
+      "obj  0.07485295263606241\n",
+      "obj  0.07484035286995884\n",
+      "obj  0.07484141900156345\n",
+      "obj  0.07484183422896018\n",
+      "obj  0.0748343331646704\n",
+      "obj  0.07483511386213709\n",
+      "obj  0.07482549187014455\n",
+      "obj  0.0748237146789029\n",
+      "obj  0.07482368467518487\n",
+      "obj  0.07482367083879939\n",
+      "obj  0.07482367083046154\n",
+      "model [0.3925 0.6007] sum 0.9931778590255735\n",
+      "my_len 4\n",
+      "v33 f0 t5: original ll 0.0789/0.0757, ensemble ll 0.0789/0.0757\n",
+      "running time 3.0676307678222656\n",
+      "starting fold 1 target 0\n",
+      "my_len 4\n",
+      "obj  0.0919894615986076\n",
+      "obj  0.09198934066490368\n",
+      "obj  0.09198934060039965\n",
+      "obj  0.0919893485003721\n",
+      "obj  0.09198977183141734\n",
+      "obj  0.09199123504674073\n",
+      "obj  0.09199391461415146\n",
+      "obj  0.09201565951872456\n",
+      "obj  0.09211729091908993\n",
+      "obj  0.09208098074046837\n",
+      "obj  0.0919837225645165\n",
+      "obj  0.0919736624585904\n",
+      "obj  0.09197157155893894\n",
+      "obj  0.09197109088607663\n",
+      "obj  0.09197098268778833\n",
+      "obj  0.09197095367445211\n",
+      "obj  0.0919709467643533\n",
+      "model [0.5953 0.4047] sum 0.9999621194280907\n",
+      "my_len 4\n",
+      "v33 f1 t0: original ll 0.0963/0.0902, ensemble ll 0.0963/0.0902\n",
+      "running time 3.3472983837127686\n",
+      "starting fold 1 target 1\n",
+      "my_len 4\n",
+      "obj  0.014958787142420498\n",
+      "obj  0.014937330106503348\n",
+      "obj  0.014942650987592622\n",
+      "obj  0.014975860772633154\n",
+      "obj  0.014972362994514807\n",
+      "obj  0.014957564541716397\n",
+      "obj  0.014951577023955265\n",
+      "obj  0.014951063187963957\n",
+      "obj  0.01491070342318423\n",
+      "obj  0.014853979550418115\n",
+      "obj  0.014829774294376331\n",
+      "obj  0.014821112462190839\n",
+      "obj  0.014821058186807711\n",
+      "obj  0.0148210268020669\n",
+      "obj  0.01482102580854534\n",
+      "model [0.1376 0.8624] sum 0.9999999409483264\n",
+      "my_len 4\n",
+      "v33 f1 t1: original ll 0.0128/0.0110, ensemble ll 0.0128/0.0110\n",
+      "running time 2.9967260360717773\n",
+      "starting fold 1 target 2\n",
+      "my_len 4\n",
+      "obj  0.039245835968578474\n",
+      "obj  0.03924574127471867\n",
+      "obj  0.039245713624497434\n",
+      "obj  0.03924588587989087\n",
+      "obj  0.03924803573797128\n",
+      "obj  0.03925147467544376\n",
+      "obj  0.0392563703952373\n",
+      "obj  0.03927551263462263\n",
+      "obj  0.03925650976537233\n",
+      "obj  0.03926796310975214\n",
+      "obj  0.0392185324397789\n",
+      "obj  0.039216537422768455\n",
+      "obj  0.039216281028530475\n",
+      "obj  0.039216255398415924\n",
+      "obj  0.03921625454996835\n",
+      "obj  0.039216254539564024\n",
+      "model [0.3469 0.6519] sum 0.9988259427442799\n",
+      "my_len 4\n",
+      "v33 f1 t2: original ll 0.0401/0.0381, ensemble ll 0.0401/0.0381\n",
+      "running time 3.1578216552734375\n",
+      "starting fold 1 target 3\n",
+      "my_len 4\n",
+      "obj  0.02395696038549021\n",
+      "obj  0.02395486428261125\n",
+      "obj  0.023954835163552384\n",
+      "obj  0.023954877532169596\n",
+      "obj  0.023955568418781947\n",
+      "obj  0.023963995166198675\n",
+      "obj  0.023978023975066425\n",
+      "obj  0.024002845343395824\n",
+      "obj  0.023983817519113094\n",
+      "obj  0.023997071439984398\n",
+      "obj  0.02394045500310195\n",
+      "obj  0.023937978579431436\n",
+      "obj  0.0239372920681272\n",
+      "obj  0.02393711483122209\n",
+      "obj  0.02393708937017656\n",
+      "model [0.359 0.641] sum 0.9999985792555948\n",
+      "my_len 4\n",
+      "v33 f1 t3: original ll 0.0233/0.0221, ensemble ll 0.0233/0.0220\n",
+      "running time 3.0442991256713867\n",
+      "starting fold 1 target 4\n",
+      "my_len 4\n",
+      "obj  0.061258507345704066\n",
+      "obj  0.061265689746832726\n",
+      "obj  0.06126562077837275\n",
+      "obj  0.061265854859751424\n",
+      "obj  0.0612658046238735\n",
+      "obj  0.061265351617187\n",
+      "obj  0.061264866771111565\n",
+      "obj  0.061262444514258725\n",
+      "obj  0.061251536610214256\n",
+      "obj  0.06115744444115026\n",
+      "obj  0.061149983693155184\n",
+      "obj  0.061149771919456586\n",
+      "obj  0.061149771087428396\n",
+      "obj  0.06114975345151202\n",
+      "model [0.2158 0.7842] sum 0.9999996248180504\n",
+      "my_len 4\n",
+      "v33 f1 t4: original ll 0.0632/0.0594, ensemble ll 0.0632/0.0594\n",
+      "running time 2.8806824684143066\n",
+      "starting fold 1 target 5\n",
+      "my_len 4\n",
+      "obj  0.07535926071665933\n",
+      "obj  0.07534861733988092\n",
+      "obj  0.07534762674133844\n",
+      "obj  0.07534904493869508\n",
+      "obj  0.07535936082490458\n",
+      "obj  0.0753471265997745\n",
+      "obj  0.07534426077367337\n",
+      "obj  0.07534711702093719\n",
+      "obj  0.07533211331536023\n",
+      "obj  0.07533317814561168\n",
+      "obj  0.07531220405379302\n",
+      "obj  0.07530996229389857\n",
+      "obj  0.07530993777029112\n",
+      "obj  0.07530993774604199\n",
+      "model [0.3331 0.6604] sum 0.993527447026961\n",
+      "my_len 4\n",
+      "v33 f1 t5: original ll 0.0779/0.0742, ensemble ll 0.0779/0.0742\n",
+      "running time 2.8882410526275635\n",
+      "starting fold 2 target 0\n",
+      "my_len 4\n",
+      "obj  0.09489490438158145\n",
+      "obj  0.09489430912501066\n",
+      "obj  0.09489431102390815\n",
+      "obj  0.09489431535393611\n",
+      "obj  0.0948945806962745\n",
+      "obj  0.09489608391205885\n",
+      "obj  0.09489866734487919\n",
+      "obj  0.0949200247646217\n",
+      "obj  0.09503918400778456\n",
+      "obj  0.09501153296540055\n",
+      "obj  0.09490249627913898\n",
+      "obj  0.09488951860739707\n",
+      "obj  0.09488647087827386\n",
+      "obj  0.09488564556714987\n",
+      "obj  0.0948854679188669\n",
+      "obj  0.09488545200417911\n",
+      "model [0.5661 0.4339] sum 0.9999997699565845\n",
+      "my_len 4\n",
+      "v33 f2 t0: original ll 0.0905/0.0845, ensemble ll 0.0905/0.0845\n",
+      "running time 3.214533567428589\n",
+      "starting fold 2 target 1\n",
+      "my_len 4\n",
+      "obj  0.013868197433815987\n",
+      "obj  0.01386027871457582\n",
+      "obj  0.013862065714890364\n",
+      "obj  0.013858828553407412\n",
+      "obj  0.013860879366817503\n",
+      "obj  0.013866290527273424\n",
+      "obj  0.013857530201794333\n",
+      "obj  0.013858298202236378\n",
+      "obj  0.013836364815367146\n",
+      "obj  0.013804921280345871\n",
+      "obj  0.01379261828630837\n",
+      "obj  0.013789536265747205\n",
+      "obj  0.013789525064620644\n",
+      "model [0.2207 0.7593] sum 0.980004158654775\n",
+      "my_len 4\n",
+      "v33 f2 t1: original ll 0.0150/0.0133, ensemble ll 0.0149/0.0131\n",
+      "running time 2.7753772735595703\n",
+      "starting fold 2 target 2\n",
+      "my_len 4\n",
+      "obj  0.04081306058254699\n",
+      "obj  0.040812031203401905\n",
+      "obj  0.040811937510774186\n",
+      "obj  0.04081223601044173\n",
+      "obj  0.04081528137789779\n",
+      "obj  0.04081538347060062\n",
+      "obj  0.04081682793135578\n",
+      "obj  0.04083251985984981\n",
+      "obj  0.040810479353506623\n",
+      "obj  0.04081936079563107\n",
+      "obj  0.04077962409069144\n",
+      "obj  0.04077101062103325\n",
+      "obj  0.0407701494171347\n",
+      "obj  0.04077012004624905\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "obj  0.040770119816992766\n",
+      "model [0.3174 0.68  ] sum 0.9973906231915857\n",
+      "my_len 4\n",
+      "v33 f2 t2: original ll 0.0370/0.0348, ensemble ll 0.0370/0.0348\n",
+      "running time 3.0440049171447754\n",
+      "starting fold 2 target 3\n",
+      "my_len 4\n",
+      "obj  0.023823516135291243\n",
+      "obj  0.02382017911708748\n",
+      "obj  0.023820106378154727\n",
+      "obj  0.023820136798804403\n",
+      "obj  0.023820572725337157\n",
+      "obj  0.02383469183098074\n",
+      "obj  0.02384809531847105\n",
+      "obj  0.023873357339416913\n",
+      "obj  0.02385181419582523\n",
+      "obj  0.02386641578011786\n",
+      "obj  0.023805227006125536\n",
+      "obj  0.023802547496832128\n",
+      "obj  0.023801797197722675\n",
+      "obj  0.02380161177878747\n",
+      "obj  0.02380158861610797\n",
+      "model [0.3532 0.6468] sum 0.9999989006282439\n",
+      "my_len 4\n",
+      "v33 f2 t3: original ll 0.0236/0.0230, ensemble ll 0.0236/0.0229\n",
+      "running time 3.017551898956299\n",
+      "starting fold 2 target 4\n",
+      "my_len 4\n",
+      "obj  0.06243179531025402\n",
+      "obj  0.062427099035585125\n",
+      "obj  0.06242713613481103\n",
+      "obj  0.062430316328200154\n",
+      "obj  0.06243658002881348\n",
+      "obj  0.062430816202982437\n",
+      "obj  0.06243507738993893\n",
+      "obj  0.06244554339226623\n",
+      "obj  0.062427434946619766\n",
+      "obj  0.06243147007524259\n",
+      "obj  0.06240271238770716\n",
+      "obj  0.06239411214025914\n",
+      "obj  0.062393648133430374\n",
+      "obj  0.06239362889706076\n",
+      "obj  0.06239362873376792\n",
+      "model [0.3265 0.6706] sum 0.9971639400865144\n",
+      "my_len 4\n",
+      "v33 f2 t4: original ll 0.0608/0.0580, ensemble ll 0.0607/0.0578\n",
+      "running time 3.0167412757873535\n",
+      "starting fold 2 target 5\n",
+      "my_len 4\n",
+      "obj  0.07838134560788608\n",
+      "obj  0.07838076163206673\n",
+      "obj  0.07838071177563007\n",
+      "obj  0.07838080623175392\n",
+      "obj  0.07838065017243255\n",
+      "obj  0.07838512557832436\n",
+      "obj  0.07839379106272942\n",
+      "obj  0.07841541302344214\n",
+      "obj  0.07839227446721775\n",
+      "obj  0.0784030307958988\n",
+      "obj  0.07835324790612748\n",
+      "obj  0.078350745139307\n",
+      "obj  0.07835024106315232\n",
+      "obj  0.07835010723361426\n",
+      "obj  0.07835007445229823\n",
+      "obj  0.07835006754602017\n",
+      "obj  0.0783500665027853\n",
+      "obj  0.07835006642985422\n",
+      "model [0.366  0.6339] sum 0.999906731906863\n",
+      "my_len 4\n",
+      "v33 f2 t5: original ll 0.0718/0.0680, ensemble ll 0.0718/0.0680\n",
+      "running time 3.3957345485687256\n",
+      "total running time 55.21563124656677\n"
+     ]
+    }
+   ],
+   "source": [
+    "stg = time.time()\n",
+    "for fold in range(3):\n",
+    "    for target in range(6):\n",
+    "        train_ensemble(train_md, preds_all, fold=fold, target=target, weighted=False)\n",
+    "print('total running time', time.time() - stg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>valid_loss</th>\n",
+       "      <th>valid_loss_ens</th>\n",
+       "      <th>valid_w_loss</th>\n",
+       "      <th>valid_w_loss_ens</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>weighted</th>\n",
+       "      <th>target</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td rowspan=\"6\" valign=\"top\">False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.093420</td>\n",
+       "      <td>0.093428</td>\n",
+       "      <td>0.087781</td>\n",
+       "      <td>0.087797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>0.014243</td>\n",
+       "      <td>0.014183</td>\n",
+       "      <td>0.012694</td>\n",
+       "      <td>0.012633</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>0.039539</td>\n",
+       "      <td>0.039512</td>\n",
+       "      <td>0.037398</td>\n",
+       "      <td>0.037367</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>0.023751</td>\n",
+       "      <td>0.023728</td>\n",
+       "      <td>0.022988</td>\n",
+       "      <td>0.022953</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>0.061900</td>\n",
+       "      <td>0.061866</td>\n",
+       "      <td>0.058991</td>\n",
+       "      <td>0.058947</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>0.076200</td>\n",
+       "      <td>0.076194</td>\n",
+       "      <td>0.072653</td>\n",
+       "      <td>0.072625</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 valid_loss  valid_loss_ens  valid_w_loss  valid_w_loss_ens\n",
+       "weighted target                                                            \n",
+       "False    0         0.093420        0.093428      0.087781          0.087797\n",
+       "         1         0.014243        0.014183      0.012694          0.012633\n",
+       "         2         0.039539        0.039512      0.037398          0.037367\n",
+       "         3         0.023751        0.023728      0.022988          0.022953\n",
+       "         4         0.061900        0.061866      0.058991          0.058947\n",
+       "         5         0.076200        0.076194      0.072653          0.072625"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stats = pd.read_csv(PATH_DISK/'ensemble'/'stats.v{}'.format(VERSION))\n",
+    "stats.groupby(['weighted','target'])[['valid_loss','valid_loss_ens','valid_w_loss','valid_w_loss_ens']].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>not weighted</th>\n",
+       "      <th>weighted</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>valid_loss</td>\n",
+       "      <td>0.057518</td>\n",
+       "      <td>0.057518</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss</td>\n",
+       "      <td>0.054293</td>\n",
+       "      <td>0.054293</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_loss_ens</td>\n",
+       "      <td>0.057500</td>\n",
+       "      <td>0.057498</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss_ens</td>\n",
+       "      <td>0.054274</td>\n",
+       "      <td>0.054269</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  not weighted  weighted\n",
+       "valid_loss            0.057518  0.057518\n",
+       "valid_w_loss          0.054293  0.054293\n",
+       "valid_loss_ens        0.057500  0.057498\n",
+       "valid_w_loss_ens      0.054274  0.054269"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# STAGE2 weighted models\n",
+    "tt = pd.concat([\n",
+    "stats.loc[stats.weighted == False].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                      'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean(),\n",
+    "stats.loc[stats.weighted == True].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                     'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean()\n",
+    "],axis=1)\n",
+    "tt.columns = ['not weighted','weighted']\n",
+    "tt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>not weighted</th>\n",
+       "      <th>weighted</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>valid_loss</td>\n",
+       "      <td>0.057496</td>\n",
+       "      <td>0.057496</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss</td>\n",
+       "      <td>0.054326</td>\n",
+       "      <td>0.054326</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_loss_ens</td>\n",
+       "      <td>0.057477</td>\n",
+       "      <td>0.057475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss_ens</td>\n",
+       "      <td>0.054303</td>\n",
+       "      <td>0.054299</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  not weighted  weighted\n",
+       "valid_loss            0.057496  0.057496\n",
+       "valid_w_loss          0.054326  0.054326\n",
+       "valid_loss_ens        0.057477  0.057475\n",
+       "valid_w_loss_ens      0.054303  0.054299"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# STAGE2 non-wegihted models\n",
+    "tt = pd.concat([\n",
+    "stats.loc[stats.weighted == False].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                      'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean(),\n",
+    "stats.loc[stats.weighted == True].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                     'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean()\n",
+    "],axis=1)\n",
+    "tt.columns = ['not weighted','weighted']\n",
+    "tt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>not weighted</th>\n",
+       "      <th>weighted</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>valid_loss</td>\n",
+       "      <td>0.057750</td>\n",
+       "      <td>0.057750</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss</td>\n",
+       "      <td>0.061831</td>\n",
+       "      <td>0.061831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_loss_ens</td>\n",
+       "      <td>0.057658</td>\n",
+       "      <td>0.058210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss_ens</td>\n",
+       "      <td>0.062176</td>\n",
+       "      <td>0.061514</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  not weighted  weighted\n",
+       "valid_loss            0.057750  0.057750\n",
+       "valid_w_loss          0.061831  0.061831\n",
+       "valid_loss_ens        0.057658  0.058210\n",
+       "valid_w_loss_ens      0.062176  0.061514"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# wegihted models\n",
+    "tt = pd.concat([\n",
+    "stats.loc[stats.weighted == False].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                      'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean(),\n",
+    "stats.loc[stats.weighted == True].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                     'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean()\n",
+    "],axis=1)\n",
+    "tt.columns = ['not weighted','weighted']\n",
+    "tt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>not weighted</th>\n",
+       "      <th>weighted</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>valid_loss</td>\n",
+       "      <td>0.057661</td>\n",
+       "      <td>0.057661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss</td>\n",
+       "      <td>0.062715</td>\n",
+       "      <td>0.062715</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_loss_ens</td>\n",
+       "      <td>0.057638</td>\n",
+       "      <td>0.057799</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>valid_w_loss_ens</td>\n",
+       "      <td>0.062705</td>\n",
+       "      <td>0.062648</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  not weighted  weighted\n",
+       "valid_loss            0.057661  0.057661\n",
+       "valid_w_loss          0.062715  0.062715\n",
+       "valid_loss_ens        0.057638  0.057799\n",
+       "valid_w_loss_ens      0.062705  0.062648"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# non-weighted models\n",
+    "tt = pd.concat([\n",
+    "stats.loc[stats.weighted == False].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                      'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean(),\n",
+    "stats.loc[stats.weighted == True].groupby('target')[['valid_loss','valid_w_loss',\n",
+    "                                                     'valid_loss_ens','valid_w_loss_ens']].mean()\\\n",
+    "    .apply(lambda x: x*class_weights).mean()\n",
+    "],axis=1)\n",
+    "tt.columns = ['not weighted','weighted']\n",
+    "tt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 [0.5599 0.4398] 0.9996370455376221\n",
+      "1 [0.2003 0.7864] 0.9866685528969734\n",
+      "2 [0.3142 0.6845] 0.99873854778024\n",
+      "3 [0.3394 0.6606] 0.9999990672969397\n",
+      "4 [0.2394 0.7571] 0.9964796234369401\n",
+      "5 [0.3639 0.6317] 0.9955373459864658\n",
+      "total [0.3362 0.66  ] 0.9961766971558637\n"
+     ]
+    }
+   ],
+   "source": [
+    "np.set_printoptions(precision=4)\n",
+    "res2_all = []\n",
+    "for target in range(6):\n",
+    "    res2 = np.zeros((3, 2))\n",
+    "    for fold in range(3):\n",
+    "        model = pickle.load(open(PATH_DISK/'ensemble'/'model.f{}.t{}.v{}'\n",
+    "                                 .format(fold,target,VERSION),'rb'))\n",
+    "        res2[fold] = model.x\n",
+    "        #print(fold,target,model.x)\n",
+    "    print(target, res2.mean(0), res2.mean(0).sum())\n",
+    "    res2_all.append(res2)\n",
+    "print('total', np.stack(res2_all).mean((0,1)), np.stack(res2_all).mean((0,1)).sum())"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {},
+   "source": [
+    "# STAGE2 weighted\n",
+    "0 [0.5514 0.4486] 0.999988938547882\n",
+    "1 [0.1934 0.7932] 0.9866673384339762\n",
+    "2 [0.3245 0.6748] 0.99933085408868\n",
+    "3 [0.2924 0.7076] 0.999999807185227\n",
+    "4 [0.2338 0.7643] 0.9981083416558326\n",
+    "5 [0.347  0.6474] 0.9944152840034981\n",
+    "total [0.3237 0.6727] 0.9964184273191827\n",
+    "\n",
+    "\n",
+    "# STAGE2 non-weighted\n",
+    "0 [0.5599 0.4398] 0.9996370455376221\n",
+    "1 [0.2003 0.7864] 0.9866685528969734\n",
+    "2 [0.3142 0.6845] 0.99873854778024\n",
+    "3 [0.3394 0.6606] 0.9999990672969397\n",
+    "4 [0.2394 0.7571] 0.9964796234369401\n",
+    "5 [0.3639 0.6317] 0.9955373459864658\n",
+    "total [0.3362 0.66  ] 0.9961766971558637\n",
+    "\n",
+    "# weighted + focal both\n",
+    "0 [9.8936e-01 4.6289e-06] 0.9893636389192056\n",
+    "1 [0.1052 0.8948] 0.9999984169006635\n",
+    "2 [0.4988 0.49  ] 0.9887665083664696\n",
+    "3 [0.3443 0.6427] 0.9869733391806492\n",
+    "4 [0.4923 0.4959] 0.9882284866416893\n",
+    "5 [0.7736 0.217 ] 0.9906108307629572\n",
+    "total [0.5339 0.4567] 0.9906568701286057\n",
+    "\n",
+    "# weighted + focal\n",
+    "0 [0.9758 0.0133] 0.9890208236733224\n",
+    "1 [0.0755 0.9245] 0.99999750757956\n",
+    "2 [0.5121 0.4765] 0.9885906315242545\n",
+    "3 [0.3465 0.6394] 0.9858337972624043\n",
+    "4 [0.4733 0.5144] 0.987734118671811\n",
+    "5 [0.6697 0.3208] 0.9904312808036815\n",
+    "total [0.5088 0.4815] 0.990268026585839\n",
+    "\n",
+    "# weighted\n",
+    "0 [0.9856 0.0034] 0.9890322827488863\n",
+    "1 [0.1394 0.8606] 0.9999977090921796\n",
+    "2 [0.5308 0.4582] 0.9890278807370222\n",
+    "3 [0.3542 0.6317] 0.9858961392052805\n",
+    "4 [0.4851 0.5028] 0.9879196279125524\n",
+    "5 [0.7677 0.2223] 0.9900299923215763\n",
+    "total [0.5438 0.4465] 0.9903172720029163\n",
+    "\n",
+    "# non-weighted\n",
+    "0 [0.3504 0.6483] 0.9987279422120475\n",
+    "1 [0.16   0.8267] 0.9866673030259768\n",
+    "2 [0.2285 0.7706] 0.9990219638127198\n",
+    "3 [0.2355 0.7636] 0.9991180197159109\n",
+    "4 [0.1587 0.8378] 0.9965445852859403\n",
+    "5 [0.2654 0.7281] 0.9934664823990461\n",
+    "total [0.2331 0.7625] 0.995591049408607"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds3 = np.stack([pickle.load(open(PATH_DISK/'preds_d{}_v{}'.format(ds, VERSION),'rb')) for ds in my_datasets3])\n",
+    "preds5 = np.stack([pickle.load(open(PATH_DISK/'preds_d{}_v{}'.format(ds, VERSION),'rb')) for ds in my_datasets5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds = np.concatenate([preds3.mean((1,2)), preds5.mean((1,2))],axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#del test_md['yuval_idx']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "yuval_test = pickle.load(open(PATH_DISK/'yuval/ensemble_test_image_ids_stage2.pkl','rb'))\n",
+    "assert len(yuval_test) == len(test_md)\n",
+    "\n",
+    "df = pd.DataFrame(np.arange(len(yuval_test)), columns=['yuval_idx'])\n",
+    "df.index = yuval_test\n",
+    "test_md = test_md.join(df, on = 'img_id')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_y3 = [\n",
+    "    #'model_Densenet201_3_version_classifier_splits_fullhead_resmodel_pool2_3_type_OOF_pred_split_{}.pkl',\n",
+    "    #'model_Densenet161_3_version_classifier_splits_fullhead_resmodel_pool2_3_type_OOF_pred_split_{}.pkl',\n",
+    "'model_Densenet169_3_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl',\n",
+    "'model_se_resnext101_32x4d_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl',\n",
+    "'model_se_resnet101_version_classifier_splits_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl'\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_y5 = [\n",
+    "'model_se_resnext101_32x4d_version_new_splits_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl',\n",
+    "'model_se_resnet101_version_new_splits_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl',\n",
+    "'model_se_resnet101_version_new_splits_focal_fullhead_resmodel_pool2_stage2_3_type_test_pred_ensemble_split_{}.pkl',\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_y3 = np.stack([torch.sigmoid(torch.stack([torch.stack(pickle.load(\n",
+    "    open(PATH_DISK/'yuval/OOF_stage2'/name.format(fold),'rb'))) for fold in range(3)])).numpy() for name in names_y3])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_y5 = np.stack([torch.sigmoid(torch.stack([torch.stack(pickle.load(\n",
