160 lines (159 with data), 4.9 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                  dataset        cutoff    algorithm    rank_auc   \n",
       " geis_250.00          :30   1 visit :210   LR :210   Min.   : 1.0  \n",
       " geis_250.00_cutoff182:30   1 year  :210   RF :210   1st Qu.: 8.0  \n",
       " geis_250.00_cutoff365:30   6 months:210   XGB:210   Median :15.5  \n",
       " geis_250.40          :30                            Mean   :15.5  \n",
       " geis_250.40_cutoff182:30                            3rd Qu.:23.0  \n",
       " geis_250.40_cutoff365:30                            Max.   :30.0  \n",
       " geis_327.23          :30                                          \n",
       " geis_327.23_cutoff182:30                                          \n",
       " geis_327.23_cutoff365:30                                          \n",
       " geis_331.0           :30                                          \n",
       " geis_331.0_cutoff182 :30                                          \n",
       " geis_331.0_cutoff365 :30                                          \n",
       " geis_530.81          :30                                          \n",
       " geis_530.81_cutoff182:30                                          \n",
       " geis_530.81_cutoff365:30                                          \n",
       " geis_571.8           :30                                          \n",
       " geis_571.8_cutoff182 :30                                          \n",
       " geis_571.8_cutoff365 :30                                          \n",
       " geis_585.9           :30                                          \n",
       " geis_585.9_cutoff182 :30                                          \n",
       " geis_585.9_cutoff365 :30                                          "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "setwd('/media/bill/Drive/projects/geis-ehr/analysis')\n",
    "\n",
    "df <- read.csv(\"auc_rankings.csv\",header=TRUE,sep=',')\n",
    "# df <- subset(df,!is.na(rank))\n",
    "# df <- subset(df,dataset!='505_tecator')\n",
    "# df <- subset(df,algorithm != 'LR')\n",
    "summary(df,maxsum=21)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "\tPairwise comparisons using Wilcoxon signed rank test \n",
       "\n",
       "data:  dfs$rank_auc and dfs$algorithm \n",
       "\n",
       "    LR      RF     \n",
       "RF  1.0e-12 -      \n",
       "XGB 1.1e-12 7.8e-12\n",
       "\n",
       "P value adjustment method: bonferroni "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs <- subset(df,cutoff=='1 visit')\n",
    "pairwise.wilcox.test(dfs$rank_auc, dfs$algorithm, p.adjust.method = 'bonferroni',\n",
    "                      paired = T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "\tPairwise comparisons using Wilcoxon signed rank test \n",
       "\n",
       "data:  dfs$rank_auc and dfs$algorithm \n",
       "\n",
       "    LR      RF     \n",
       "RF  1.0e-12 -      \n",
       "XGB 1.0e-12 2.3e-12\n",
       "\n",
       "P value adjustment method: bonferroni "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs <- subset(df,cutoff=='6 months')\n",
    "pairwise.wilcox.test(dfs$rank_auc, dfs$algorithm, p.adjust.method = 'bonferroni',\n",
    "                      paired = T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "\tPairwise comparisons using Wilcoxon signed rank test \n",
       "\n",
       "data:  dfs$rank_auc and dfs$algorithm \n",
       "\n",
       "    LR      RF     \n",
       "RF  1.0e-12 -      \n",
       "XGB 1.0e-12 9.5e-12\n",
       "\n",
       "P value adjustment method: bonferroni "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs <- subset(df,cutoff=='1 year')\n",
    "pairwise.wilcox.test(dfs$rank_auc, dfs$algorithm, p.adjust.method = 'bonferroni',\n",
    "                      paired = T)"
   ]
  }
 ],
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