--- a
+++ b/Notebook/Lung Cancer Prediction.ipynb
@@ -0,0 +1,1681 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "136d9e6c",
+   "metadata": {},
+   "source": [
+    "By :- Aditya Naranje"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "c4a367f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import warnings\n",
+    "warnings.filterwarnings(action=\"ignore\")\n",
+    "plt.style.use([\"seaborn-bright\",\"dark_background\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d7a21f85",
+   "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>GENDER</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>SMOKING</th>\n",
+       "      <th>YELLOW_FINGERS</th>\n",
+       "      <th>ANXIETY</th>\n",
+       "      <th>PEER_PRESSURE</th>\n",
+       "      <th>CHRONIC DISEASE</th>\n",
+       "      <th>FATIGUE</th>\n",
+       "      <th>ALLERGY</th>\n",
+       "      <th>WHEEZING</th>\n",
+       "      <th>ALCOHOL CONSUMING</th>\n",
+       "      <th>COUGHING</th>\n",
+       "      <th>SHORTNESS OF BREATH</th>\n",
+       "      <th>SWALLOWING DIFFICULTY</th>\n",
+       "      <th>CHEST PAIN</th>\n",
+       "      <th>LUNG_CANCER</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M</td>\n",
+       "      <td>69</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>YES</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>M</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>YES</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>F</td>\n",
+       "      <td>59</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NO</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>63</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NO</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>F</td>\n",
+       "      <td>63</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NO</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
+       "0      M   69        1               2        2              1   \n",
+       "1      M   74        2               1        1              1   \n",
+       "2      F   59        1               1        1              2   \n",
+       "3      M   63        2               2        2              1   \n",
+       "4      F   63        1               2        1              1   \n",
+       "\n",
+       "   CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  COUGHING  \\\n",
+       "0                1         2         1         2                  2         2   \n",
+       "1                2         2         2         1                  1         1   \n",
+       "2                1         2         1         2                  1         2   \n",
+       "3                1         1         1         1                  2         1   \n",
+       "4                1         1         1         2                  1         2   \n",
+       "\n",
+       "   SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN LUNG_CANCER  \n",
+       "0                    2                      2           2         YES  \n",
+       "1                    2                      2           2         YES  \n",
+       "2                    2                      1           2          NO  \n",
+       "3                    1                      2           2          NO  \n",
+       "4                    2                      1           1          NO  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = pd.read_csv(\"survey lung cancer.csv\")\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "364f3219",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(309, 16)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cf864668",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 309 entries, 0 to 308\n",