+    "    open(PATH_DISK/'yuval/OOF_stage2'/name.format(fold),'rb'))) for fold in range(5)])).numpy() for name in names_y5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_y = np.concatenate([preds_y3.mean((1,2)), preds_y5.mean((1,2))],axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds_y = preds_y[:,test_md.yuval_idx]\n",
+    "preds_y = preds_y[:,:,np.array([5,0,1,2,3,4])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds = np.concatenate([preds, preds_y], axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds = preds[ds_mask]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 121232, 6)"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "any too low inconsistencies\n",
+      "1 class: 0.000837237693018345\n",
+      "2 class: 0.016652369011482118\n",
+      "3 class: 0.008991850336544807\n",
+      "4 class: 0.016291903127887027\n",
+      "5 class: 0.05360135937706216\n",
+      "total 0.08837930579384981\n",
+      "any too high inconsistencies\n",
+      "total 0.21430810347103074\n"
+     ]
+    }
+   ],
+   "source": [
+    "preds = predBounding(preds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#predictions = preds.mean((0,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "version 33 my_len 4\n",
+      "total running time 0.07065796852111816\n"
+     ]
+    }
+   ],
+   "source": [
+    "stg = time.time()\n",
+    "\n",
+    "test_preds_trgt = []\n",
+    "print('version', VERSION, 'my_len', my_len)\n",
+    "for target in range(6):\n",
+    "    \n",
+    "    test_preds_fold = []\n",
+    "    for fold in range(3):\n",
+    "        X = np.stack([preds[:my_len,:,target].mean(0), \n",
+    "                      preds[my_len:,:,target].mean(0)], axis=0)\n",
+    "        \n",
+    "        model = pickle.load(open(PATH_DISK/'ensemble'/'model.f{}.t{}.v{}'.format(fold,target,VERSION),'rb'))\n",
+    "        test_preds_fold.append((X*np.expand_dims(model.x, axis=1)).sum(0))\n",
+    "    \n",
+    "    test_preds_trgt.append(np.stack(test_preds_fold).mean(0))\n",
+    "\n",
+    "predictions = np.stack(test_preds_trgt,axis=1)\n",
+    "\n",
+    "print('total running time', time.time() - stg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1.    , 0.9956, 0.9954, 0.9953, 0.9958, 0.9937, 0.9942, 0.9947,\n",
+       "        0.9946, 0.9943],\n",
+       "       [0.9956, 1.    , 0.9978, 0.9977, 0.9951, 0.997 , 0.9964, 0.9986,\n",
+       "        0.997 , 0.9967],\n",
+       "       [0.9954, 0.9978, 1.    , 0.9992, 0.9951, 0.9956, 0.9972, 0.9966,\n",
+       "        0.9984, 0.9978],\n",
+       "       [0.9953, 0.9977, 0.9992, 1.    , 0.995 , 0.9957, 0.9973, 0.9967,\n",
+       "        0.9982, 0.9985],\n",
+       "       [0.9958, 0.9951, 0.9951, 0.995 , 1.    , 0.9944, 0.9949, 0.9954,\n",
+       "        0.9955, 0.9951],\n",
+       "       [0.9937, 0.997 , 0.9956, 0.9957, 0.9944, 1.    , 0.9965, 0.998 ,\n",
+       "        0.9968, 0.9967],\n",
+       "       [0.9942, 0.9964, 0.9972, 0.9973, 0.9949, 0.9965, 1.    , 0.9971,\n",
+       "        0.9983, 0.9982],\n",
+       "       [0.9947, 0.9986, 0.9966, 0.9967, 0.9954, 0.998 , 0.9971, 1.    ,\n",
+       "        0.9979, 0.9977],\n",
+       "       [0.9946, 0.997 , 0.9984, 0.9982, 0.9955, 0.9968, 0.9983, 0.9979,\n",
+       "        1.    , 0.9993],\n",
+       "       [0.9943, 0.9967, 0.9978, 0.9985, 0.9951, 0.9967, 0.9982, 0.9977,\n",
+       "        0.9993, 1.    ]])"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.corrcoef(preds[:,:,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(121232, 6)"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "predictions.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Submitting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "id_column = np.array([a + '_' + b for a in test_md.SOPInstanceUID for b in all_ich])\n",
+    "sub = pd.DataFrame({'ID': id_column, 'Label': predictions.reshape(-1)})\n",
+    "sub.to_csv(PATH/'sub.csv', index=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Sanity checks"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_md['pred_any'] = predictions[:,0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>12436</td>\n",
+       "      <td>68c2b8b03</td>\n",
+       "      <td>ID_68c2b8b03</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_db5b61c1</td>\n",
+       "      <td>ID_451abcb4a1</td>\n",
+       "      <td>ID_36778f2a4a</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-148.300', '135.250']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064000</td>\n",
+       "      <td>-1.548000</td>\n",
+       "      <td>-1.402099</td>\n",
+       "      <td>-1.620352</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-148.3</td>\n",
+       "      <td>135.250000</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-1.110667</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.045487</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.5810</td>\n",
+       "      <td>-0.1190</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>1.355932</td>\n",
+       "      <td>37</td>\n",
+       "      <td>-1.016949</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.266667</td>\n",
+       "      <td>1.771429</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>-0.600000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>80726</td>\n",
+       "      <td>0.000082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>82308</td>\n",
+       "      <td>7f95e978e</td>\n",
+       "      <td>ID_7f95e978e</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_ae6fa62a</td>\n",
+       "      <td>ID_3a1815c27a</td>\n",
+       "      <td>ID_64db061397</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-108.000', '-116.300', '114.000']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.421875', '0.421875']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>100</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064000</td>\n",
+       "      <td>-1.572000</td>\n",
+       "      <td>-1.392679</td>\n",
+       "      <td>-1.599246</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-108.0</td>\n",
+       "      <td>-116.3</td>\n",
+       "      <td>114.000000</td>\n",
+       "      <td>0.421875</td>\n",
+       "      <td>0.421875</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.733333</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.684000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.075931</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.295</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.4760</td>\n",
+       "      <td>-0.1840</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>1.016949</td>\n",
+       "      <td>32</td>\n",
+       "      <td>-1.084746</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.878788</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.600000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>68171</td>\n",
+       "      <td>0.000082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>60800</td>\n",
+       "      <td>84735b84a</td>\n",
+       "      <td>ID_84735b84a</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_ddcad7d4</td>\n",
+       "      <td>ID_d7e80c40be</td>\n",
+       "      <td>ID_11c94b7b33</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-155', '23', '138.699997']</td>\n",
+       "      <td>['1', '0', '0', '0', '1', '0']</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00036', '00036']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.314667</td>\n",
+       "      <td>-1.914667</td>\n",
+       "      <td>-2.872322</td>\n",
+       "      <td>-0.693297</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-155.0</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>138.699997</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.480000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.173333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.040544</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.5748</td>\n",
+       "      <td>-0.1252</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>1.152542</td>\n",
+       "      <td>34</td>\n",
+       "      <td>-1.084746</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.266666</td>\n",
+       "      <td>1.885714</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599994</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>27981</td>\n",
+       "      <td>0.000083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>102453</td>\n",
+       "      <td>d6a5e0432</td>\n",
+       "      <td>ID_d6a5e0432</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_73887cfd</td>\n",
+       "      <td>ID_4cc0b3574d</td>\n",
+       "      <td>ID_bd88957d37</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-131.700', '105.000']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064000</td>\n",
+       "      <td>-1.558667</td>\n",
+       "      <td>-1.401150</td>\n",
+       "      <td>-1.616006</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-131.7</td>\n",
+       "      <td>105.000000</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.889333</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.088825</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.480</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.4400</td>\n",
+       "      <td>-0.1800</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>0.881356</td>\n",
+       "      <td>30</td>\n",
+       "      <td>-1.084746</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.266667</td>\n",
+       "      <td>1.870968</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.600000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>90163</td>\n",
+       "      <td>0.000085</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10097</td>\n",
+       "      <td>6df94672e</td>\n",
+       "      <td>ID_6df94672e</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_39c82642</td>\n",
+       "      <td>ID_9f4b3b7a4d</td>\n",
+       "      <td>ID_81c1365f46</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '18', '-120.099976']</td>\n",
+       "      <td>['1', '0', '0', '0', '1', '0']</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00036', '00036']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.108000</td>\n",
+       "      <td>-2.544276</td>\n",
+       "      <td>-0.594726</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>-120.099976</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.106667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.411318</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>-0.4404</td>\n",
+       "      <td>-1.4004</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>1.966102</td>\n",
+       "      <td>46</td>\n",
+       "      <td>-1.016949</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.833333</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.600000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>14678</td>\n",
+       "      <td>0.000086</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "12436   68c2b8b03   ID_68c2b8b03       CT  ID_db5b61c1    ID_451abcb4a1   \n",
+       "82308   7f95e978e   ID_7f95e978e       CT  ID_ae6fa62a    ID_3a1815c27a   \n",
+       "60800   84735b84a   ID_84735b84a       CT  ID_ddcad7d4    ID_d7e80c40be   \n",
+       "102453  d6a5e0432   ID_d6a5e0432       CT  ID_73887cfd    ID_4cc0b3574d   \n",
+       "10097   6df94672e   ID_6df94672e       CT  ID_39c82642    ID_9f4b3b7a4d   \n",
+       "\n",
+       "       SeriesInstanceUID  StudyID                 ImagePositionPatient  \\\n",
+       "12436      ID_36778f2a4a      NaN  ['-125.000', '-148.300', '135.250']   \n",
+       "82308      ID_64db061397      NaN  ['-108.000', '-116.300', '114.000']   \n",
+       "60800      ID_11c94b7b33      NaN         ['-155', '23', '138.699997']   \n",
+       "102453     ID_bd88957d37      NaN  ['-125.000', '-131.700', '105.000']   \n",
+       "10097      ID_81c1365f46      NaN        ['-125', '18', '-120.099976']   \n",
+       "\n",
+       "                                  ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "12436   ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "82308   ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "60800                      ['1', '0', '0', '0', '1', '0']                1   \n",
+       "102453  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "10097                      ['1', '0', '0', '0', '1', '0']                1   \n",
+       "\n",
+       "       PhotometricInterpretation  Rows  Columns                  PixelSpacing  \\\n",
+       "12436                MONOCHROME2   512      512      ['0.488281', '0.488281']   \n",
+       "82308                MONOCHROME2   512      512      ['0.421875', '0.421875']   \n",
+       "60800                MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "102453               MONOCHROME2   512      512      ['0.488281', '0.488281']   \n",
+       "10097                MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "\n",
+       "        BitsAllocated  BitsStored  HighBit  PixelRepresentation  \\\n",
+       "12436              16          16       15                    1   \n",
+       "82308              16          16       15                    1   \n",
+       "60800              16          12       11                    0   \n",
+       "102453             16          16       15                    1   \n",
+       "10097              16          12       11                    0   \n",
+       "\n",
+       "              WindowCenter         WindowWidth  RescaleIntercept  \\\n",
+       "12436                   40                 150           -1024.0   \n",
+       "82308                   40                 100           -1024.0   \n",
+       "60800   ['00036', '00036']  ['00080', '00080']           -1024.0   \n",
+       "102453                  40                 150           -1024.0   \n",
+       "10097   ['00036', '00036']  ['00080', '00080']           -1024.0   \n",
+       "\n",
+       "        RescaleSlope    PxlMin    PxlMax    PxlStd   PxlMean   test  test2  \\\n",
+       "12436            1.0 -0.064000 -1.548000 -1.402099 -1.620352  False   True   \n",
+       "82308            1.0 -0.064000 -1.572000 -1.392679 -1.599246  False   True   \n",
+       "60800            1.0  1.314667 -1.914667 -2.872322 -0.693297  False   True   \n",
+       "102453           1.0 -0.064000 -1.558667 -1.401150 -1.616006  False   True   \n",
+       "10097            1.0  1.301333  0.108000 -2.544276 -0.594726  False   True   \n",
+       "\n",
+       "        ImageOrientationPatient_0  ImageOrientationPatient_1  \\\n",
+       "12436                         1.0                        0.0   \n",
+       "82308                         1.0                        0.0   \n",
+       "60800                         1.0                        0.0   \n",
+       "102453                        1.0                        0.0   \n",
+       "10097                         1.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_2  ImageOrientationPatient_3  \\\n",
+       "12436                         0.0                        0.0   \n",
+       "82308                         0.0                        0.0   \n",
+       "60800                         0.0                        0.0   \n",
+       "102453                        0.0                        0.0   \n",
+       "10097                         0.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_4  ImageOrientationPatient_5  \\\n",
+       "12436                         1.0                        0.0   \n",
+       "82308                         1.0                        0.0   \n",
+       "60800                         1.0                        0.0   \n",
+       "102453                        1.0                        0.0   \n",
+       "10097                         1.0                        0.0   \n",
+       "\n",
+       "        ImagePositionPatient_0  ImagePositionPatient_1  \\\n",
+       "12436                   -125.0                  -148.3   \n",
+       "82308                   -108.0                  -116.3   \n",
+       "60800                   -155.0                    23.0   \n",
+       "102453                  -125.0                  -131.7   \n",
+       "10097                   -125.0                    18.0   \n",
+       "\n",
+       "        ImagePositionPatient_2  PixelSpacing_0  PixelSpacing_1  \\\n",
+       "12436               135.250000        0.488281        0.488281   \n",
+       "82308               114.000000        0.421875        0.421875   \n",
+       "60800               138.699997        0.488281        0.488281   \n",
+       "102453              105.000000        0.488281        0.488281   \n",
+       "10097              -120.099976        0.488281        0.488281   \n",
+       "\n",
+       "        WindowCenter_0  WindowCenter_1  WindowCenter_1_NAN  WindowWidth_0  \\\n",
+       "12436             40.0             NaN                True          150.0   \n",
+       "82308             40.0             NaN                True          100.0   \n",
+       "60800             36.0            36.0               False           80.0   \n",
+       "102453            40.0             NaN                True          150.0   \n",
+       "10097             36.0            36.0               False           80.0   \n",
+       "\n",
+       "        WindowWidth_1  WindowWidth_0_le  WindowWidth_1_le  WindowCenter_1_le  \\\n",
+       "12436             NaN                 1                 1                  3   \n",
+       "82308             NaN                 2                 1                  3   \n",
+       "60800            80.0                 0                 0                  0   \n",
+       "102453            NaN                 1                 1                  3   \n",
+       "10097            80.0                 0                 0                  0   \n",
+       "\n",
+       "        BitType_le  ImageOrientationPatient_4_f  \\\n",
+       "12436            0                    -1.333333   \n",
+       "82308            0                    -1.333333   \n",
+       "60800            1                    -1.333333   \n",
+       "102453           0                    -1.333333   \n",
+       "10097            1                    -1.333333   \n",
+       "\n",
+       "        ImageOrientationPatient_4_enc_0  ...  ImageOrientationPatient_5_f  \\\n",
+       "12436                               1.0  ...                    -0.666667   \n",
+       "82308                               1.0  ...                    -0.666667   \n",
+       "60800                               1.0  ...                    -0.666667   \n",
+       "102453                              1.0  ...                    -0.666667   \n",
+       "10097                               1.0  ...                    -0.666667   \n",
+       "\n",
+       "        ImageOrientationPatient_5_enc_0  ImageOrientationPatient_5_enc_1  \\\n",
+       "12436                               1.0                            False   \n",
+       "82308                               1.0                            False   \n",
+       "60800                               1.0                            False   \n",
+       "102453                              1.0                            False   \n",
+       "10097                               1.0                            False   \n",
+       "\n",
+       "        ImagePositionPatient_0_f  ImagePositionPatient_0_enc_0  \\\n",
+       "12436                  -0.720000                           1.0   \n",
+       "82308                   1.733333                           0.0   \n",
+       "60800                   0.480000                           0.0   \n",
+       "102453                 -0.720000                           1.0   \n",
+       "10097                  -0.720000                           1.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_enc_1  ImagePositionPatient_0_f_r1  \\\n",
+       "12436                            0.0                          1.0   \n",
+       "82308                            0.0                          1.0   \n",
+       "60800                            0.0                          1.0   \n",
+       "102453                           0.0                          1.0   \n",
+       "10097                            0.0                          1.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_f_r05  ImagePositionPatient_1_f  \\\n",
+       "12436                            1.0                 -1.110667   \n",
+       "82308                            1.0                 -0.684000   \n",
+       "60800                            1.0                  1.173333   \n",
+       "102453                           1.0                 -0.889333   \n",
+       "10097                            1.0                  1.106667   \n",
+       "\n",
+       "        ImagePositionPatient_1_enc_0  ImagePositionPatient_2_f  \\\n",
+       "12436                            0.0                 -0.045487   \n",
+       "82308                            0.0                 -0.075931   \n",
+       "60800                            1.0                 -0.040544   \n",
+       "102453                           0.0                 -0.088825   \n",
+       "10097                            1.0                 -0.411318   \n",
+       "\n",
+       "        ImagePositionPatient_2_f_r05  PixelSpacing_1_f  PixelSpacing_1_enc_0  \\\n",
+       "12436                            0.0            -0.480                   1.0   \n",
+       "82308                            1.0             1.295                   0.0   \n",
+       "60800                            0.0            -0.480                   1.0   \n",
+       "102453                           1.0            -0.480                   1.0   \n",
+       "10097                            0.0            -0.480                   1.0   \n",
+       "\n",
+       "        PixelSpacing_1_enc_1  WindowCenter_0_le  pos_max  pos_min  pos_size  \\\n",
+       "12436                  False                  2   0.5810  -0.1190       0.5   \n",
+       "82308                  False                  2   0.4760  -0.1840      -0.1   \n",
+       "60800                  False                  1   0.5748  -0.1252       0.1   \n",
+       "102453                 False                  2   0.4400  -0.1800      -0.3   \n",
+       "10097                  False                  1  -0.4404  -1.4004       1.4   \n",
+       "\n",
+       "        pos_idx1  pos_idx  pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  \\\n",
+       "12436   1.355932       37 -1.016949      -1.5      -1.5                3   \n",
+       "82308   1.016949       32 -1.084746      -1.5      -1.5                3   \n",
+       "60800   1.152542       34 -1.084746      -1.5      -1.5                3   \n",
+       "102453  0.881356       30 -1.084746      -1.5      -1.5                3   \n",
+       "10097   1.966102       46 -1.016949      -1.5      -1.5                3   \n",
+       "\n",
+       "        pos_inc2_grp_le  pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  \\\n",
+       "12436                 3          1.0             1.0             0.0   \n",
+       "82308                 3          1.0             1.0             0.0   \n",
+       "60800                 3          1.0             1.0             0.0   \n",
+       "102453                3          1.0             1.0             0.0   \n",
+       "10097                 3          1.0             1.0             0.0   \n",
+       "\n",
+       "        pos_inc2_enc_0  pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  \\\n",
+       "12436              0.0             1.0             1.0            1   \n",
+       "82308              0.0             1.0             1.0            4   \n",
+       "60800              0.0             1.0             1.0            2   \n",
+       "102453             0.0             1.0             1.0            0   \n",
+       "10097              0.0             1.0             1.0           10   \n",
+       "\n",
+       "        pos_range   pos_rel  pos_zeros  pos_inc_rng  pos_zeros_le  \\\n",
+       "12436    0.266667  1.771429        1.6    -0.600000             1   \n",
+       "82308    0.000000  1.878788        0.0    -0.600000             0   \n",
+       "60800    0.266666  1.885714        0.0    -0.599994             0   \n",
+       "102453  -0.266667  1.870968        0.0    -0.600000             0   \n",
+       "10097    2.000000  1.833333        0.0    -0.600000             0   \n",
+       "\n",
+       "        PxlMin_grp_le  PxlMin_zero  any  epidural  intraparenchymal  \\\n",
+       "12436               1        False  NaN       NaN               NaN   \n",
+       "82308               1        False  NaN       NaN               NaN   \n",
+       "60800               2        False  NaN       NaN               NaN   \n",
+       "102453              1        False  NaN       NaN               NaN   \n",
+       "10097               2        False  NaN       NaN               NaN   \n",
+       "\n",
+       "        intraventricular  subarachnoid  subdural  any_series  SeriesPP  \\\n",
+       "12436                NaN           NaN       NaN       False      -0.5   \n",
+       "82308                NaN           NaN       NaN       False      -0.5   \n",
+       "60800                NaN           NaN       NaN       False      -0.5   \n",
+       "102453               NaN           NaN       NaN       False      -0.5   \n",
+       "10097                NaN           NaN       NaN       False      -0.5   \n",
+       "\n",
+       "        yuval_idx  pred_any  \n",
+       "12436       80726  0.000082  \n",
+       "82308       68171  0.000082  \n",
+       "60800       27981  0.000083  \n",
+       "102453      90163  0.000085  \n",
+       "10097       14678  0.000086  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md.sort_values('pred_any').head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>100029</td>\n",
+       "      <td>d3bd67ff1</td>\n",
+       "      <td>ID_d3bd67ff1</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_07aa4e90</td>\n",
+       "      <td>ID_19039aeb7f</td>\n",
+       "      <td>ID_83a456ed02</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '-5.28788193', '235.817384']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.927183855', '-0.374606...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>-0.618874</td>\n",
+       "      <td>1.229975</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.927184</td>\n",
+       "      <td>-0.374607</td>\n",
+       "      <td>-125.000000</td>\n",
+       "      <td>-5.287882</td>\n",
+       "      <td>235.817384</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.695785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.835956</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.796162</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.098592</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.202425</td>\n",
+       "      <td>0.502892</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>17</td>\n",
+       "      <td>-0.474576</td>\n",
+       "      <td>2.247192</td>\n",
+       "      <td>2.247192</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.263550</td>\n",
+       "      <td>0.518123</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.575802</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>52190</td>\n",
+       "      <td>0.998915</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>101618</td>\n",
+       "      <td>b5c2fbbe1</td>\n",
+       "      <td>ID_b5c2fbbe1</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_877a2214</td>\n",
+       "      <td>ID_f5d8b2ad40</td>\n",
+       "      <td>ID_c37347c9a3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '92.449158']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.148000</td>\n",
+       "      <td>-0.975081</td>\n",
+       "      <td>1.044669</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>92.449158</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.106806</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.609797</td>\n",
+       "      <td>-0.010203</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>0.135593</td>\n",
+       "      <td>19</td>\n",
+       "      <td>-0.338983</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.266667</td>\n",
+       "      <td>0.451613</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.600000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>93649</td>\n",
+       "      <td>0.998922</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>54912</td>\n",
+       "      <td>5519471d4</td>\n",
+       "      <td>ID_5519471d4</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_35384be6</td>\n",
+       "      <td>ID_cc5b6c0a29</td>\n",
+       "      <td>ID_5d7a4ca229</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '72.8792912', '193.380843']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.920504853', '-0.390731...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>1.525333</td>\n",
+       "      <td>-0.941557</td>\n",
+       "      <td>1.166305</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.920505</td>\n",
+       "      <td>-0.390731</td>\n",
+       "      <td>-125.000000</td>\n",
+       "      <td>72.879291</td>\n",
+       "      <td>193.380843</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.606731</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.728459</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.838391</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.037795</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.480000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.078723</td>\n",
+       "      <td>0.490115</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>-0.271186</td>\n",
+       "      <td>13</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>1.726074</td>\n",
+       "      <td>1.723938</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.475944</td>\n",
+       "      <td>-0.074042</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.598386</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>115357</td>\n",
+       "      <td>0.998966</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>29363</td>\n",
+       "      <td>dfc1d30ba</td>\n",
+       "      <td>ID_dfc1d30ba</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_7ed798ca</td>\n",
+       "      <td>ID_bca01d4025</td>\n",
+       "      <td>ID_bf75646cb6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-132.5', '13.0711274', '189.612208']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.965925826', '-0.258819...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.517578125', '0.517578125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>-0.217333</td>\n",
+       "      <td>-0.920688</td>\n",
+       "      <td>0.910508</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.965926</td>\n",
+       "      <td>-0.258819</td>\n",
+       "      <td>-132.500000</td>\n",
+       "      <td>13.071127</td>\n",
+       "      <td>189.612208</td>\n",
+       "      <td>0.517578</td>\n",
+       "      <td>0.517578</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.212344</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.607873</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.08</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.040948</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.032396</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.060625</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.026354</td>\n",
+       "      <td>0.428849</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>16</td>\n",
+       "      <td>-0.271186</td>\n",
+       "      <td>1.561829</td>\n",
+       "      <td>1.588135</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>-0.416634</td>\n",
+       "      <td>0.206507</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.579463</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>111444</td>\n",
+       "      <td>0.999020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>92120</td>\n",
+       "      <td>e33160522</td>\n",
+       "      <td>ID_e33160522</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_7ed798ca</td>\n",
+       "      <td>ID_bca01d4025</td>\n",
+       "      <td>ID_bf75646cb6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-132.5', '13.0711274', '184.488551']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.965925826', '-0.258819...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.517578125', '0.517578125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>-0.197333</td>\n",
+       "      <td>-0.930595</td>\n",
+       "      <td>0.931032</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.965926</td>\n",
+       "      <td>-0.258819</td>\n",
+       "      <td>-132.500000</td>\n",
+       "      <td>13.071127</td>\n",
+       "      <td>184.488551</td>\n",
+       "      <td>0.517578</td>\n",
+       "      <td>0.517578</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.212344</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.607873</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.08</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.040948</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.025055</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.060625</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.026354</td>\n",
+       "      <td>0.428849</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>15</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>1.588134</td>\n",
+       "      <td>1.561829</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>-0.416634</td>\n",
+       "      <td>0.069305</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.579463</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>111443</td>\n",
+       "      <td>0.999043</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "100029  d3bd67ff1   ID_d3bd67ff1       CT  ID_07aa4e90    ID_19039aeb7f   \n",
+       "101618  b5c2fbbe1   ID_b5c2fbbe1       CT  ID_877a2214    ID_f5d8b2ad40   \n",
+       "54912   5519471d4   ID_5519471d4       CT  ID_35384be6    ID_cc5b6c0a29   \n",
+       "29363   dfc1d30ba   ID_dfc1d30ba       CT  ID_7ed798ca    ID_bca01d4025   \n",
+       "92120   e33160522   ID_e33160522       CT  ID_7ed798ca    ID_bca01d4025   \n",
+       "\n",
+       "       SeriesInstanceUID  StudyID  \\\n",
+       "100029     ID_83a456ed02      NaN   \n",
+       "101618     ID_c37347c9a3      NaN   \n",
+       "54912      ID_5d7a4ca229      NaN   \n",
+       "29363      ID_bf75646cb6      NaN   \n",
+       "92120      ID_bf75646cb6      NaN   \n",
+       "\n",
+       "                               ImagePositionPatient  \\\n",
+       "100029        ['-125', '-5.28788193', '235.817384']   \n",
+       "101618  ['-126.408875', '-126.408875', '92.449158']   \n",
+       "54912          ['-125', '72.8792912', '193.380843']   \n",
+       "29363        ['-132.5', '13.0711274', '189.612208']   \n",
+       "92120        ['-132.5', '13.0711274', '184.488551']   \n",
+       "\n",
+       "                                  ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "100029  ['1', '0', '0', '0', '0.927183855', '-0.374606...                1   \n",
+       "101618  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "54912   ['1', '0', '0', '0', '0.920504853', '-0.390731...                1   \n",
+       "29363   ['1', '0', '0', '0', '0.965925826', '-0.258819...                1   \n",
+       "92120   ['1', '0', '0', '0', '0.965925826', '-0.258819...                1   \n",
+       "\n",
+       "       PhotometricInterpretation  Rows  Columns  \\\n",
+       "100029               MONOCHROME2   512      512   \n",
+       "101618               MONOCHROME2   512      512   \n",
+       "54912                MONOCHROME2   512      512   \n",
+       "29363                MONOCHROME2   512      512   \n",
+       "92120                MONOCHROME2   512      512   \n",
+       "\n",
+       "                                PixelSpacing  BitsAllocated  BitsStored  \\\n",
+       "100029          ['0.48828125', '0.48828125']             16          12   \n",
+       "101618  ['0.494750976563', '0.494750976563']             16          16   \n",
+       "54912           ['0.48828125', '0.48828125']             16          12   \n",
+       "29363         ['0.517578125', '0.517578125']             16          12   \n",
+       "92120         ['0.517578125', '0.517578125']             16          12   \n",
+       "\n",
+       "        HighBit  PixelRepresentation        WindowCenter         WindowWidth  \\\n",
+       "100029       11                    0  ['00040', '00040']  ['00080', '00080']   \n",
+       "101618       15                    1           35.000000          135.000000   \n",
+       "54912        11                    0  ['00040', '00040']  ['00080', '00080']   \n",
+       "29363        11                    1  ['00040', '00040']  ['00080', '00080']   \n",
+       "92120        11                    1  ['00040', '00040']  ['00080', '00080']   \n",
+       "\n",
+       "        RescaleIntercept  RescaleSlope    PxlMin    PxlMax    PxlStd  \\\n",
+       "100029           -1024.0           1.0  1.301333  0.093333 -0.618874   \n",
+       "101618           -1024.0           1.0  1.301333  0.148000 -0.975081   \n",
+       "54912            -1024.0           1.0  1.301333  1.525333 -0.941557   \n",
+       "29363                0.0           1.0  1.333333 -0.217333 -0.920688   \n",
+       "92120                0.0           1.0  1.333333 -0.197333 -0.930595   \n",
+       "\n",
+       "         PxlMean   test  test2  ImageOrientationPatient_0  \\\n",
+       "100029  1.229975  False   True                        1.0   \n",
+       "101618  1.044669  False   True                        1.0   \n",
+       "54912   1.166305  False   True                        1.0   \n",
+       "29363   0.910508  False   True                        1.0   \n",
+       "92120   0.931032  False   True                        1.0   \n",
+       "\n",
+       "        ImageOrientationPatient_1  ImageOrientationPatient_2  \\\n",
+       "100029                        0.0                        0.0   \n",
+       "101618                        0.0                        0.0   \n",
+       "54912                         0.0                        0.0   \n",
+       "29363                         0.0                        0.0   \n",
+       "92120                         0.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_3  ImageOrientationPatient_4  \\\n",
+       "100029                        0.0                   0.927184   \n",
+       "101618                        0.0                   1.000000   \n",
+       "54912                         0.0                   0.920505   \n",
+       "29363                         0.0                   0.965926   \n",
+       "92120                         0.0                   0.965926   \n",
+       "\n",
+       "        ImageOrientationPatient_5  ImagePositionPatient_0  \\\n",
+       "100029                  -0.374607             -125.000000   \n",
+       "101618                   0.000000             -126.408875   \n",
+       "54912                   -0.390731             -125.000000   \n",
+       "29363                   -0.258819             -132.500000   \n",
+       "92120                   -0.258819             -132.500000   \n",
+       "\n",
+       "        ImagePositionPatient_1  ImagePositionPatient_2  PixelSpacing_0  \\\n",
+       "100029               -5.287882              235.817384        0.488281   \n",
+       "101618             -126.408875               92.449158        0.494751   \n",
+       "54912                72.879291              193.380843        0.488281   \n",
+       "29363                13.071127              189.612208        0.517578   \n",
+       "92120                13.071127              184.488551        0.517578   \n",
+       "\n",
+       "        PixelSpacing_1  WindowCenter_0  WindowCenter_1  WindowCenter_1_NAN  \\\n",
+       "100029        0.488281            40.0            40.0               False   \n",
+       "101618        0.494751            35.0             NaN                True   \n",
+       "54912         0.488281            40.0            40.0               False   \n",
+       "29363         0.517578            40.0            40.0               False   \n",
+       "92120         0.517578            40.0            40.0               False   \n",
+       "\n",
+       "        WindowWidth_0  WindowWidth_1  WindowWidth_0_le  WindowWidth_1_le  \\\n",
+       "100029           80.0           80.0                 0                 0   \n",
+       "101618          135.0            NaN                 3                 1   \n",
+       "54912            80.0           80.0                 0                 0   \n",
+       "29363            80.0           80.0                 0                 0   \n",
+       "92120            80.0           80.0                 0                 0   \n",
+       "\n",
+       "        WindowCenter_1_le  BitType_le  ImageOrientationPatient_4_f  \\\n",
+       "100029                  1           1                     1.695785   \n",
+       "101618                  3           0                    -1.333333   \n",
+       "54912                   1           1                     1.606731   \n",
+       "29363                   1           2                     2.212344   \n",
+       "92120                   1           2                     2.212344   \n",
+       "\n",
+       "        ImageOrientationPatient_4_enc_0  ...  ImageOrientationPatient_5_f  \\\n",
+       "100029                              0.0  ...                     0.835956   \n",
+       "101618                              1.0  ...                    -0.666667   \n",
+       "54912                               0.0  ...                     0.728459   \n",
+       "29363                               0.0  ...                     1.607873   \n",
+       "92120                               0.0  ...                     1.607873   \n",
+       "\n",
+       "        ImageOrientationPatient_5_enc_0  ImageOrientationPatient_5_enc_1  \\\n",
+       "100029                              0.0                            False   \n",
+       "101618                              1.0                            False   \n",
+       "54912                               0.0                            False   \n",
+       "29363                               0.0                            False   \n",
+       "92120                               0.0                            False   \n",
+       "\n",
+       "        ImagePositionPatient_0_f  ImagePositionPatient_0_enc_0  \\\n",
+       "100029                     -0.72                           1.0   \n",
+       "101618                     -0.72                           0.0   \n",
+       "54912                      -0.72                           1.0   \n",
+       "29363                       1.08                           0.0   \n",
+       "92120                       1.08                           0.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_enc_1  ImagePositionPatient_0_f_r1  \\\n",
+       "100029                           0.0                          1.0   \n",
+       "101618                           1.0                          1.0   \n",
+       "54912                            0.0                          1.0   \n",
+       "29363                            0.0                          0.0   \n",
+       "92120                            0.0                          0.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_f_r05  ImagePositionPatient_1_f  \\\n",
+       "100029                           1.0                  0.796162   \n",
+       "101618                           1.0                 -0.818785   \n",
+       "54912                            1.0                  1.838391   \n",
+       "29363                            1.0                  1.040948   \n",
+       "92120                            1.0                  1.040948   \n",
+       "\n",
+       "        ImagePositionPatient_1_enc_0  ImagePositionPatient_2_f  \\\n",
+       "100029                           1.0                  0.098592   \n",
+       "101618                           0.0                 -0.106806   \n",
+       "54912                            1.0                  0.037795   \n",
+       "29363                            1.0                  0.032396   \n",
+       "92120                            1.0                  0.025055   \n",
+       "\n",
+       "        ImagePositionPatient_2_f_r05  PixelSpacing_1_f  PixelSpacing_1_enc_0  \\\n",
+       "100029                           0.0         -0.480000                   1.0   \n",
+       "101618                           0.0         -0.480000                   0.0   \n",
+       "54912                            0.0         -0.480000                   1.0   \n",
+       "29363                            0.0          2.060625                   0.0   \n",
+       "92120                            0.0          2.060625                   0.0   \n",
+       "\n",
+       "        PixelSpacing_1_enc_1  WindowCenter_0_le   pos_max   pos_min  pos_size  \\\n",
+       "100029                 False                  2  1.202425  0.502892      -0.7   \n",
+       "101618                  True                  3  0.609797 -0.010203      -0.3   \n",
+       "54912                  False                  2  1.078723  0.490115      -0.7   \n",
+       "29363                  False                  2  1.026354  0.428849      -0.5   \n",
+       "92120                  False                  2  1.026354  0.428849      -0.5   \n",
+       "\n",
+       "        pos_idx1  pos_idx  pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  \\\n",
+       "100029  0.000000       17 -0.474576  2.247192  2.247192                3   \n",
+       "101618  0.135593       19 -0.338983 -1.500000 -1.500000                3   \n",
+       "54912  -0.271186       13 -0.203390  1.726074  1.723938                3   \n",
+       "29363  -0.067797       16 -0.271186  1.561829  1.588135                3   \n",
+       "92120  -0.135593       15 -0.203390  1.588134  1.561829                3   \n",
+       "\n",
+       "        pos_inc2_grp_le  pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  \\\n",
+       "100029                3          0.0             0.0             0.0   \n",
+       "101618                3          1.0             1.0             0.0   \n",
+       "54912                 3          0.0             0.0             0.0   \n",
+       "29363                 3          0.0             0.0             0.0   \n",
+       "92120                 3          0.0             0.0             0.0   \n",
+       "\n",
+       "        pos_inc2_enc_0  pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  \\\n",
+       "100029             0.0             0.0             0.0            3   \n",
+       "101618             0.0             1.0             1.0            0   \n",
+       "54912              0.0             0.0             0.0            3   \n",
+       "29363              0.0             0.0             0.0            5   \n",
+       "92120              0.0             0.0             0.0            5   \n",
+       "\n",
+       "        pos_range   pos_rel  pos_zeros  pos_inc_rng  pos_zeros_le  \\\n",
+       "100029   0.263550  0.518123        0.0    -0.575802             0   \n",
+       "101618  -0.266667  0.451613        0.0    -0.600000             0   \n",
+       "54912   -0.475944 -0.074042        0.0    -0.598386             0   \n",
+       "29363   -0.416634  0.206507        0.0    -0.579463             0   \n",
+       "92120   -0.416634  0.069305        0.0    -0.579463             0   \n",
+       "\n",
+       "        PxlMin_grp_le  PxlMin_zero  any  epidural  intraparenchymal  \\\n",
+       "100029              2        False  NaN       NaN               NaN   \n",
+       "101618              2        False  NaN       NaN               NaN   \n",
+       "54912               2        False  NaN       NaN               NaN   \n",
+       "29363               2        False  NaN       NaN               NaN   \n",
+       "92120               2        False  NaN       NaN               NaN   \n",
+       "\n",
+       "        intraventricular  subarachnoid  subdural  any_series  SeriesPP  \\\n",
+       "100029               NaN           NaN       NaN       False      -0.5   \n",
+       "101618               NaN           NaN       NaN       False      -0.5   \n",
+       "54912                NaN           NaN       NaN       False      -0.5   \n",
+       "29363                NaN           NaN       NaN       False      -0.5   \n",
+       "92120                NaN           NaN       NaN       False      -0.5   \n",
+       "\n",
+       "        yuval_idx  pred_any  \n",
+       "100029      52190  0.998915  \n",
+       "101618      93649  0.998922  \n",
+       "54912      115357  0.998966  \n",
+       "29363      111444  0.999020  \n",
+       "92120      111443  0.999043  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>85421</td>\n",
+       "      <td>ba1a7894c</td>\n",
+       "      <td>ID_ba1a7894c</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_6f87831a</td>\n",
+       "      <td>ID_a6ca244172</td>\n",
+       "      <td>ID_d00cee7f0c</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000000', '-119.997978', '127.192337']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>30</td>\n",