+      "Data columns (total 16 columns):\n",
+      " #   Column                 Non-Null Count  Dtype \n",
+      "---  ------                 --------------  ----- \n",
+      " 0   GENDER                 309 non-null    object\n",
+      " 1   AGE                    309 non-null    int64 \n",
+      " 2   SMOKING                309 non-null    int64 \n",
+      " 3   YELLOW_FINGERS         309 non-null    int64 \n",
+      " 4   ANXIETY                309 non-null    int64 \n",
+      " 5   PEER_PRESSURE          309 non-null    int64 \n",
+      " 6   CHRONIC DISEASE        309 non-null    int64 \n",
+      " 7   FATIGUE                309 non-null    int64 \n",
+      " 8   ALLERGY                309 non-null    int64 \n",
+      " 9   WHEEZING               309 non-null    int64 \n",
+      " 10  ALCOHOL CONSUMING      309 non-null    int64 \n",
+      " 11  COUGHING               309 non-null    int64 \n",
+      " 12  SHORTNESS OF BREATH    309 non-null    int64 \n",
+      " 13  SWALLOWING DIFFICULTY  309 non-null    int64 \n",
+      " 14  CHEST PAIN             309 non-null    int64 \n",
+      " 15  LUNG_CANCER            309 non-null    object\n",
+      "dtypes: int64(14), object(2)\n",
+      "memory usage: 38.8+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "8fc3dd31",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "GENDER                    2\n",
+       "AGE                      39\n",
+       "SMOKING                   2\n",
+       "YELLOW_FINGERS            2\n",
+       "ANXIETY                   2\n",
+       "PEER_PRESSURE             2\n",
+       "CHRONIC DISEASE           2\n",
+       "FATIGUE                   2\n",
+       "ALLERGY                   2\n",
+       "WHEEZING                  2\n",
+       "ALCOHOL CONSUMING         2\n",
+       "COUGHING                  2\n",
+       "SHORTNESS OF BREATH       2\n",
+       "SWALLOWING DIFFICULTY     2\n",
+       "CHEST PAIN                2\n",
+       "LUNG_CANCER               2\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.nunique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "67631f6f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data['GENDER'] = data['GENDER'].replace(['F','M'],[0,1])\n",
+    "data['LUNG_CANCER'] = data['LUNG_CANCER'].replace(['YES','NO'],[1,0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "54543586",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mapping = {1:0,\n",
+    "           2:1}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a2fea930",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "column = ['SMOKING', 'YELLOW_FINGERS', 'ANXIETY','PEER_PRESSURE', 'CHRONIC DISEASE', 'FATIGUE ',\n",
+    "          'ALLERGY ', 'WHEEZING','ALCOHOL CONSUMING', 'COUGHING', 'SHORTNESS OF BREATH','SWALLOWING DIFFICULTY', 'CHEST PAIN']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "23be48f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in column:\n",