+       "      <td>80</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-1.365333</td>\n",
+       "      <td>0.310667</td>\n",
+       "      <td>1.642553</td>\n",
+       "      <td>-0.881730</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.927184</td>\n",
+       "      <td>-0.374607</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-119.997978</td>\n",
+       "      <td>127.192337</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.733306</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.057031</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.918601</td>\n",
+       "      <td>0.249929</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.338983</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.135593</td>\n",
+       "      <td>1.695991</td>\n",
+       "      <td>1.696335</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.057814</td>\n",
+       "      <td>-0.451618</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599737</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>111470</td>\n",
+       "      <td>0.902253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>46168</td>\n",
+       "      <td>7f9480ae5</td>\n",
+       "      <td>ID_7f9480ae5</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_61101bd3</td>\n",
+       "      <td>ID_6aca8f9834</td>\n",
+       "      <td>ID_1cb45bbcea</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '42.4079503', '222.344198']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.939692621', '-0.342020...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.006667</td>\n",
+       "      <td>-0.700807</td>\n",
+       "      <td>1.484853</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.939693</td>\n",
+       "      <td>-0.342020</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>42.407950</td>\n",
+       "      <td>222.344198</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.862568</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.053199</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.432106</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.079290</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.249860</td>\n",
+       "      <td>0.592577</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.639649</td>\n",
+       "      <td>1.660400</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.018112</td>\n",
+       "      <td>-0.193775</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.584230</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>35441</td>\n",
+       "      <td>0.911084</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>90394</td>\n",
+       "      <td>5d403bd8a</td>\n",
+       "      <td>ID_5d403bd8a</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_61101bd3</td>\n",
+       "      <td>ID_6aca8f9834</td>\n",
+       "      <td>ID_1cb45bbcea</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '42.4079503', '206.464926']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.939692621', '-0.342020...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.010667</td>\n",
+       "      <td>-0.780873</td>\n",
+       "      <td>1.496547</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.939693</td>\n",
+       "      <td>-0.342020</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>42.407950</td>\n",
+       "      <td>206.464926</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.862568</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.053199</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.432106</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.056540</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.249860</td>\n",
+       "      <td>0.592577</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.406780</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>1.660400</td>\n",
+       "      <td>1.639587</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.018112</td>\n",
+       "      <td>-0.580318</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.584230</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>35438</td>\n",
+       "      <td>0.911625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23519</td>\n",
+       "      <td>645917b86</td>\n",
+       "      <td>ID_645917b86</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_61101bd3</td>\n",
+       "      <td>ID_6aca8f9834</td>\n",
+       "      <td>ID_1cb45bbcea</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '42.4079503', '211.7441']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.939692621', '-0.342020...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.037333</td>\n",
+       "      <td>-0.754200</td>\n",
+       "      <td>1.500107</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.939693</td>\n",
+       "      <td>-0.342020</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>42.407950</td>\n",
+       "      <td>211.744100</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.862568</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.053199</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.432106</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.064103</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.249860</td>\n",
+       "      <td>0.592577</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.338983</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.135593</td>\n",
+       "      <td>1.639587</td>\n",
+       "      <td>1.660400</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.018112</td>\n",
+       "      <td>-0.451810</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.584230</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>35439</td>\n",
+       "      <td>0.916977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>41043</td>\n",
+       "      <td>0f43a379c</td>\n",
+       "      <td>ID_0f43a379c</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_61101bd3</td>\n",
+       "      <td>ID_6aca8f9834</td>\n",
+       "      <td>ID_1cb45bbcea</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '42.4079503', '217.064901']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.939692621', '-0.342020...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-0.718398</td>\n",
+       "      <td>1.505203</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.939693</td>\n",
+       "      <td>-0.342020</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>42.407950</td>\n",
+       "      <td>217.064901</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.862568</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.053199</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.432106</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.071726</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.249860</td>\n",
+       "      <td>0.592577</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.271186</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0.067797</td>\n",
+       "      <td>1.660400</td>\n",
+       "      <td>1.639649</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.018112</td>\n",
+       "      <td>-0.322287</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.584230</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>35440</td>\n",
+       "      <td>0.917555</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "85421  ba1a7894c   ID_ba1a7894c       CT  ID_6f87831a    ID_a6ca244172   \n",
+       "46168  7f9480ae5   ID_7f9480ae5       CT  ID_61101bd3    ID_6aca8f9834   \n",
+       "90394  5d403bd8a   ID_5d403bd8a       CT  ID_61101bd3    ID_6aca8f9834   \n",
+       "23519  645917b86   ID_645917b86       CT  ID_61101bd3    ID_6aca8f9834   \n",
+       "41043  0f43a379c   ID_0f43a379c       CT  ID_61101bd3    ID_6aca8f9834   \n",
+       "\n",
+       "      SeriesInstanceUID  StudyID  \\\n",
+       "85421     ID_d00cee7f0c      NaN   \n",
+       "46168     ID_1cb45bbcea      NaN   \n",
+       "90394     ID_1cb45bbcea      NaN   \n",
+       "23519     ID_1cb45bbcea      NaN   \n",
+       "41043     ID_1cb45bbcea      NaN   \n",
+       "\n",
+       "                               ImagePositionPatient  \\\n",
+       "85421  ['-125.000000', '-119.997978', '127.192337']   \n",
+       "46168          ['-125', '42.4079503', '222.344198']   \n",
+       "90394          ['-125', '42.4079503', '206.464926']   \n",
+       "23519            ['-125', '42.4079503', '211.7441']   \n",
+       "41043          ['-125', '42.4079503', '217.064901']   \n",
+       "\n",
+       "                                 ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "85421  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "46168  ['1', '0', '0', '0', '0.939692621', '-0.342020...                1   \n",
+       "90394  ['1', '0', '0', '0', '0.939692621', '-0.342020...                1   \n",
+       "23519  ['1', '0', '0', '0', '0.939692621', '-0.342020...                1   \n",
+       "41043  ['1', '0', '0', '0', '0.939692621', '-0.342020...                1   \n",
+       "\n",
+       "      PhotometricInterpretation  Rows  Columns                  PixelSpacing  \\\n",
+       "85421               MONOCHROME2   512      512      ['0.488281', '0.488281']   \n",
+       "46168               MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "90394               MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "23519               MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "41043               MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "\n",
+       "       BitsAllocated  BitsStored  HighBit  PixelRepresentation  \\\n",
+       "85421             16          16       15                    1   \n",
+       "46168             16          12       11                    0   \n",
+       "90394             16          12       11                    0   \n",
+       "23519             16          12       11                    0   \n",
+       "41043             16          12       11                    0   \n",
+       "\n",
+       "             WindowCenter         WindowWidth  RescaleIntercept  RescaleSlope  \\\n",
+       "85421                  30                  80           -1024.0           1.0   \n",
+       "46168  ['00040', '00040']  ['00080', '00080']           -1024.0           1.0   \n",
+       "90394  ['00040', '00040']  ['00080', '00080']           -1024.0           1.0   \n",
+       "23519  ['00040', '00040']  ['00080', '00080']           -1024.0           1.0   \n",
+       "41043  ['00040', '00040']  ['00080', '00080']           -1024.0           1.0   \n",
+       "\n",
+       "         PxlMin    PxlMax    PxlStd   PxlMean   test  test2  \\\n",
+       "85421 -1.365333  0.310667  1.642553 -0.881730  False   True   \n",
+       "46168  1.301333  0.006667 -0.700807  1.484853  False   True   \n",
+       "90394  1.301333  0.010667 -0.780873  1.496547  False   True   \n",
+       "23519  1.301333  0.037333 -0.754200  1.500107  False   True   \n",
+       "41043  1.301333  0.000000 -0.718398  1.505203  False   True   \n",
+       "\n",
+       "       ImageOrientationPatient_0  ImageOrientationPatient_1  \\\n",
+       "85421                        1.0                        0.0   \n",
+       "46168                        1.0                        0.0   \n",
+       "90394                        1.0                        0.0   \n",
+       "23519                        1.0                        0.0   \n",
+       "41043                        1.0                        0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_2  ImageOrientationPatient_3  \\\n",
+       "85421                        0.0                        0.0   \n",
+       "46168                        0.0                        0.0   \n",
+       "90394                        0.0                        0.0   \n",
+       "23519                        0.0                        0.0   \n",
+       "41043                        0.0                        0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_4  ImageOrientationPatient_5  \\\n",
+       "85421                   0.927184                  -0.374607   \n",
+       "46168                   0.939693                  -0.342020   \n",
+       "90394                   0.939693                  -0.342020   \n",
+       "23519                   0.939693                  -0.342020   \n",
+       "41043                   0.939693                  -0.342020   \n",
+       "\n",
+       "       ImagePositionPatient_0  ImagePositionPatient_1  ImagePositionPatient_2  \\\n",
+       "85421                  -125.0             -119.997978              127.192337   \n",
+       "46168                  -125.0               42.407950              222.344198   \n",
+       "90394                  -125.0               42.407950              206.464926   \n",
+       "23519                  -125.0               42.407950              211.744100   \n",
+       "41043                  -125.0               42.407950              217.064901   \n",
+       "\n",
+       "       PixelSpacing_0  PixelSpacing_1  WindowCenter_0  WindowCenter_1  \\\n",
+       "85421        0.488281        0.488281            30.0             NaN   \n",
+       "46168        0.488281        0.488281            40.0            40.0   \n",
+       "90394        0.488281        0.488281            40.0            40.0   \n",
+       "23519        0.488281        0.488281            40.0            40.0   \n",
+       "41043        0.488281        0.488281            40.0            40.0   \n",
+       "\n",
+       "       WindowCenter_1_NAN  WindowWidth_0  WindowWidth_1  WindowWidth_0_le  \\\n",
+       "85421                True           80.0            NaN                 0   \n",
+       "46168               False           80.0           80.0                 0   \n",
+       "90394               False           80.0           80.0                 0   \n",
+       "23519               False           80.0           80.0                 0   \n",
+       "41043               False           80.0           80.0                 0   \n",
+       "\n",
+       "       WindowWidth_1_le  WindowCenter_1_le  BitType_le  \\\n",
+       "85421                 1                  3           0   \n",
+       "46168                 0                  1           1   \n",
+       "90394                 0                  1           1   \n",
+       "23519                 0                  1           1   \n",
+       "41043                 0                  1           1   \n",
+       "\n",
+       "       ImageOrientationPatient_4_f  ImageOrientationPatient_4_enc_0  ...  \\\n",
+       "85421                    -1.333333                              0.0  ...   \n",
+       "46168                     1.862568                              0.0  ...   \n",
+       "90394                     1.862568                              0.0  ...   \n",
+       "23519                     1.862568                              0.0  ...   \n",
+       "41043                     1.862568                              0.0  ...   \n",
+       "\n",
+       "       ImageOrientationPatient_5_f  ImageOrientationPatient_5_enc_0  \\\n",
+       "85421                    -0.666667                              0.0   \n",
+       "46168                     1.053199                              0.0   \n",
+       "90394                     1.053199                              0.0   \n",
+       "23519                     1.053199                              0.0   \n",
+       "41043                     1.053199                              0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_5_enc_1  ImagePositionPatient_0_f  \\\n",
+       "85421                             True                     -0.72   \n",
+       "46168                            False                     -0.72   \n",
+       "90394                            False                     -0.72   \n",
+       "23519                            False                     -0.72   \n",
+       "41043                            False                     -0.72   \n",
+       "\n",
+       "       ImagePositionPatient_0_enc_0  ImagePositionPatient_0_enc_1  \\\n",
+       "85421                           1.0                           0.0   \n",
+       "46168                           1.0                           0.0   \n",
+       "90394                           1.0                           0.0   \n",
+       "23519                           1.0                           0.0   \n",
+       "41043                           1.0                           0.0   \n",
+       "\n",
+       "       ImagePositionPatient_0_f_r1  ImagePositionPatient_0_f_r05  \\\n",
+       "85421                          1.0                           1.0   \n",
+       "46168                          1.0                           1.0   \n",
+       "90394                          1.0                           1.0   \n",
+       "23519                          1.0                           1.0   \n",
+       "41043                          1.0                           1.0   \n",
+       "\n",
+       "       ImagePositionPatient_1_f  ImagePositionPatient_1_enc_0  \\\n",
+       "85421                 -0.733306                           0.0   \n",
+       "46168                  1.432106                           1.0   \n",
+       "90394                  1.432106                           1.0   \n",
+       "23519                  1.432106                           1.0   \n",
+       "41043                  1.432106                           1.0   \n",
+       "\n",
+       "       ImagePositionPatient_2_f  ImagePositionPatient_2_f_r05  \\\n",
+       "85421                 -0.057031                           0.0   \n",
+       "46168                  0.079290                           0.0   \n",
+       "90394                  0.056540                           0.0   \n",
+       "23519                  0.064103                           0.0   \n",
+       "41043                  0.071726                           0.0   \n",
+       "\n",
+       "       PixelSpacing_1_f  PixelSpacing_1_enc_0  PixelSpacing_1_enc_1  \\\n",
+       "85421             -0.48                   1.0                 False   \n",
+       "46168             -0.48                   1.0                 False   \n",
+       "90394             -0.48                   1.0                 False   \n",
+       "23519             -0.48                   1.0                 False   \n",
+       "41043             -0.48                   1.0                 False   \n",
+       "\n",
+       "       WindowCenter_0_le   pos_max   pos_min  pos_size  pos_idx1  pos_idx  \\\n",
+       "85421                  0  0.918601  0.249929      -0.3 -0.338983       12   \n",
+       "46168                  2  1.249860  0.592577      -0.3 -0.203390       14   \n",
+       "90394                  2  1.249860  0.592577      -0.3 -0.406780       11   \n",
+       "23519                  2  1.249860  0.592577      -0.3 -0.338983       12   \n",
+       "41043                  2  1.249860  0.592577      -0.3 -0.271186       13   \n",
+       "\n",
+       "       pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  pos_inc2_grp_le  \\\n",
+       "85421  0.135593  1.695991  1.696335                3                3   \n",
+       "46168  0.000000  1.639649  1.660400                3                3   \n",
+       "90394  0.203390  1.660400  1.639587                3                3   \n",
+       "23519  0.135593  1.639587  1.660400                3                3   \n",
+       "41043  0.067797  1.660400  1.639649                3                3   \n",
+       "\n",
+       "       pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  pos_inc2_enc_0  \\\n",
+       "85421          0.0             0.0             0.0             0.0   \n",
+       "46168          0.0             0.0             0.0             0.0   \n",
+       "90394          0.0             0.0             0.0             0.0   \n",
+       "23519          0.0             0.0             0.0             0.0   \n",
+       "41043          0.0             0.0             0.0             0.0   \n",
+       "\n",
+       "       pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  pos_range   pos_rel  \\\n",
+       "85421             0.0             0.0            0   0.057814 -0.451618   \n",
+       "46168             0.0             0.0            0  -0.018112 -0.193775   \n",
+       "90394             0.0             0.0            0  -0.018112 -0.580318   \n",
+       "23519             0.0             0.0            0  -0.018112 -0.451810   \n",
+       "41043             0.0             0.0            0  -0.018112 -0.322287   \n",
+       "\n",
+       "       pos_zeros  pos_inc_rng  pos_zeros_le  PxlMin_grp_le  PxlMin_zero  any  \\\n",
+       "85421        0.0    -0.599737             0              0         True  NaN   \n",
+       "46168        0.0    -0.584230             0              2        False  NaN   \n",
+       "90394        0.0    -0.584230             0              2        False  NaN   \n",
+       "23519        0.0    -0.584230             0              2        False  NaN   \n",
+       "41043        0.0    -0.584230             0              2        False  NaN   \n",
+       "\n",
+       "       epidural  intraparenchymal  intraventricular  subarachnoid  subdural  \\\n",
+       "85421       NaN               NaN               NaN           NaN       NaN   \n",
+       "46168       NaN               NaN               NaN           NaN       NaN   \n",
+       "90394       NaN               NaN               NaN           NaN       NaN   \n",
+       "23519       NaN               NaN               NaN           NaN       NaN   \n",
+       "41043       NaN               NaN               NaN           NaN       NaN   \n",
+       "\n",
+       "       any_series  SeriesPP  yuval_idx  pred_any  \n",
+       "85421       False      -0.5     111470  0.902253  \n",
+       "46168       False      -0.5      35441  0.911084  \n",
+       "90394       False      -0.5      35438  0.911625  \n",
+       "23519       False      -0.5      35439  0.916977  \n",
+       "41043       False      -0.5      35440  0.917555  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md['pred_any'] = predictions[:,1]\n",
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>56318</td>\n",
+       "      <td>aaea1517d</td>\n",
+       "      <td>ID_aaea1517d</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_e875aaac</td>\n",
+       "      <td>ID_ace87fc419</td>\n",
+       "      <td>ID_c2050c1b62</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '157.507935']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.309333</td>\n",
+       "      <td>-0.835506</td>\n",
+       "      <td>1.294749</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>157.507935</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.013599</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.850032</td>\n",
+       "      <td>-0.009968</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.016949</td>\n",
+       "      <td>32</td>\n",
+       "      <td>-0.406780</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1.333334</td>\n",
+       "      <td>0.976744</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599997</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>20605</td>\n",
+       "      <td>0.995869</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11838</td>\n",
+       "      <td>8a3a7113f</td>\n",
+       "      <td>ID_8a3a7113f</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_1f7020f7</td>\n",
+       "      <td>ID_ffd91b71d1</td>\n",
+       "      <td>ID_a0997b616a</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-118', '20.437079', '167.587618']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.978147601', '-0.207911...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.126667</td>\n",
+       "      <td>-0.975261</td>\n",
+       "      <td>0.972069</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.978148</td>\n",
+       "      <td>-0.207912</td>\n",
+       "      <td>-118.000000</td>\n",
+       "      <td>20.437079</td>\n",
+       "      <td>167.587618</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.375301</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.947255</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.466667</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.139161</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000842</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.078350</td>\n",
+       "      <td>0.445865</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.406780</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>1.560669</td>\n",
+       "      <td>1.539367</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.183431</td>\n",
+       "      <td>-0.580297</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.583175</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>49264</td>\n",
+       "      <td>0.995902</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>60633</td>\n",
+       "      <td>fd5080c37</td>\n",
+       "      <td>ID_fd5080c37</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_16b922cc</td>\n",
+       "      <td>ID_b48b0482e3</td>\n",
+       "      <td>ID_653f493476</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '32.528565', '161.22819']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.939692621', '-0.342020...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>-0.090667</td>\n",
+       "      <td>-0.796026</td>\n",
+       "      <td>1.330736</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.939693</td>\n",
+       "      <td>-0.342020</td>\n",
+       "      <td>-125.000000</td>\n",
+       "      <td>32.528565</td>\n",
+       "      <td>161.228190</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.862568</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.053199</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.300381</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.008269</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.132596</td>\n",
+       "      <td>0.432912</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>-0.474576</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0.406780</td>\n",
+       "      <td>1.639588</td>\n",
+       "      <td>1.660400</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.264557</td>\n",
+       "      <td>-0.788021</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.584137</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>59637</td>\n",
+       "      <td>0.995940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>30971</td>\n",
+       "      <td>8dbff5245</td>\n",
+       "      <td>ID_8dbff5245</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f0ef989c</td>\n",
+       "      <td>ID_fcdfd2db4e</td>\n",
+       "      <td>ID_b9627ee31c</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '19.0514449', '123.026026']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.981627183', '-0.190808...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.164000</td>\n",
+       "      <td>-0.675198</td>\n",
+       "      <td>1.380203</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.981627</td>\n",
+       "      <td>-0.190809</td>\n",
+       "      <td>-125.000000</td>\n",
+       "      <td>19.051445</td>\n",
+       "      <td>123.026026</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.421696</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.061273</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.120686</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.063000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.940904</td>\n",
+       "      <td>0.267694</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>-0.406780</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.338983</td>\n",
+       "      <td>1.551270</td>\n",
+       "      <td>1.548767</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.088070</td>\n",
+       "      <td>-0.666627</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.597988</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>59366</td>\n",
+       "      <td>0.995958</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23816</td>\n",
+       "      <td>423cee314</td>\n",
+       "      <td>ID_423cee314</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_e875aaac</td>\n",
+       "      <td>ID_ace87fc419</td>\n",
+       "      <td>ID_c2050c1b62</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '167.507935']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.265333</td>\n",
+       "      <td>-0.826401</td>\n",
+       "      <td>1.185491</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>167.507935</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000728</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.850032</td>\n",
+       "      <td>-0.009968</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.152542</td>\n",
+       "      <td>34</td>\n",
+       "      <td>-0.542373</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>-1.500000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1.333334</td>\n",
+       "      <td>1.162791</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599997</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>20607</td>\n",
+       "      <td>0.996068</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "56318  aaea1517d   ID_aaea1517d       CT  ID_e875aaac    ID_ace87fc419   \n",
+       "11838  8a3a7113f   ID_8a3a7113f       CT  ID_1f7020f7    ID_ffd91b71d1   \n",
+       "60633  fd5080c37   ID_fd5080c37       CT  ID_16b922cc    ID_b48b0482e3   \n",
+       "30971  8dbff5245   ID_8dbff5245       CT  ID_f0ef989c    ID_fcdfd2db4e   \n",
+       "23816  423cee314   ID_423cee314       CT  ID_e875aaac    ID_ace87fc419   \n",
+       "\n",
+       "      SeriesInstanceUID  StudyID  \\\n",
+       "56318     ID_c2050c1b62      NaN   \n",
+       "11838     ID_a0997b616a      NaN   \n",
+       "60633     ID_653f493476      NaN   \n",
+       "30971     ID_b9627ee31c      NaN   \n",
+       "23816     ID_c2050c1b62      NaN   \n",
+       "\n",
+       "                               ImagePositionPatient  \\\n",
+       "56318  ['-126.408875', '-126.408875', '157.507935']   \n",
+       "11838           ['-118', '20.437079', '167.587618']   \n",
+       "60633            ['-125', '32.528565', '161.22819']   \n",
+       "30971          ['-125', '19.0514449', '123.026026']   \n",
+       "23816  ['-126.408875', '-126.408875', '167.507935']   \n",
+       "\n",
+       "                                 ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "56318  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "11838  ['1', '0', '0', '0', '0.978147601', '-0.207911...                1   \n",
+       "60633  ['1', '0', '0', '0', '0.939692621', '-0.342020...                1   \n",
+       "30971  ['1', '0', '0', '0', '0.981627183', '-0.190808...                1   \n",
+       "23816  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "\n",
+       "      PhotometricInterpretation  Rows  Columns  \\\n",
+       "56318               MONOCHROME2   512      512   \n",
+       "11838               MONOCHROME2   512      512   \n",
+       "60633               MONOCHROME2   512      512   \n",
+       "30971               MONOCHROME2   512      512   \n",
+       "23816               MONOCHROME2   512      512   \n",
+       "\n",
+       "                               PixelSpacing  BitsAllocated  BitsStored  \\\n",
+       "56318  ['0.494750976563', '0.494750976563']             16          16   \n",
+       "11838          ['0.48828125', '0.48828125']             16          12   \n",
+       "60633          ['0.48828125', '0.48828125']             16          12   \n",
+       "30971          ['0.48828125', '0.48828125']             16          12   \n",
+       "23816  ['0.494750976563', '0.494750976563']             16          16   \n",
+       "\n",
+       "       HighBit  PixelRepresentation        WindowCenter         WindowWidth  \\\n",
+       "56318       15                    1           35.000000          135.000000   \n",
+       "11838       11                    0  ['00040', '00040']  ['00080', '00080']   \n",
+       "60633       11                    0  ['00040', '00040']  ['00080', '00080']   \n",
+       "30971       11                    0  ['00040', '00040']  ['00080', '00080']   \n",
+       "23816       15                    1           35.000000          135.000000   \n",
+       "\n",
+       "       RescaleIntercept  RescaleSlope    PxlMin    PxlMax    PxlStd   PxlMean  \\\n",
+       "56318           -1024.0           1.0  1.301333  0.309333 -0.835506  1.294749   \n",
+       "11838           -1024.0           1.0  1.301333  0.126667 -0.975261  0.972069   \n",
+       "60633           -1024.0           1.0  1.301333 -0.090667 -0.796026  1.330736   \n",
+       "30971           -1024.0           1.0  1.301333  0.164000 -0.675198  1.380203   \n",
+       "23816           -1024.0           1.0  1.301333  0.265333 -0.826401  1.185491   \n",
+       "\n",
+       "        test  test2  ImageOrientationPatient_0  ImageOrientationPatient_1  \\\n",
+       "56318  False   True                        1.0                        0.0   \n",
+       "11838  False   True                        1.0                        0.0   \n",
+       "60633  False   True                        1.0                        0.0   \n",
+       "30971  False   True                        1.0                        0.0   \n",
+       "23816  False   True                        1.0                        0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_2  ImageOrientationPatient_3  \\\n",
+       "56318                        0.0                        0.0   \n",
+       "11838                        0.0                        0.0   \n",
+       "60633                        0.0                        0.0   \n",
+       "30971                        0.0                        0.0   \n",
+       "23816                        0.0                        0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_4  ImageOrientationPatient_5  \\\n",
+       "56318                   1.000000                   0.000000   \n",
+       "11838                   0.978148                  -0.207912   \n",
+       "60633                   0.939693                  -0.342020   \n",
+       "30971                   0.981627                  -0.190809   \n",
+       "23816                   1.000000                   0.000000   \n",
+       "\n",
+       "       ImagePositionPatient_0  ImagePositionPatient_1  ImagePositionPatient_2  \\\n",
+       "56318             -126.408875             -126.408875              157.507935   \n",
+       "11838             -118.000000               20.437079              167.587618   \n",
+       "60633             -125.000000               32.528565              161.228190   \n",
+       "30971             -125.000000               19.051445              123.026026   \n",
+       "23816             -126.408875             -126.408875              167.507935   \n",
+       "\n",
+       "       PixelSpacing_0  PixelSpacing_1  WindowCenter_0  WindowCenter_1  \\\n",
+       "56318        0.494751        0.494751            35.0             NaN   \n",
+       "11838        0.488281        0.488281            40.0            40.0   \n",
+       "60633        0.488281        0.488281            40.0            40.0   \n",
+       "30971        0.488281        0.488281            40.0            40.0   \n",
+       "23816        0.494751        0.494751            35.0             NaN   \n",
+       "\n",
+       "       WindowCenter_1_NAN  WindowWidth_0  WindowWidth_1  WindowWidth_0_le  \\\n",
+       "56318                True          135.0            NaN                 3   \n",
+       "11838               False           80.0           80.0                 0   \n",
+       "60633               False           80.0           80.0                 0   \n",
+       "30971               False           80.0           80.0                 0   \n",
+       "23816                True          135.0            NaN                 3   \n",
+       "\n",
+       "       WindowWidth_1_le  WindowCenter_1_le  BitType_le  \\\n",
+       "56318                 1                  3           0   \n",
+       "11838                 0                  1           1   \n",
+       "60633                 0                  1           1   \n",
+       "30971                 0                  1           1   \n",
+       "23816                 1                  3           0   \n",
+       "\n",
+       "       ImageOrientationPatient_4_f  ImageOrientationPatient_4_enc_0  ...  \\\n",
+       "56318                    -1.333333                              1.0  ...   \n",
+       "11838                     2.375301                              0.0  ...   \n",
+       "60633                     1.862568                              0.0  ...   \n",
+       "30971                     2.421696                              0.0  ...   \n",
+       "23816                    -1.333333                              1.0  ...   \n",
+       "\n",
+       "       ImageOrientationPatient_5_f  ImageOrientationPatient_5_enc_0  \\\n",
+       "56318                    -0.666667                              1.0   \n",
+       "11838                     1.947255                              0.0   \n",
+       "60633                     1.053199                              0.0   \n",
+       "30971                     2.061273                              0.0   \n",
+       "23816                    -0.666667                              1.0   \n",
+       "\n",
+       "       ImageOrientationPatient_5_enc_1  ImagePositionPatient_0_f  \\\n",
+       "56318                            False                 -0.720000   \n",
+       "11838                            False                  1.466667   \n",
+       "60633                            False                 -0.720000   \n",
+       "30971                            False                 -0.720000   \n",
+       "23816                            False                 -0.720000   \n",
+       "\n",
+       "       ImagePositionPatient_0_enc_0  ImagePositionPatient_0_enc_1  \\\n",
+       "56318                           0.0                           1.0   \n",
+       "11838                           0.0                           0.0   \n",
+       "60633                           1.0                           0.0   \n",
+       "30971                           1.0                           0.0   \n",
+       "23816                           0.0                           1.0   \n",
+       "\n",
+       "       ImagePositionPatient_0_f_r1  ImagePositionPatient_0_f_r05  \\\n",
+       "56318                          1.0                           1.0   \n",
+       "11838                          1.0                           1.0   \n",
+       "60633                          1.0                           1.0   \n",
+       "30971                          1.0                           1.0   \n",
+       "23816                          1.0                           1.0   \n",
+       "\n",
+       "       ImagePositionPatient_1_f  ImagePositionPatient_1_enc_0  \\\n",
+       "56318                 -0.818785                           0.0   \n",
+       "11838                  1.139161                           1.0   \n",
+       "60633                  1.300381                           1.0   \n",
+       "30971                  1.120686                           1.0   \n",
+       "23816                 -0.818785                           0.0   \n",
+       "\n",
+       "       ImagePositionPatient_2_f  ImagePositionPatient_2_f_r05  \\\n",
+       "56318                 -0.013599                           0.0   \n",
+       "11838                  0.000842                           0.0   \n",
+       "60633                 -0.008269                           0.0   \n",
+       "30971                 -0.063000                           0.0   \n",
+       "23816                  0.000728                           0.0   \n",
+       "\n",
+       "       PixelSpacing_1_f  PixelSpacing_1_enc_0  PixelSpacing_1_enc_1  \\\n",
+       "56318             -0.48                   0.0                  True   \n",
+       "11838             -0.48                   1.0                 False   \n",
+       "60633             -0.48                   1.0                 False   \n",
+       "30971             -0.48                   1.0                 False   \n",
+       "23816             -0.48                   0.0                  True   \n",
+       "\n",
+       "       WindowCenter_0_le   pos_max   pos_min  pos_size  pos_idx1  pos_idx  \\\n",
+       "56318                  3  0.850032 -0.009968       0.9  1.016949       32   \n",
+       "11838                  2  1.078350  0.445865      -0.3 -0.406780       11   \n",
+       "60633                  2  1.132596  0.432912      -0.1 -0.474576       10   \n",
+       "30971                  2  0.940904  0.267694      -0.1 -0.406780       11   \n",
+       "23816                  3  0.850032 -0.009968       0.9  1.152542       34   \n",
+       "\n",
+       "       pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  pos_inc2_grp_le  \\\n",
+       "56318 -0.406780 -1.500000 -1.500000                3                3   \n",
+       "11838  0.203390  1.560669  1.539367                3                3   \n",
+       "60633  0.406780  1.639588  1.660400                3                3   \n",
+       "30971  0.338983  1.551270  1.548767                3                3   \n",
+       "23816 -0.542373 -1.500000 -1.500000                3                3   \n",
+       "\n",
+       "       pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  pos_inc2_enc_0  \\\n",
+       "56318          1.0             1.0             0.0             0.0   \n",
+       "11838          0.0             0.0             0.0             0.0   \n",
+       "60633          0.0             0.0             0.0             0.0   \n",
+       "30971          0.0             0.0             0.0             0.0   \n",
+       "23816          1.0             1.0             0.0             0.0   \n",
+       "\n",
+       "       pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  pos_range   pos_rel  \\\n",
+       "56318             1.0             1.0            9   1.333334  0.976744   \n",
+       "11838             0.0             0.0            0  -0.183431 -0.580297   \n",
+       "60633             0.0             0.0            4   0.264557 -0.788021   \n",
+       "30971             0.0             0.0            4   0.088070 -0.666627   \n",
+       "23816             1.0             1.0            9   1.333334  1.162791   \n",
+       "\n",
+       "       pos_zeros  pos_inc_rng  pos_zeros_le  PxlMin_grp_le  PxlMin_zero  any  \\\n",
+       "56318        0.0    -0.599997             0              2        False  NaN   \n",
+       "11838        0.0    -0.583175             0              2        False  NaN   \n",
+       "60633        0.0    -0.584137             0              2        False  NaN   \n",
+       "30971        0.0    -0.597988             0              2        False  NaN   \n",
+       "23816        0.0    -0.599997             0              2        False  NaN   \n",
+       "\n",
+       "       epidural  intraparenchymal  intraventricular  subarachnoid  subdural  \\\n",
+       "56318       NaN               NaN               NaN           NaN       NaN   \n",
+       "11838       NaN               NaN               NaN           NaN       NaN   \n",
+       "60633       NaN               NaN               NaN           NaN       NaN   \n",
+       "30971       NaN               NaN               NaN           NaN       NaN   \n",
+       "23816       NaN               NaN               NaN           NaN       NaN   \n",
+       "\n",
+       "       any_series  SeriesPP  yuval_idx  pred_any  \n",
+       "56318       False      -0.5      20605  0.995869  \n",
+       "11838       False      -0.5      49264  0.995902  \n",
+       "60633       False      -0.5      59637  0.995940  \n",
+       "30971       False      -0.5      59366  0.995958  \n",
+       "23816       False      -0.5      20607  0.996068  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md['pred_any'] = predictions[:,2]\n",
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>8592</td>\n",
+       "      <td>2b3878103</td>\n",
+       "      <td>ID_2b3878103</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_b81caf1c</td>\n",
+       "      <td>ID_3d31a06240</td>\n",
+       "      <td>ID_25c620d29b</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '77.500000']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.394667</td>\n",
+       "      <td>-0.776436</td>\n",
+       "      <td>1.134899</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>77.5</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.128223</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.4800</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>16</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.266667</td>\n",
+       "      <td>0.064516</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>95036</td>\n",
+       "      <td>0.995983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>101233</td>\n",
+       "      <td>734856256</td>\n",
+       "      <td>ID_734856256</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_4482f018</td>\n",
+       "      <td>ID_5ccd14e6b7</td>\n",
+       "      <td>ID_b75da817b2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.438', '-126.438', '97.500']</td>\n",
+       "      <td>['1.0', '0.0', '0.0', '0.0', '1.0', '0.0']</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.4949', '0.4949']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.0</td>\n",
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+       "      <td>0.378667</td>\n",
+       "      <td>-0.862722</td>\n",
+       "      <td>1.089866</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
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+       "      <td>-126.438000</td>\n",
+       "      <td>-126.438000</td>\n",
+       "      <td>97.5</td>\n",
+       "      <td>0.494900</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
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+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.241653</td>\n",
+       "      <td>0.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>-0.099570</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.8792</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>0.135593</td>\n",
+       "      <td>19</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.303030</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>23495</td>\n",
+       "      <td>0.996200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>38580</td>\n",
+       "      <td>1bb3fe555</td>\n",
+       "      <td>ID_1bb3fe555</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_ca92b4e6</td>\n",
+       "      <td>ID_e14681614d</td>\n",
+       "      <td>ID_23f8022c7d</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '72.500000']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.472000</td>\n",
+       "      <td>-0.733947</td>\n",
+       "      <td>1.184966</td>\n",
+       "      <td>False</td>\n",
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+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>72.5</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.135387</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.4800</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>15</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.266667</td>\n",
+       "      <td>-0.064516</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>40054</td>\n",
+       "      <td>0.996345</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>29351</td>\n",
+       "      <td>5bd2084d9</td>\n",
+       "      <td>ID_5bd2084d9</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_4482f018</td>\n",
+       "      <td>ID_5ccd14e6b7</td>\n",
+       "      <td>ID_b75da817b2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.438', '-126.438', '102.500']</td>\n",
+       "      <td>['1.0', '0.0', '0.0', '0.0', '1.0', '0.0']</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.4949', '0.4949']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.442667</td>\n",
+       "      <td>-0.849438</td>\n",
+       "      <td>1.059636</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-126.438000</td>\n",
+       "      <td>-126.438000</td>\n",
+       "      <td>102.5</td>\n",
+       "      <td>0.494900</td>\n",
+       "      <td>0.494900</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1.241653</td>\n",
+       "      <td>0.0</td>\n",
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+       "      <td>0.0</td>\n",
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+       "      <td>-0.819173</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.092407</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.8792</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>20</td>\n",
+       "      <td>-0.271186</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.424242</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>23496</td>\n",
+       "      <td>0.996412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>90564</td>\n",
+       "      <td>2941d6eba</td>\n",
+       "      <td>ID_2941d6eba</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_ca92b4e6</td>\n",
+       "      <td>ID_e14681614d</td>\n",
+       "      <td>ID_23f8022c7d</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-126.408875', '-126.408875', '77.500000']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.494750976563', '0.494750976563']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>135.000000</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.482667</td>\n",
+       "      <td>-0.703788</td>\n",
+       "      <td>1.179639</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>-126.408875</td>\n",
+       "      <td>77.5</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>0.494751</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1.333333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.666667</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.720000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.818785</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.128223</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.4800</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>16</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.266667</td>\n",
+       "      <td>0.064516</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>40055</td>\n",
+       "      <td>0.996628</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "8592    2b3878103   ID_2b3878103       CT  ID_b81caf1c    ID_3d31a06240   \n",
+       "101233  734856256   ID_734856256       CT  ID_4482f018    ID_5ccd14e6b7   \n",
+       "38580   1bb3fe555   ID_1bb3fe555       CT  ID_ca92b4e6    ID_e14681614d   \n",
+       "29351   5bd2084d9   ID_5bd2084d9       CT  ID_4482f018    ID_5ccd14e6b7   \n",
+       "90564   2941d6eba   ID_2941d6eba       CT  ID_ca92b4e6    ID_e14681614d   \n",
+       "\n",
+       "       SeriesInstanceUID  StudyID  \\\n",
+       "8592       ID_25c620d29b      NaN   \n",
+       "101233     ID_b75da817b2      NaN   \n",
+       "38580      ID_23f8022c7d      NaN   \n",
+       "29351      ID_b75da817b2      NaN   \n",
+       "90564      ID_23f8022c7d      NaN   \n",
+       "\n",
+       "                               ImagePositionPatient  \\\n",
+       "8592    ['-126.408875', '-126.408875', '77.500000']   \n",
+       "101233           ['-126.438', '-126.438', '97.500']   \n",
+       "38580   ['-126.408875', '-126.408875', '72.500000']   \n",
+       "29351           ['-126.438', '-126.438', '102.500']   \n",
+       "90564   ['-126.408875', '-126.408875', '77.500000']   \n",
+       "\n",
+       "                                  ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "8592    ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "101233         ['1.0', '0.0', '0.0', '0.0', '1.0', '0.0']                1   \n",
+       "38580   ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "29351          ['1.0', '0.0', '0.0', '0.0', '1.0', '0.0']                1   \n",
+       "90564   ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "\n",
+       "       PhotometricInterpretation  Rows  Columns  \\\n",
+       "8592                 MONOCHROME2   512      512   \n",
+       "101233               MONOCHROME2   512      512   \n",
+       "38580                MONOCHROME2   512      512   \n",
+       "29351                MONOCHROME2   512      512   \n",
+       "90564                MONOCHROME2   512      512   \n",
+       "\n",
+       "                                PixelSpacing  BitsAllocated  BitsStored  \\\n",
+       "8592    ['0.494750976563', '0.494750976563']             16          16   \n",
+       "101233                  ['0.4949', '0.4949']             16          16   \n",
+       "38580   ['0.494750976563', '0.494750976563']             16          16   \n",
+       "29351                   ['0.4949', '0.4949']             16          16   \n",
+       "90564   ['0.494750976563', '0.494750976563']             16          16   \n",
+       "\n",
+       "        HighBit  PixelRepresentation WindowCenter WindowWidth  \\\n",
+       "8592         15                    1    35.000000  135.000000   \n",
+       "101233       15                    1         35.0       135.0   \n",
+       "38580        15                    1    35.000000  135.000000   \n",
+       "29351        15                    1         35.0       135.0   \n",
+       "90564        15                    1    35.000000  135.000000   \n",
+       "\n",
+       "        RescaleIntercept  RescaleSlope    PxlMin    PxlMax    PxlStd  \\\n",
+       "8592             -1024.0           1.0  1.301333  0.394667 -0.776436   \n",
+       "101233           -1024.0           1.0  1.301333  0.378667 -0.862722   \n",
+       "38580            -1024.0           1.0  1.301333  0.472000 -0.733947   \n",
+       "29351            -1024.0           1.0  1.301333  0.442667 -0.849438   \n",
+       "90564            -1024.0           1.0  1.301333  0.482667 -0.703788   \n",
+       "\n",
+       "         PxlMean   test  test2  ImageOrientationPatient_0  \\\n",
+       "8592    1.134899  False   True                        1.0   \n",
+       "101233  1.089866  False   True                        1.0   \n",
+       "38580   1.184966  False   True                        1.0   \n",
+       "29351   1.059636  False   True                        1.0   \n",
+       "90564   1.179639  False   True                        1.0   \n",
+       "\n",
+       "        ImageOrientationPatient_1  ImageOrientationPatient_2  \\\n",
+       "8592                          0.0                        0.0   \n",
+       "101233                        0.0                        0.0   \n",
+       "38580                         0.0                        0.0   \n",
+       "29351                         0.0                        0.0   \n",
+       "90564                         0.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_3  ImageOrientationPatient_4  \\\n",
+       "8592                          0.0                        1.0   \n",
+       "101233                        0.0                        1.0   \n",
+       "38580                         0.0                        1.0   \n",
+       "29351                         0.0                        1.0   \n",
+       "90564                         0.0                        1.0   \n",
+       "\n",
+       "        ImageOrientationPatient_5  ImagePositionPatient_0  \\\n",
+       "8592                          0.0             -126.408875   \n",
+       "101233                        0.0             -126.438000   \n",
+       "38580                         0.0             -126.408875   \n",
+       "29351                         0.0             -126.438000   \n",
+       "90564                         0.0             -126.408875   \n",
+       "\n",
+       "        ImagePositionPatient_1  ImagePositionPatient_2  PixelSpacing_0  \\\n",
+       "8592               -126.408875                    77.5        0.494751   \n",
+       "101233             -126.438000                    97.5        0.494900   \n",
+       "38580              -126.408875                    72.5        0.494751   \n",
+       "29351              -126.438000                   102.5        0.494900   \n",
+       "90564              -126.408875                    77.5        0.494751   \n",
+       "\n",
+       "        PixelSpacing_1  WindowCenter_0  WindowCenter_1  WindowCenter_1_NAN  \\\n",
+       "8592          0.494751            35.0             NaN                True   \n",
+       "101233        0.494900            35.0             NaN                True   \n",
+       "38580         0.494751            35.0             NaN                True   \n",
+       "29351         0.494900            35.0             NaN                True   \n",
+       "90564         0.494751            35.0             NaN                True   \n",
+       "\n",
+       "        WindowWidth_0  WindowWidth_1  WindowWidth_0_le  WindowWidth_1_le  \\\n",
+       "8592            135.0            NaN                 3                 1   \n",
+       "101233          135.0            NaN                 3                 1   \n",
+       "38580           135.0            NaN                 3                 1   \n",
+       "29351           135.0            NaN                 3                 1   \n",
+       "90564           135.0            NaN                 3                 1   \n",
+       "\n",
+       "        WindowCenter_1_le  BitType_le  ImageOrientationPatient_4_f  \\\n",
+       "8592                    3           0                    -1.333333   \n",
+       "101233                  3           0                    -1.333333   \n",
+       "38580                   3           0                    -1.333333   \n",
+       "29351                   3           0                    -1.333333   \n",
+       "90564                   3           0                    -1.333333   \n",
+       "\n",
+       "        ImageOrientationPatient_4_enc_0  ...  ImageOrientationPatient_5_f  \\\n",
+       "8592                                1.0  ...                    -0.666667   \n",
+       "101233                              1.0  ...                    -0.666667   \n",
+       "38580                               1.0  ...                    -0.666667   \n",
+       "29351                               1.0  ...                    -0.666667   \n",
+       "90564                               1.0  ...                    -0.666667   \n",
+       "\n",
+       "        ImageOrientationPatient_5_enc_0  ImageOrientationPatient_5_enc_1  \\\n",
+       "8592                                1.0                            False   \n",
+       "101233                              1.0                            False   \n",
+       "38580                               1.0                            False   \n",
+       "29351                               1.0                            False   \n",
+       "90564                               1.0                            False   \n",
+       "\n",
+       "        ImagePositionPatient_0_f  ImagePositionPatient_0_enc_0  \\\n",
+       "8592                   -0.720000                           0.0   \n",
+       "101233                  1.241653                           0.0   \n",
+       "38580                  -0.720000                           0.0   \n",
+       "29351                   1.241653                           0.0   \n",
+       "90564                  -0.720000                           0.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_enc_1  ImagePositionPatient_0_f_r1  \\\n",
+       "8592                             1.0                          1.0   \n",
+       "101233                           0.0                          0.0   \n",
+       "38580                            1.0                          1.0   \n",
+       "29351                            0.0                          0.0   \n",
+       "90564                            1.0                          1.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_f_r05  ImagePositionPatient_1_f  \\\n",
+       "8592                             1.0                 -0.818785   \n",
+       "101233                           0.0                 -0.819173   \n",
+       "38580                            1.0                 -0.818785   \n",
+       "29351                            0.0                 -0.819173   \n",
+       "90564                            1.0                 -0.818785   \n",
+       "\n",
+       "        ImagePositionPatient_1_enc_0  ImagePositionPatient_2_f  \\\n",
+       "8592                             0.0                 -0.128223   \n",
+       "101233                           0.0                 -0.099570   \n",
+       "38580                            0.0                 -0.135387   \n",
+       "29351                            0.0                 -0.092407   \n",
+       "90564                            0.0                 -0.128223   \n",
+       "\n",
+       "        ImagePositionPatient_2_f_r05  PixelSpacing_1_f  PixelSpacing_1_enc_0  \\\n",
+       "8592                             1.0           -0.4800                   0.0   \n",
+       "101233                           1.0            1.8792                   0.0   \n",
+       "38580                            1.0           -0.4800                   0.0   \n",
+       "29351                            1.0            1.8792                   0.0   \n",
+       "90564                            1.0           -0.4800                   0.0   \n",
+       "\n",
+       "        PixelSpacing_1_enc_1  WindowCenter_0_le  pos_max  pos_min  pos_size  \\\n",
+       "8592                    True                  3     0.61    -0.01      -0.3   \n",
+       "101233                 False                  3     0.67     0.01      -0.1   \n",
+       "38580                   True                  3     0.61    -0.01      -0.3   \n",
+       "29351                  False                  3     0.67     0.01      -0.1   \n",
+       "90564                   True                  3     0.61    -0.01      -0.3   \n",
+       "\n",
+       "        pos_idx1  pos_idx  pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  \\\n",
+       "8592   -0.067797       16 -0.135593      -1.5      -1.5                3   \n",
+       "101233  0.135593       19 -0.203390      -1.5      -1.5                3   \n",
+       "38580  -0.135593       15 -0.067797      -1.5      -1.5                3   \n",
+       "29351   0.203390       20 -0.271186      -1.5      -1.5                3   \n",
+       "90564  -0.067797       16 -0.135593      -1.5      -1.5                3   \n",
+       "\n",
+       "        pos_inc2_grp_le  pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  \\\n",
+       "8592                  3          1.0             1.0             0.0   \n",
+       "101233                3          1.0             1.0             0.0   \n",
+       "38580                 3          1.0             1.0             0.0   \n",
+       "29351                 3          1.0             1.0             0.0   \n",
+       "90564                 3          1.0             1.0             0.0   \n",
+       "\n",
+       "        pos_inc2_enc_0  pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  \\\n",
+       "8592               0.0             1.0             1.0            0   \n",
+       "101233             0.0             1.0             1.0            4   \n",
+       "38580              0.0             1.0             1.0            0   \n",
+       "29351              0.0             1.0             1.0            4   \n",
+       "90564              0.0             1.0             1.0            0   \n",
+       "\n",
+       "        pos_range   pos_rel  pos_zeros  pos_inc_rng  pos_zeros_le  \\\n",
+       "8592    -0.266667  0.064516        0.0         -0.6             0   \n",
+       "101233   0.000000  0.303030        0.0         -0.6             0   \n",
+       "38580   -0.266667 -0.064516        0.0         -0.6             0   \n",
+       "29351    0.000000  0.424242        0.0         -0.6             0   \n",
+       "90564   -0.266667  0.064516        0.0         -0.6             0   \n",
+       "\n",
+       "        PxlMin_grp_le  PxlMin_zero  any  epidural  intraparenchymal  \\\n",
+       "8592                2        False  NaN       NaN               NaN   \n",
+       "101233              2        False  NaN       NaN               NaN   \n",
+       "38580               2        False  NaN       NaN               NaN   \n",
+       "29351               2        False  NaN       NaN               NaN   \n",
+       "90564               2        False  NaN       NaN               NaN   \n",
+       "\n",
+       "        intraventricular  subarachnoid  subdural  any_series  SeriesPP  \\\n",
+       "8592                 NaN           NaN       NaN       False      -0.5   \n",
+       "101233               NaN           NaN       NaN       False      -0.5   \n",
+       "38580                NaN           NaN       NaN       False      -0.5   \n",
+       "29351                NaN           NaN       NaN       False      -0.5   \n",
+       "90564                NaN           NaN       NaN       False      -0.5   \n",
+       "\n",
+       "        yuval_idx  pred_any  \n",
+       "8592        95036  0.995983  \n",
+       "101233      23495  0.996200  \n",
+       "38580       40054  0.996345  \n",
+       "29351       23496  0.996412  \n",
+       "90564       40055  0.996628  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md['pred_any'] = predictions[:,3]\n",
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>46433</td>\n",
+       "      <td>f3a75309f</td>\n",
+       "      <td>ID_f3a75309f</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f6723c35</td>\n",
+       "      <td>ID_fc07fac521</td>\n",
+       "      <td>ID_cfd350c878</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-118.558', '151.625']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064</td>\n",
+       "      <td>0.292000</td>\n",
+       "      <td>0.113617</td>\n",
+       "      <td>-0.426832</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.961262</td>\n",
+       "      <td>-0.275637</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-118.558</td>\n",
+       "      <td>151.625</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.15016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.495753</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.714107</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.022027</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.68972</td>\n",
+       "      <td>0.127984</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.406780</td>\n",
+       "      <td>23</td>\n",
+       "      <td>-0.881356</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.655093</td>\n",
+       "      <td>1.407408</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>55354</td>\n",
+       "      <td>0.993246</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>59590</td>\n",
+       "      <td>dc7e09cbd</td>\n",
+       "      <td>ID_dc7e09cbd</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f6723c35</td>\n",
+       "      <td>ID_fc07fac521</td>\n",
+       "      <td>ID_cfd350c878</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-118.558', '130.820']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
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+       "      <td>-0.064</td>\n",
+       "      <td>0.180000</td>\n",
+       "      <td>0.216861</td>\n",
+       "      <td>-0.102710</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.961262</td>\n",
+       "      <td>-0.275637</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-118.558</td>\n",
+       "      <td>130.820</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.15016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.495753</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
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+       "      <td>1.0</td>\n",
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+       "      <td>1.0</td>\n",
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+       "      <td>-0.051834</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.68972</td>\n",
+       "      <td>0.127984</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.135593</td>\n",
+       "      <td>19</td>\n",
+       "      <td>-0.610169</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.655093</td>\n",
+       "      <td>0.814817</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>55350</td>\n",
+       "      <td>0.993314</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>33815</td>\n",
+       "      <td>397e899f6</td>\n",
+       "      <td>ID_397e899f6</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f6723c35</td>\n",
+       "      <td>ID_fc07fac521</td>\n",
+       "      <td>ID_cfd350c878</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-118.558', '146.424']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
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+       "      <td>0.218667</td>\n",
+       "      <td>0.157382</td>\n",
+       "      <td>-0.319805</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
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+       "      <td>0.961262</td>\n",
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+       "      <td>-125.0</td>\n",
+       "      <td>-118.558</td>\n",
+       "      <td>146.424</td>\n",
+       "      <td>0.488281</td>\n",
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+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
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+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>2.15016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.495753</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
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+       "      <td>1.0</td>\n",
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+       "      <td>-0.714107</td>\n",
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+       "      <td>-0.029479</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.68972</td>\n",
+       "      <td>0.127984</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.338983</td>\n",
+       "      <td>22</td>\n",
+       "      <td>-0.813559</td>\n",
+       "      <td>1.6010</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.655093</td>\n",
+       "      <td>1.259268</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>55353</td>\n",
+       "      <td>0.993623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2113</td>\n",
+       "      <td>ed2a8477b</td>\n",
+       "      <td>ID_ed2a8477b</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f6723c35</td>\n",
+       "      <td>ID_fc07fac521</td>\n",
+       "      <td>ID_cfd350c878</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-118.558', '141.222']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064</td>\n",
+       "      <td>0.169333</td>\n",
+       "      <td>0.193354</td>\n",
+       "      <td>-0.226621</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.961262</td>\n",
+       "      <td>-0.275637</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-118.558</td>\n",
+       "      <td>141.222</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.15016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.495753</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
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+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.714107</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.036931</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.68972</td>\n",
+       "      <td>0.127984</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.271186</td>\n",
+       "      <td>21</td>\n",
+       "      <td>-0.745763</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>1.6010</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.655093</td>\n",
+       "      <td>1.111098</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>55352</td>\n",
+       "      <td>0.993728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>61829</td>\n",
+       "      <td>b2d64d052</td>\n",
+       "      <td>ID_b2d64d052</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_f6723c35</td>\n",
+       "      <td>ID_fc07fac521</td>\n",
+       "      <td>ID_cfd350c878</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125.000', '-118.558', '136.021']</td>\n",
+       "      <td>['1.000000', '0.000000', '0.000000', '0.000000...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.488281', '0.488281']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>150</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.064</td>\n",
+       "      <td>0.148000</td>\n",
+       "      <td>0.208909</td>\n",
+       "      <td>-0.156506</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.961262</td>\n",
+       "      <td>-0.275637</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>-118.558</td>\n",
+       "      <td>136.021</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.15016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.495753</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.714107</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.044383</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.68972</td>\n",
+       "      <td>0.127984</td>\n",
+       "      <td>-0.7</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>20</td>\n",
+       "      <td>-0.677966</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>1.6005</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.655093</td>\n",
+       "      <td>0.962958</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.599615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>55351</td>\n",
+       "      <td>0.993775</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "46433  f3a75309f   ID_f3a75309f       CT  ID_f6723c35    ID_fc07fac521   \n",
+       "59590  dc7e09cbd   ID_dc7e09cbd       CT  ID_f6723c35    ID_fc07fac521   \n",
+       "33815  397e899f6   ID_397e899f6       CT  ID_f6723c35    ID_fc07fac521   \n",
+       "2113   ed2a8477b   ID_ed2a8477b       CT  ID_f6723c35    ID_fc07fac521   \n",
+       "61829  b2d64d052   ID_b2d64d052       CT  ID_f6723c35    ID_fc07fac521   \n",
+       "\n",
+       "      SeriesInstanceUID  StudyID                 ImagePositionPatient  \\\n",
+       "46433     ID_cfd350c878      NaN  ['-125.000', '-118.558', '151.625']   \n",
+       "59590     ID_cfd350c878      NaN  ['-125.000', '-118.558', '130.820']   \n",
+       "33815     ID_cfd350c878      NaN  ['-125.000', '-118.558', '146.424']   \n",
+       "2113      ID_cfd350c878      NaN  ['-125.000', '-118.558', '141.222']   \n",
+       "61829     ID_cfd350c878      NaN  ['-125.000', '-118.558', '136.021']   \n",
+       "\n",
+       "                                 ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "46433  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "59590  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "33815  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "2113   ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "61829  ['1.000000', '0.000000', '0.000000', '0.000000...                1   \n",
+       "\n",
+       "      PhotometricInterpretation  Rows  Columns              PixelSpacing  \\\n",
+       "46433               MONOCHROME2   512      512  ['0.488281', '0.488281']   \n",
+       "59590               MONOCHROME2   512      512  ['0.488281', '0.488281']   \n",
+       "33815               MONOCHROME2   512      512  ['0.488281', '0.488281']   \n",
+       "2113                MONOCHROME2   512      512  ['0.488281', '0.488281']   \n",
+       "61829               MONOCHROME2   512      512  ['0.488281', '0.488281']   \n",
+       "\n",
+       "       BitsAllocated  BitsStored  HighBit  PixelRepresentation WindowCenter  \\\n",
+       "46433             16          16       15                    1           40   \n",
+       "59590             16          16       15                    1           40   \n",
+       "33815             16          16       15                    1           40   \n",
+       "2113              16          16       15                    1           40   \n",
+       "61829             16          16       15                    1           40   \n",
+       "\n",
+       "      WindowWidth  RescaleIntercept  RescaleSlope  PxlMin    PxlMax    PxlStd  \\\n",
+       "46433         150           -1024.0           1.0  -0.064  0.292000  0.113617   \n",
+       "59590         150           -1024.0           1.0  -0.064  0.180000  0.216861   \n",
+       "33815         150           -1024.0           1.0  -0.064  0.218667  0.157382   \n",
+       "2113          150           -1024.0           1.0  -0.064  0.169333  0.193354   \n",
+       "61829         150           -1024.0           1.0  -0.064  0.148000  0.208909   \n",
+       "\n",
+       "        PxlMean   test  test2  ImageOrientationPatient_0  \\\n",
+       "46433 -0.426832  False   True                        1.0   \n",
+       "59590 -0.102710  False   True                        1.0   \n",
+       "33815 -0.319805  False   True                        1.0   \n",
+       "2113  -0.226621  False   True                        1.0   \n",
+       "61829 -0.156506  False   True                        1.0   \n",
+       "\n",
+       "       ImageOrientationPatient_1  ImageOrientationPatient_2  \\\n",
+       "46433                        0.0                        0.0   \n",
+       "59590                        0.0                        0.0   \n",
+       "33815                        0.0                        0.0   \n",
+       "2113                         0.0                        0.0   \n",
+       "61829                        0.0                        0.0   \n",
+       "\n",
+       "       ImageOrientationPatient_3  ImageOrientationPatient_4  \\\n",
+       "46433                        0.0                   0.961262   \n",
+       "59590                        0.0                   0.961262   \n",
+       "33815                        0.0                   0.961262   \n",
+       "2113                         0.0                   0.961262   \n",
+       "61829                        0.0                   0.961262   \n",
+       "\n",
+       "       ImageOrientationPatient_5  ImagePositionPatient_0  \\\n",
+       "46433                  -0.275637                  -125.0   \n",
+       "59590                  -0.275637                  -125.0   \n",
+       "33815                  -0.275637                  -125.0   \n",
+       "2113                   -0.275637                  -125.0   \n",
+       "61829                  -0.275637                  -125.0   \n",
+       "\n",
+       "       ImagePositionPatient_1  ImagePositionPatient_2  PixelSpacing_0  \\\n",
+       "46433                -118.558                 151.625        0.488281   \n",
+       "59590                -118.558                 130.820        0.488281   \n",
+       "33815                -118.558                 146.424        0.488281   \n",
+       "2113                 -118.558                 141.222        0.488281   \n",
+       "61829                -118.558                 136.021        0.488281   \n",
+       "\n",
+       "       PixelSpacing_1  WindowCenter_0  WindowCenter_1  WindowCenter_1_NAN  \\\n",
+       "46433        0.488281            40.0             NaN                True   \n",
+       "59590        0.488281            40.0             NaN                True   \n",
+       "33815        0.488281            40.0             NaN                True   \n",
+       "2113         0.488281            40.0             NaN                True   \n",
+       "61829        0.488281            40.0             NaN                True   \n",
+       "\n",
+       "       WindowWidth_0  WindowWidth_1  WindowWidth_0_le  WindowWidth_1_le  \\\n",
+       "46433          150.0            NaN                 1                 1   \n",
+       "59590          150.0            NaN                 1                 1   \n",
+       "33815          150.0            NaN                 1                 1   \n",
+       "2113           150.0            NaN                 1                 1   \n",
+       "61829          150.0            NaN                 1                 1   \n",
+       "\n",
+       "       WindowCenter_1_le  BitType_le  ImageOrientationPatient_4_f  \\\n",
+       "46433                  3           0                      2.15016   \n",
+       "59590                  3           0                      2.15016   \n",
+       "33815                  3           0                      2.15016   \n",
+       "2113                   3           0                      2.15016   \n",
+       "61829                  3           0                      2.15016   \n",
+       "\n",
+       "       ImageOrientationPatient_4_enc_0  ...  ImageOrientationPatient_5_f  \\\n",
+       "46433                              0.0  ...                     1.495753   \n",
+       "59590                              0.0  ...                     1.495753   \n",
+       "33815                              0.0  ...                     1.495753   \n",
+       "2113                               0.0  ...                     1.495753   \n",
+       "61829                              0.0  ...                     1.495753   \n",
+       "\n",
+       "       ImageOrientationPatient_5_enc_0  ImageOrientationPatient_5_enc_1  \\\n",
+       "46433                              0.0                            False   \n",
+       "59590                              0.0                            False   \n",
+       "33815                              0.0                            False   \n",
+       "2113                               0.0                            False   \n",
+       "61829                              0.0                            False   \n",
+       "\n",
+       "       ImagePositionPatient_0_f  ImagePositionPatient_0_enc_0  \\\n",
+       "46433                     -0.72                           1.0   \n",
+       "59590                     -0.72                           1.0   \n",
+       "33815                     -0.72                           1.0   \n",
+       "2113                      -0.72                           1.0   \n",
+       "61829                     -0.72                           1.0   \n",
+       "\n",
+       "       ImagePositionPatient_0_enc_1  ImagePositionPatient_0_f_r1  \\\n",
+       "46433                           0.0                          1.0   \n",
+       "59590                           0.0                          1.0   \n",
+       "33815                           0.0                          1.0   \n",
+       "2113                            0.0                          1.0   \n",
+       "61829                           0.0                          1.0   \n",
+       "\n",
+       "       ImagePositionPatient_0_f_r05  ImagePositionPatient_1_f  \\\n",
+       "46433                           1.0                 -0.714107   \n",
+       "59590                           1.0                 -0.714107   \n",
+       "33815                           1.0                 -0.714107   \n",
+       "2113                            1.0                 -0.714107   \n",
+       "61829                           1.0                 -0.714107   \n",
+       "\n",
+       "       ImagePositionPatient_1_enc_0  ImagePositionPatient_2_f  \\\n",
+       "46433                           0.0                 -0.022027   \n",
+       "59590                           0.0                 -0.051834   \n",
+       "33815                           0.0                 -0.029479   \n",
+       "2113                            0.0                 -0.036931   \n",
+       "61829                           0.0                 -0.044383   \n",
+       "\n",
+       "       ImagePositionPatient_2_f_r05  PixelSpacing_1_f  PixelSpacing_1_enc_0  \\\n",
+       "46433                           0.0             -0.48                   1.0   \n",
+       "59590                           0.0             -0.48                   1.0   \n",
+       "33815                           0.0             -0.48                   1.0   \n",
+       "2113                            0.0             -0.48                   1.0   \n",
+       "61829                           0.0             -0.48                   1.0   \n",
+       "\n",
+       "       PixelSpacing_1_enc_1  WindowCenter_0_le  pos_max   pos_min  pos_size  \\\n",
+       "46433                 False                  2  0.68972  0.127984      -0.7   \n",
+       "59590                 False                  2  0.68972  0.127984      -0.7   \n",
+       "33815                 False                  2  0.68972  0.127984      -0.7   \n",
+       "2113                  False                  2  0.68972  0.127984      -0.7   \n",
+       "61829                 False                  2  0.68972  0.127984      -0.7   \n",
+       "\n",
+       "       pos_idx1  pos_idx  pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  \\\n",
+       "46433  0.406780       23 -0.881356    1.6005    1.6005                3   \n",
+       "59590  0.135593       19 -0.610169    1.6005    1.6005                3   \n",
+       "33815  0.338983       22 -0.813559    1.6010    1.6005                3   \n",
+       "2113   0.271186       21 -0.745763    1.6005    1.6010                3   \n",
+       "61829  0.203390       20 -0.677966    1.6005    1.6005                3   \n",
+       "\n",
+       "       pos_inc2_grp_le  pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  \\\n",
+       "46433                3          0.0             1.0             0.0   \n",
+       "59590                3          0.0             1.0             0.0   \n",
+       "33815                3          0.0             1.0             0.0   \n",
+       "2113                 3          0.0             1.0             0.0   \n",
+       "61829                3          0.0             1.0             0.0   \n",
+       "\n",
+       "       pos_inc2_enc_0  pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  pos_range  \\\n",
+       "46433             0.0             0.0             0.0            3  -0.655093   \n",
+       "59590             0.0             0.0             0.0            3  -0.655093   \n",
+       "33815             0.0             0.0             0.0            3  -0.655093   \n",
+       "2113              0.0             0.0             0.0            3  -0.655093   \n",
+       "61829             0.0             0.0             0.0            3  -0.655093   \n",
+       "\n",
+       "        pos_rel  pos_zeros  pos_inc_rng  pos_zeros_le  PxlMin_grp_le  \\\n",
+       "46433  1.407408        0.0    -0.599615             0              1   \n",
+       "59590  0.814817        0.0    -0.599615             0              1   \n",
+       "33815  1.259268        0.0    -0.599615             0              1   \n",
+       "2113   1.111098        0.0    -0.599615             0              1   \n",
+       "61829  0.962958        0.0    -0.599615             0              1   \n",
+       "\n",
+       "       PxlMin_zero  any  epidural  intraparenchymal  intraventricular  \\\n",
+       "46433        False  NaN       NaN               NaN               NaN   \n",
+       "59590        False  NaN       NaN               NaN               NaN   \n",
+       "33815        False  NaN       NaN               NaN               NaN   \n",
+       "2113         False  NaN       NaN               NaN               NaN   \n",
+       "61829        False  NaN       NaN               NaN               NaN   \n",
+       "\n",
+       "       subarachnoid  subdural  any_series  SeriesPP  yuval_idx  pred_any  \n",
+       "46433           NaN       NaN       False      -0.5      55354  0.993246  \n",
+       "59590           NaN       NaN       False      -0.5      55350  0.993314  \n",
+       "33815           NaN       NaN       False      -0.5      55353  0.993623  \n",
+       "2113            NaN       NaN       False      -0.5      55352  0.993728  \n",
+       "61829           NaN       NaN       False      -0.5      55351  0.993775  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md['pred_any'] = predictions[:,4]\n",
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>img_id</th>\n",
+       "      <th>SOPInstanceUID</th>\n",
+       "      <th>Modality</th>\n",
+       "      <th>PatientID</th>\n",
+       "      <th>StudyInstanceUID</th>\n",
+       "      <th>SeriesInstanceUID</th>\n",
+       "      <th>StudyID</th>\n",
+       "      <th>ImagePositionPatient</th>\n",
+       "      <th>ImageOrientationPatient</th>\n",
+       "      <th>SamplesPerPixel</th>\n",
+       "      <th>PhotometricInterpretation</th>\n",
+       "      <th>Rows</th>\n",
+       "      <th>Columns</th>\n",
+       "      <th>PixelSpacing</th>\n",
+       "      <th>BitsAllocated</th>\n",
+       "      <th>BitsStored</th>\n",
+       "      <th>HighBit</th>\n",
+       "      <th>PixelRepresentation</th>\n",
+       "      <th>WindowCenter</th>\n",
+       "      <th>WindowWidth</th>\n",
+       "      <th>RescaleIntercept</th>\n",
+       "      <th>RescaleSlope</th>\n",
+       "      <th>PxlMin</th>\n",
+       "      <th>PxlMax</th>\n",
+       "      <th>PxlStd</th>\n",
+       "      <th>PxlMean</th>\n",
+       "      <th>test</th>\n",
+       "      <th>test2</th>\n",
+       "      <th>ImageOrientationPatient_0</th>\n",
+       "      <th>ImageOrientationPatient_1</th>\n",
+       "      <th>ImageOrientationPatient_2</th>\n",
+       "      <th>ImageOrientationPatient_3</th>\n",
+       "      <th>ImageOrientationPatient_4</th>\n",
+       "      <th>ImageOrientationPatient_5</th>\n",
+       "      <th>ImagePositionPatient_0</th>\n",
+       "      <th>ImagePositionPatient_1</th>\n",
+       "      <th>ImagePositionPatient_2</th>\n",
+       "      <th>PixelSpacing_0</th>\n",
+       "      <th>PixelSpacing_1</th>\n",
+       "      <th>WindowCenter_0</th>\n",
+       "      <th>WindowCenter_1</th>\n",
+       "      <th>WindowCenter_1_NAN</th>\n",
+       "      <th>WindowWidth_0</th>\n",
+       "      <th>WindowWidth_1</th>\n",
+       "      <th>WindowWidth_0_le</th>\n",
+       "      <th>WindowWidth_1_le</th>\n",
+       "      <th>WindowCenter_1_le</th>\n",
+       "      <th>BitType_le</th>\n",
+       "      <th>ImageOrientationPatient_4_f</th>\n",
+       "      <th>ImageOrientationPatient_4_enc_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ImageOrientationPatient_5_f</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_0</th>\n",
+       "      <th>ImageOrientationPatient_5_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f</th>\n",
+       "      <th>ImagePositionPatient_0_enc_0</th>\n",
+       "      <th>ImagePositionPatient_0_enc_1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r1</th>\n",
+       "      <th>ImagePositionPatient_0_f_r05</th>\n",
+       "      <th>ImagePositionPatient_1_f</th>\n",
+       "      <th>ImagePositionPatient_1_enc_0</th>\n",
+       "      <th>ImagePositionPatient_2_f</th>\n",
+       "      <th>ImagePositionPatient_2_f_r05</th>\n",
+       "      <th>PixelSpacing_1_f</th>\n",
+       "      <th>PixelSpacing_1_enc_0</th>\n",
+       "      <th>PixelSpacing_1_enc_1</th>\n",
+       "      <th>WindowCenter_0_le</th>\n",
+       "      <th>pos_max</th>\n",
+       "      <th>pos_min</th>\n",
+       "      <th>pos_size</th>\n",
+       "      <th>pos_idx1</th>\n",
+       "      <th>pos_idx</th>\n",
+       "      <th>pos_idx2</th>\n",
+       "      <th>pos_inc1</th>\n",
+       "      <th>pos_inc2</th>\n",
+       "      <th>pos_inc1_grp_le</th>\n",
+       "      <th>pos_inc2_grp_le</th>\n",
+       "      <th>pos_inc1_r1</th>\n",
+       "      <th>pos_inc1_r0001</th>\n",
+       "      <th>pos_inc1_enc_0</th>\n",
+       "      <th>pos_inc2_enc_0</th>\n",
+       "      <th>pos_inc1_enc_1</th>\n",
+       "      <th>pos_inc2_enc_1</th>\n",
+       "      <th>pos_size_le</th>\n",
+       "      <th>pos_range</th>\n",
+       "      <th>pos_rel</th>\n",
+       "      <th>pos_zeros</th>\n",
+       "      <th>pos_inc_rng</th>\n",
+       "      <th>pos_zeros_le</th>\n",
+       "      <th>PxlMin_grp_le</th>\n",
+       "      <th>PxlMin_zero</th>\n",
+       "      <th>any</th>\n",
+       "      <th>epidural</th>\n",
+       "      <th>intraparenchymal</th>\n",
+       "      <th>intraventricular</th>\n",
+       "      <th>subarachnoid</th>\n",
+       "      <th>subdural</th>\n",
+       "      <th>any_series</th>\n",
+       "      <th>SeriesPP</th>\n",
+       "      <th>yuval_idx</th>\n",
+       "      <th>pred_any</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>9661</td>\n",
+       "      <td>feb0a9076</td>\n",
+       "      <td>ID_feb0a9076</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_252323d1</td>\n",
+       "      <td>ID_0257ad04c2</td>\n",
+       "      <td>ID_58b46714eb</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '24.4169536', '204.228683']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.990268069', '-0.139173...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.126667</td>\n",
+       "      <td>-0.761993</td>\n",
+       "      <td>1.166719</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.990268</td>\n",
+       "      <td>-0.139173</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>24.416954</td>\n",
+       "      <td>204.228683</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.536908</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.405513</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.192226</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.053336</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.099715</td>\n",
+       "      <td>0.473493</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>17</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>1.527710</td>\n",
+       "      <td>1.522339</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-0.225189</td>\n",
+       "      <td>0.193609</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.595692</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>49823</td>\n",
+       "      <td>0.992338</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>107285</td>\n",
+       "      <td>cfbf38afe</td>\n",
+       "      <td>ID_cfbf38afe</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_6e75b42a</td>\n",
+       "      <td>ID_b94674c76f</td>\n",
+       "      <td>ID_93d835d9f3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '17.5586391', '177.279488']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.933580426', '-0.358367...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.098667</td>\n",
+       "      <td>-0.807341</td>\n",
+       "      <td>1.049002</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.933580</td>\n",
+       "      <td>-0.358368</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>17.558639</td>\n",
+       "      <td>177.279488</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.781072</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.944214</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.100782</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.014727</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.051518</td>\n",
+       "      <td>0.388022</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>15</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>1.687011</td>\n",
+       "      <td>1.663025</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.023307</td>\n",
+       "      <td>-0.064219</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.581939</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>74776</td>\n",
+       "      <td>0.992465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>81787</td>\n",
+       "      <td>95aace9ba</td>\n",
+       "      <td>ID_95aace9ba</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_6e75b42a</td>\n",
+       "      <td>ID_b94674c76f</td>\n",
+       "      <td>ID_93d835d9f3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '17.5586391', '193.305489']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.933580426', '-0.358367...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.086667</td>\n",
+       "      <td>-0.789830</td>\n",
+       "      <td>0.920645</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.933580</td>\n",
+       "      <td>-0.358368</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>17.558639</td>\n",
+       "      <td>193.305489</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.781072</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.944214</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.100782</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.037687</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.051518</td>\n",
+       "      <td>0.388022</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>0.067797</td>\n",
+       "      <td>18</td>\n",
+       "      <td>-0.271186</td>\n",
+       "      <td>1.662964</td>\n",
+       "      <td>1.687012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.023307</td>\n",
+       "      <td>0.322242</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.581939</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>74779</td>\n",
+       "      <td>0.992568</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>87951</td>\n",
+       "      <td>5092c392f</td>\n",
+       "      <td>ID_5092c392f</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_6e75b42a</td>\n",
+       "      <td>ID_b94674c76f</td>\n",
+       "      <td>ID_93d835d9f3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '17.5586391', '187.979561']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.933580426', '-0.358367...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.130667</td>\n",
+       "      <td>-0.782852</td>\n",
+       "      <td>0.978311</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.933580</td>\n",
+       "      <td>-0.358368</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>17.558639</td>\n",
+       "      <td>187.979561</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.781072</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.944214</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.100782</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.030057</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.051518</td>\n",
+       "      <td>0.388022</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>17</td>\n",
+       "      <td>-0.203390</td>\n",
+       "      <td>1.687011</td>\n",
+       "      <td>1.662964</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.023307</td>\n",
+       "      <td>0.193809</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.581939</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>74778</td>\n",
+       "      <td>0.992820</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>86533</td>\n",
+       "      <td>3a20374d3</td>\n",
+       "      <td>ID_3a20374d3</td>\n",
+       "      <td>CT</td>\n",
+       "      <td>ID_6e75b42a</td>\n",
+       "      <td>ID_b94674c76f</td>\n",
+       "      <td>ID_93d835d9f3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>['-125', '17.5586391', '182.605538']</td>\n",
+       "      <td>['1', '0', '0', '0', '0.933580426', '-0.358367...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>MONOCHROME2</td>\n",
+       "      <td>512</td>\n",
+       "      <td>512</td>\n",
+       "      <td>['0.48828125', '0.48828125']</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>['00040', '00040']</td>\n",
+       "      <td>['00080', '00080']</td>\n",
+       "      <td>-1024.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.301333</td>\n",
+       "      <td>0.124000</td>\n",
+       "      <td>-0.788199</td>\n",
+       "      <td>1.016346</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.933580</td>\n",
+       "      <td>-0.358368</td>\n",
+       "      <td>-125.0</td>\n",
+       "      <td>17.558639</td>\n",
+       "      <td>182.605538</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>0.488281</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.781072</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.944214</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.72</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.100782</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.022358</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.051518</td>\n",
+       "      <td>0.388022</td>\n",
+       "      <td>-0.3</td>\n",
+       "      <td>-0.067797</td>\n",
+       "      <td>16</td>\n",
+       "      <td>-0.135593</td>\n",
+       "      <td>1.663025</td>\n",
+       "      <td>1.687011</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.023307</td>\n",
+       "      <td>0.064217</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.581939</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>74777</td>\n",
+       "      <td>0.992826</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           img_id SOPInstanceUID Modality    PatientID StudyInstanceUID  \\\n",
+       "9661    feb0a9076   ID_feb0a9076       CT  ID_252323d1    ID_0257ad04c2   \n",
+       "107285  cfbf38afe   ID_cfbf38afe       CT  ID_6e75b42a    ID_b94674c76f   \n",
+       "81787   95aace9ba   ID_95aace9ba       CT  ID_6e75b42a    ID_b94674c76f   \n",
+       "87951   5092c392f   ID_5092c392f       CT  ID_6e75b42a    ID_b94674c76f   \n",
+       "86533   3a20374d3   ID_3a20374d3       CT  ID_6e75b42a    ID_b94674c76f   \n",
+       "\n",
+       "       SeriesInstanceUID  StudyID                  ImagePositionPatient  \\\n",
+       "9661       ID_58b46714eb      NaN  ['-125', '24.4169536', '204.228683']   \n",
+       "107285     ID_93d835d9f3      NaN  ['-125', '17.5586391', '177.279488']   \n",
+       "81787      ID_93d835d9f3      NaN  ['-125', '17.5586391', '193.305489']   \n",
+       "87951      ID_93d835d9f3      NaN  ['-125', '17.5586391', '187.979561']   \n",
+       "86533      ID_93d835d9f3      NaN  ['-125', '17.5586391', '182.605538']   \n",
+       "\n",
+       "                                  ImageOrientationPatient  SamplesPerPixel  \\\n",
+       "9661    ['1', '0', '0', '0', '0.990268069', '-0.139173...                1   \n",
+       "107285  ['1', '0', '0', '0', '0.933580426', '-0.358367...                1   \n",
+       "81787   ['1', '0', '0', '0', '0.933580426', '-0.358367...                1   \n",
+       "87951   ['1', '0', '0', '0', '0.933580426', '-0.358367...                1   \n",
+       "86533   ['1', '0', '0', '0', '0.933580426', '-0.358367...                1   \n",
+       "\n",
+       "       PhotometricInterpretation  Rows  Columns                  PixelSpacing  \\\n",
+       "9661                 MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "107285               MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "81787                MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "87951                MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "86533                MONOCHROME2   512      512  ['0.48828125', '0.48828125']   \n",
+       "\n",
+       "        BitsAllocated  BitsStored  HighBit  PixelRepresentation  \\\n",
+       "9661               16          12       11                    0   \n",
+       "107285             16          12       11                    0   \n",
+       "81787              16          12       11                    0   \n",
+       "87951              16          12       11                    0   \n",
+       "86533              16          12       11                    0   \n",
+       "\n",
+       "              WindowCenter         WindowWidth  RescaleIntercept  \\\n",
+       "9661    ['00040', '00040']  ['00080', '00080']           -1024.0   \n",
+       "107285  ['00040', '00040']  ['00080', '00080']           -1024.0   \n",
+       "81787   ['00040', '00040']  ['00080', '00080']           -1024.0   \n",
+       "87951   ['00040', '00040']  ['00080', '00080']           -1024.0   \n",
+       "86533   ['00040', '00040']  ['00080', '00080']           -1024.0   \n",
+       "\n",
+       "        RescaleSlope    PxlMin    PxlMax    PxlStd   PxlMean   test  test2  \\\n",
+       "9661             1.0  1.301333  0.126667 -0.761993  1.166719  False   True   \n",
+       "107285           1.0  1.301333  0.098667 -0.807341  1.049002  False   True   \n",
+       "81787            1.0  1.301333  0.086667 -0.789830  0.920645  False   True   \n",
+       "87951            1.0  1.301333  0.130667 -0.782852  0.978311  False   True   \n",
+       "86533            1.0  1.301333  0.124000 -0.788199  1.016346  False   True   \n",
+       "\n",
+       "        ImageOrientationPatient_0  ImageOrientationPatient_1  \\\n",
+       "9661                          1.0                        0.0   \n",
+       "107285                        1.0                        0.0   \n",
+       "81787                         1.0                        0.0   \n",
+       "87951                         1.0                        0.0   \n",
+       "86533                         1.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_2  ImageOrientationPatient_3  \\\n",
+       "9661                          0.0                        0.0   \n",
+       "107285                        0.0                        0.0   \n",
+       "81787                         0.0                        0.0   \n",
+       "87951                         0.0                        0.0   \n",
+       "86533                         0.0                        0.0   \n",
+       "\n",
+       "        ImageOrientationPatient_4  ImageOrientationPatient_5  \\\n",
+       "9661                     0.990268                  -0.139173   \n",
+       "107285                   0.933580                  -0.358368   \n",
+       "81787                    0.933580                  -0.358368   \n",
+       "87951                    0.933580                  -0.358368   \n",
+       "86533                    0.933580                  -0.358368   \n",
+       "\n",
+       "        ImagePositionPatient_0  ImagePositionPatient_1  \\\n",
+       "9661                    -125.0               24.416954   \n",
+       "107285                  -125.0               17.558639   \n",
+       "81787                   -125.0               17.558639   \n",
+       "87951                   -125.0               17.558639   \n",
+       "86533                   -125.0               17.558639   \n",
+       "\n",
+       "        ImagePositionPatient_2  PixelSpacing_0  PixelSpacing_1  \\\n",
+       "9661                204.228683        0.488281        0.488281   \n",
+       "107285              177.279488        0.488281        0.488281   \n",
+       "81787               193.305489        0.488281        0.488281   \n",
+       "87951               187.979561        0.488281        0.488281   \n",
+       "86533               182.605538        0.488281        0.488281   \n",
+       "\n",
+       "        WindowCenter_0  WindowCenter_1  WindowCenter_1_NAN  WindowWidth_0  \\\n",
+       "9661              40.0            40.0               False           80.0   \n",
+       "107285            40.0            40.0               False           80.0   \n",
+       "81787             40.0            40.0               False           80.0   \n",
+       "87951             40.0            40.0               False           80.0   \n",
+       "86533             40.0            40.0               False           80.0   \n",
+       "\n",
+       "        WindowWidth_1  WindowWidth_0_le  WindowWidth_1_le  WindowCenter_1_le  \\\n",
+       "9661             80.0                 0                 0                  1   \n",
+       "107285           80.0                 0                 0                  1   \n",
+       "81787            80.0                 0                 0                  1   \n",
+       "87951            80.0                 0                 0                  1   \n",
+       "86533            80.0                 0                 0                  1   \n",
+       "\n",
+       "        BitType_le  ImageOrientationPatient_4_f  \\\n",
+       "9661             1                     2.536908   \n",
+       "107285           1                     1.781072   \n",
+       "81787            1                     1.781072   \n",
+       "87951            1                     1.781072   \n",
+       "86533            1                     1.781072   \n",
+       "\n",
+       "        ImageOrientationPatient_4_enc_0  ...  ImageOrientationPatient_5_f  \\\n",
+       "9661                                0.0  ...                     2.405513   \n",
+       "107285                              0.0  ...                     0.944214   \n",
+       "81787                               0.0  ...                     0.944214   \n",
+       "87951                               0.0  ...                     0.944214   \n",
+       "86533                               0.0  ...                     0.944214   \n",
+       "\n",
+       "        ImageOrientationPatient_5_enc_0  ImageOrientationPatient_5_enc_1  \\\n",
+       "9661                                0.0                            False   \n",
+       "107285                              0.0                            False   \n",
+       "81787                               0.0                            False   \n",
+       "87951                               0.0                            False   \n",
+       "86533                               0.0                            False   \n",
+       "\n",
+       "        ImagePositionPatient_0_f  ImagePositionPatient_0_enc_0  \\\n",
+       "9661                       -0.72                           1.0   \n",
+       "107285                     -0.72                           1.0   \n",
+       "81787                      -0.72                           1.0   \n",
+       "87951                      -0.72                           1.0   \n",
+       "86533                      -0.72                           1.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_enc_1  ImagePositionPatient_0_f_r1  \\\n",
+       "9661                             0.0                          1.0   \n",
+       "107285                           0.0                          1.0   \n",
+       "81787                            0.0                          1.0   \n",
+       "87951                            0.0                          1.0   \n",
+       "86533                            0.0                          1.0   \n",
+       "\n",
+       "        ImagePositionPatient_0_f_r05  ImagePositionPatient_1_f  \\\n",
+       "9661                             1.0                  1.192226   \n",
+       "107285                           1.0                  1.100782   \n",
+       "81787                            1.0                  1.100782   \n",
+       "87951                            1.0                  1.100782   \n",
+       "86533                            1.0                  1.100782   \n",
+       "\n",
+       "        ImagePositionPatient_1_enc_0  ImagePositionPatient_2_f  \\\n",
+       "9661                             1.0                  0.053336   \n",
+       "107285                           1.0                  0.014727   \n",
+       "81787                            1.0                  0.037687   \n",
+       "87951                            1.0                  0.030057   \n",
+       "86533                            1.0                  0.022358   \n",
+       "\n",
+       "        ImagePositionPatient_2_f_r05  PixelSpacing_1_f  PixelSpacing_1_enc_0  \\\n",
+       "9661                             0.0             -0.48                   1.0   \n",
+       "107285                           0.0             -0.48                   1.0   \n",
+       "81787                            0.0             -0.48                   1.0   \n",
+       "87951                            0.0             -0.48                   1.0   \n",
+       "86533                            0.0             -0.48                   1.0   \n",
+       "\n",
+       "        PixelSpacing_1_enc_1  WindowCenter_0_le   pos_max   pos_min  pos_size  \\\n",
+       "9661                   False                  2  1.099715  0.473493      -0.3   \n",
+       "107285                 False                  2  1.051518  0.388022      -0.3   \n",
+       "81787                  False                  2  1.051518  0.388022      -0.3   \n",
+       "87951                  False                  2  1.051518  0.388022      -0.3   \n",
+       "86533                  False                  2  1.051518  0.388022      -0.3   \n",
+       "\n",
+       "        pos_idx1  pos_idx  pos_idx2  pos_inc1  pos_inc2  pos_inc1_grp_le  \\\n",
+       "9661    0.000000       17 -0.203390  1.527710  1.522339                3   \n",
+       "107285 -0.135593       15 -0.067797  1.687011  1.663025                3   \n",
+       "81787   0.067797       18 -0.271186  1.662964  1.687012                3   \n",
+       "87951   0.000000       17 -0.203390  1.687011  1.662964                3   \n",
+       "86533  -0.067797       16 -0.135593  1.663025  1.687011                3   \n",
+       "\n",
+       "        pos_inc2_grp_le  pos_inc1_r1  pos_inc1_r0001  pos_inc1_enc_0  \\\n",
+       "9661                  3          0.0             0.0             0.0   \n",
+       "107285                3          0.0             0.0             0.0   \n",
+       "81787                 3          0.0             0.0             0.0   \n",
+       "87951                 3          0.0             0.0             0.0   \n",
+       "86533                 3          0.0             0.0             0.0   \n",
+       "\n",
+       "        pos_inc2_enc_0  pos_inc1_enc_1  pos_inc2_enc_1  pos_size_le  \\\n",
+       "9661               0.0             0.0             0.0            0   \n",
+       "107285             0.0             0.0             0.0            0   \n",
+       "81787              0.0             0.0             0.0            0   \n",
+       "87951              0.0             0.0             0.0            0   \n",
+       "86533              0.0             0.0             0.0            0   \n",
+       "\n",
+       "        pos_range   pos_rel  pos_zeros  pos_inc_rng  pos_zeros_le  \\\n",
+       "9661    -0.225189  0.193609        0.0    -0.595692             0   \n",
+       "107285   0.023307 -0.064219        0.0    -0.581939             0   \n",
+       "81787    0.023307  0.322242        0.0    -0.581939             0   \n",
+       "87951    0.023307  0.193809        0.0    -0.581939             0   \n",
+       "86533    0.023307  0.064217        0.0    -0.581939             0   \n",
+       "\n",
+       "        PxlMin_grp_le  PxlMin_zero  any  epidural  intraparenchymal  \\\n",
+       "9661                2        False  NaN       NaN               NaN   \n",
+       "107285              2        False  NaN       NaN               NaN   \n",
+       "81787               2        False  NaN       NaN               NaN   \n",
+       "87951               2        False  NaN       NaN               NaN   \n",
+       "86533               2        False  NaN       NaN               NaN   \n",
+       "\n",
+       "        intraventricular  subarachnoid  subdural  any_series  SeriesPP  \\\n",
+       "9661                 NaN           NaN       NaN       False      -0.5   \n",
+       "107285               NaN           NaN       NaN       False      -0.5   \n",
+       "81787                NaN           NaN       NaN       False      -0.5   \n",
+       "87951                NaN           NaN       NaN       False      -0.5   \n",
+       "86533                NaN           NaN       NaN       False      -0.5   \n",
+       "\n",
+       "        yuval_idx  pred_any  \n",
+       "9661        49823  0.992338  \n",
+       "107285      74776  0.992465  \n",
+       "81787       74779  0.992568  \n",
+       "87951       74778  0.992820  \n",
+       "86533       74777  0.992826  \n",
+       "\n",
+       "[5 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_md['pred_any'] = predictions[:,5]\n",
+    "test_md.sort_values('pred_any').tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 121232, 6)"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_md['pred_any'] = preds[9,:,1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8297793f50>]"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(test_md[['pos_idx','pred_any']].groupby('pos_idx').mean())\n",
+    "plt.plot([0,60],[0,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8255ef9250>]"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(train_md[['pos_idx',all_ich[0]]].groupby('pos_idx').mean())\n",
+    "plt.plot([0,60],[0,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_md['pred_any'] = predictions[:,1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8255e69ad0>]"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(test_md[['pos_idx','pred_any']].groupby('pos_idx').mean())\n",
+    "plt.plot([0,60],[0,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 [9.30e-05 1.15e-04 1.49e-04 1.64e-03 9.96e-01 9.98e-01 9.99e-01]\n",
+      "1 [6.76e-06 8.61e-06 1.12e-05 7.63e-05 5.17e-02 3.93e-01 8.82e-01]\n",
+      "2 [2.12e-05 2.46e-05 3.09e-05 2.84e-04 9.83e-01 9.93e-01 9.95e-01]\n",
+      "3 [1.40e-05 1.65e-05 1.97e-05 8.68e-05 9.80e-01 9.93e-01 9.95e-01]\n",
+      "4 [2.81e-05 3.21e-05 4.08e-05 4.00e-04 9.59e-01 9.90e-01 9.92e-01]\n",
+      "5 [4.51e-05 5.60e-05 7.04e-05 8.55e-04 9.71e-01 9.89e-01 9.91e-01]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# weighted models + weighted ensembling\n",
+    "#0 [2.14e-04 2.50e-04 3.15e-04 2.15e-03 9.88e-01 9.93e-01 9.94e-01]\n",
+    "#1 [4.46e-06 5.32e-06 6.88e-06 8.58e-05 1.34e-01 6.16e-01 9.24e-01]\n",
+    "#2 [4.88e-05 5.54e-05 6.88e-05 3.27e-04 9.65e-01 9.86e-01 9.90e-01]\n",
+    "#3 [1.78e-05 2.00e-05 2.42e-05 1.04e-04 9.52e-01 9.77e-01 9.81e-01]\n",
+    "#4 [6.56e-05 7.67e-05 9.50e-05 4.71e-04 9.41e-01 9.85e-01 9.89e-01]\n",
+    "#5 [9.93e-05 1.21e-04 1.53e-04 9.91e-04 9.42e-01 9.86e-01 9.92e-01]\n",
+    "\n",
+    "# weighted models + non-weighted ensembling\n",
+    "#0 [9.25e-05 1.11e-04 1.41e-04 1.60e-03 9.93e-01 9.97e-01 9.99e-01]\n",
+    "#1 [8.16e-06 9.69e-06 1.24e-05 9.28e-05 1.31e-01 5.91e-01 8.94e-01]\n",
+    "#2 [2.38e-05 2.66e-05 3.46e-05 2.46e-04 9.73e-01 9.91e-01 9.94e-01]\n",
+    "#3 [1.25e-05 1.40e-05 1.71e-05 8.06e-05 9.66e-01 9.90e-01 9.94e-01]\n",
+    "#4 [3.27e-05 3.80e-05 4.71e-05 3.55e-04 9.51e-01 9.91e-01 9.94e-01]\n",
+    "#5 [4.51e-05 5.74e-05 7.40e-05 7.90e-04 9.46e-01 9.89e-01 9.94e-01]\n",
+    "\n",
+    "# non-weighted models + non-weighted ensembling\n",
+    "#0 [1.10e-04 1.24e-04 1.55e-04 1.27e-03 9.93e-01 9.97e-01 9.98e-01]\n",
+    "#1 [8.61e-06 9.98e-06 1.23e-05 8.77e-05 1.36e-01 5.73e-01 8.74e-01]\n",
+    "#2 [2.34e-05 2.66e-05 3.41e-05 2.12e-04 9.73e-01 9.91e-01 9.95e-01]\n",
+    "#3 [1.08e-05 1.25e-05 1.50e-05 6.10e-05 9.67e-01 9.92e-01 9.96e-01]\n",
+    "#4 [3.18e-05 3.68e-05 4.48e-05 3.03e-04 9.51e-01 9.91e-01 9.94e-01]\n",
+    "#5 [4.72e-05 5.48e-05 6.86e-05 6.83e-04 9.41e-01 9.88e-01 9.92e-01]\n",
+    "\n",
+    "# STAGE2 non-weighted models + non-weighted ensembling\n",
+    "#0 [9.30e-05 1.15e-04 1.49e-04 1.64e-03 9.96e-01 9.98e-01 9.99e-01]\n",
+    "#1 [6.76e-06 8.61e-06 1.12e-05 7.63e-05 5.17e-02 3.93e-01 8.82e-01]\n",
+    "#2 [2.12e-05 2.46e-05 3.09e-05 2.84e-04 9.83e-01 9.93e-01 9.95e-01]\n",
+    "#3 [1.40e-05 1.65e-05 1.97e-05 8.68e-05 9.80e-01 9.93e-01 9.95e-01]\n",
+    "#4 [2.81e-05 3.21e-05 4.08e-05 4.00e-04 9.59e-01 9.90e-01 9.92e-01]\n",
+    "#5 [4.51e-05 5.60e-05 7.04e-05 8.55e-04 9.71e-01 9.89e-01 9.91e-01]\n",
+    "\n",
+    "np.set_printoptions(precision=2)\n",
+    "for k in range(6):\n",
+    "    print(k,np.quantile(predictions[:,k],[0.0001,0.001,0.01,0.5,0.99,0.999,0.9999]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.1376, 0.0029, 0.0464, 0.0378, 0.0449, 0.0591])"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# weighted models + weighted ensembling\n",
+    "#array([0.1361, 0.0056, 0.0429, 0.0295, 0.0468, 0.0569])\n",
+    "\n",
+    "# weighted models + non-weighted ensembling\n",
+    "#array([0.1335, 0.0055, 0.0423, 0.0298, 0.0466, 0.0556])\n",
+    "\n",
+    "# non-weighted models + non-weighted ensembling\n",
+    "#array([0.1313, 0.0057, 0.0421, 0.0297, 0.0464, 0.0544])\n",
+    "\n",
+    "# STAGE2 non-weighted models + non-weighted ensembling\n",
+    "#array([0.1376, 0.0029, 0.0464, 0.0378, 0.0449, 0.0591])\n",
+    "\n",
+    "# STAGE2 weighted models + weighted ensembling\n",
+    "#array([0.1373, 0.0028, 0.0464, 0.0379, 0.045 , 0.0589])\n",
+    "\n",
+    "np.set_printoptions(precision=4)\n",
+    "predictions.mean(0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.13762015847552184"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sub.loc[range(0,len(sub),6), 'Label'].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sub = sub.sort_values('ID').reset_index(drop=True)\n",
+    "best_sub = pd.read_csv(PATH/'submission_stage2_3.csv').sort_values('ID').reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.13749181676694883"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "best_sub.loc[range(0,len(sub),6), 'Label'].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SpearmanrResult(correlation=0.985190415749868, pvalue=0.0)"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.stats.spearmanr(sub.loc[range(0,len(sub),6), 'Label'], \n",
+    "                   best_sub.loc[range(0,len(sub),6), 'Label'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SpearmanrResult(correlation=0.985190415749868, pvalue=0.0)"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.stats.spearmanr(sub.loc[range(0,len(sub),6), 'Label'], \n",
+    "                   best_sub.loc[range(0,len(sub),6), 'Label'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9992765979750622"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.corrcoef(sub.sort_values('ID').reset_index(drop=True).loc[range(0,len(sub),6), 'Label'], \n",
+    "            best_sub.sort_values('ID').reset_index(drop=True).loc[range(0,len(sub),6), 'Label'])[0,1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.999294961658725"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.corrcoef(sub.sort_values('ID').reset_index(drop=True).loc[range(0,len(sub),6), 'Label'], \n",
+    "            best_sub.sort_values('ID').reset_index(drop=True).loc[range(0,len(sub),6), 'Label'])[0,1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Submission"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████████████████████████████████| 32.1M/32.1M [00:02<00:00, 16.2MB/s]\n",
+      "Successfully submitted to RSNA Intracranial Hemorrhage Detection"
+     ]
+    }
+   ],
+   "source": [
+    "!~/.local/bin/kaggle competitions submit rsna-intracranial-hemorrhage-detection -f ~/Hemorrhage/sub.csv -m \"GCP, safe final, take 2\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!kaggle competitions submit rsna-intracranial-hemorrhage-detection -f C:/StudioProjects/Hemorrhage/sub.csv -m \"GCP, d161+d169+d201+s101+yd161, 8TTA, ensemble, bounds\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}