+    "    data[i] = data[i].map(mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "24316b73",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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zGAzw8vJqc4zo6GgsWbIEAKBSqaRrICK6Fx2G5rp167Bu3TosW7YM69evt1gRP4Xxzwkh2pxXo9FAo9EAAHQ6ncVqIiJqS4eh+ZP169fjiSeewODBg9Gr1/8vsnXrVqmVlZeXw8PDA2VlZfDw8EBFRQWAlj1LHx8fZT5vb2/cvHlTamwiImsw62rLli1bsHbtWkyYMAFqtRpqtRpjxoyRXtmhQ4cQGRkJAIiMjMTBgweV/oiICPTu3RuDBw/GsGHDcP78eenxiYgszaw9zTFjxmDkyJFSA6ekpGDy5MlQqVQoLS1FbGwsPvzwQ6SmpuKFF17A9evXMX/+fABAbm4uUlNTkZubi8bGRrz66qtobm6W3xoiIgszKzRzcnKUw2pzLVy4sM3+6dOnt9kfFxeHuLg4s8cnIrIFs0JTpVIhNzcX58+fxw8//KD0h4WFWawwIqLuyKzQfO+99yxcBhFRz2BWaH7xxReWroOIqEcwKzRv376t3DfZu3dvODo6oq6uDn379rVocURE3Y1ZofnrX//a5H1YWBgfcySiX6ROfSvGwYMHMXXq1K6uhYio2zNrT3P27NnKa3t7e4wZM6bdxxyJiO5nZoXm008/rbxubGxESUkJbzciol8ks0IzKirK0nUQEfUIZp3T9PLywr59+1BeXo6ysjLs2bOn3a9uIyK6n5kVmklJSTh06BAeeugheHl54fDhw0hKSrJ0bURE3Y5ZoTlgwAAkJyejqakJTU1N2Lx5MwYMGGDp2oiIuh2zQrOyshLPPfcc7O3tYW9vj+eeew7ffvutpWsjIup2zArNqKgohIeHo6ysDEajEfPmzcPixYstXRsRUbdj1tXz1atXIzIyEt999x2Alp/iXbt2LV544QVL1kZE1O2Ytaf56KOPKoEJANXV1QgKCrJUTURE3ZZZoWlvbw9XV1flvZubm8lvBRER/VKYlXzx8fH48ssvsWfPHgghEB4ejg8++MDStRERdTtmhebWrVtx4cIFTJ06FXZ2dpgzZw7y8vIsXRsRUbdj9jF2Xl4eg5KIfvGsfmLS398fu3btUt4//PDDePfdd+Hq6oro6GjcunULALBq1SocOXLE2uUREXXI6qFZUFCgXHm3t7fHjRs3sH//fixevBgJCQmIj4+3dklERGbr1JcQd5Vp06bh2rVruH79ui3LICIym01DMyIiAjt27FDeL1u2DJcuXUJiYqLJLU5ERN2FzULT0dERzzzzDHbv3g0A2LhxI/z8/BAYGAij0djuYXp0dDR0Oh10Oh1UKpU1SyYisl1ohoaGIisrCxUVFQCAiooKNDc3QwgBjUbT7g+3aTQaqNVqqNVqVFZWWrNkIiLbheaCBQtMDs09PDyU17Nnz0ZOTo4tyiIi6pBNnoXs06cPZsyYgaVLlyp9a9asQWBgIIQQKCkpMZlGRNRd2CQ079y50+p85KJFi2xRChGRFJtePSci6mkYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSbPJrlMXFxaipqUFTUxMaGxuhVqvh5uaGXbt2YfDgwSgpKUF4eDi+++47W5RHRNQum+1pTpkyBUFBQVCr1QCAmJgYZGRkwN/fHxkZGYiJibFVaURE7eo2h+dhYWHYvHkzAGDz5s2YNWuWbQsiImqDTUJTCIGjR4/iwoULiI6OBgC4u7ujrKwMAFBWVoaBAwe2uWx0dDR0Oh10Oh1UKpXVaiYiAmx0TnP8+PEwGo0YMGAA0tPTkZ+fb/ayGo0GGo0GAKDT6SxVIhFRm2yyp2k0GgEAt27dwv79+xEcHIzy8nJ4eHgAADw8PFBRUWGL0oiIOmT10HR2doaLi4vyeubMmcjJycGhQ4cQGRkJAIiMjMTBgwetXRoR0V1Z/fDc3d0d+/fvb1l5r15ISUlBWloadDodUlNT8cILL+D69euYP3++tUsjIrorq4dmcXExAgMDW/VXVVVh+vTp1i6HiEhKt7nliIioJ2BoEhFJYGgSEUlgaBIRSWBoEhFJYGgSEUlgaBIRSWBoEhFJYGgSEUlgaBIRSWBoEhFJYGgSEUlgaBIRSWBoEhFJYGgSEUlgaBIRSWBoEhFJYGgSEUlgaBIRSWBoEhFJsHpoent74/jx48jNzUVOTg7+8Ic/AABiY2NhMBig1+uh1+sRGhpq7dKIiO7K6r9G2djYiDfffBN6vR4uLi64ePEi0tPTAQAJCQmIj4+3dklERGazemiWlZWhrKwMAFBbW4u8vDx4eXlZuwwiok6x6TlNX19fBAUF4dy5cwCAZcuW4dKlS0hMTISrq2uby0RHR0On00Gn00GlUlmxWiIiG4bmgw8+iL1792L58uWoqanBxo0b4efnh8DAQBiNxnYP0zUaDdRqNdRqNSorK61cNRH90tkkNHv16oW9e/di+/bt2L9/PwCgoqICzc3NEEJAo9EgODjYFqUREXXIJqGZmJiIvLw8JCQkKH0eHh7K69mzZyMnJ8cWpRERdcjqF4LGjx+PRYsW4euvv4ZerwcArFq1CgsWLEBgYCCEECgpKcHSpUutXRoR0V1ZPTTPnDkDOzu7Vv1HjhyxdilERNL4RBARkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZEEhiYRkQSGJhGRBIYmEZGEbheaTz31FPLz83H16lWsXLnS1uUQEZnoVqFpb2+Pjz/+GKGhoRg5ciQWLFiAESNG2LosIiJFtwrN4OBgFBYWori4GD/++CN27tyJsLAwW5dFRKToZesCfs7LywulpaXKe4PBgLFjx5rMEx0djSVLlgAAhg8fDp1OZ9UaewKVSoXKykpbl2Ex1v43z71s1dVZ3f3899LZvxVfX992p3Wr0LSzs2vVJ4Qwea/RaKDRaKxVUo+k0+mgVqttXQb1EPx7kdOtDs8NBgN8fHyU997e3rh586YNKyIiMtWtQlOn02HYsGEYPHgwHB0dERERgUOHDtm6LCIiRbc6PG9qasKyZcuQlpYGBwcHfPrpp8jNzbV1WT3Opk2bbF0C9SD8e5FjB0DcdS4iIgLQzQ7PiYi6O4YmEZEEhuZ9ho+hkrkSExNRXl6O7OxsW5fS4wi2+6PZ29uLwsJCMWTIEOHo6Ci++uorMWLECJvXxdY928SJE0VQUJDIzs62eS09qXFP8z7Cx1BJhlarRVVVla3L6HEYmveRth5D9fLysmFFRPcfhuZ9xJzHUIno3jA07yN8DJXI8hia9xE+hkpkHTa/GsXWdS00NFRcuXJFFBYWilWrVtm8Hrbu21JSUsTNmzdFQ0ODKC0tFVFRUTavqSc0PkZJRCSBh+dERBIYmkREEhiaREQSGJpERBIYmkREEhiaREQSGJrUaVqtFiEhIcr7+fPn48iRI2hsbIRer1faT19Rd+LECTz++OMmYzz55JM4fPhwq7FHjhyJjIwMXLlyBQUFBXjnnXeUabdu3YKrqysAwMPDA0IIjB8/XpleUVGBfv36tVlzbGwsDAaDUttf//rXVrUVFxdjz549yjJz585FUlKS8v6pp57CuXPnkJeXB71ej507dypPYiUlJaGoqEgZ/8yZMwCAyMhIVFRUQK/XIy8vD8uXL1fG8/f3x4kTJ6DX65Gbm4tPPvmknU+cugub3yzK1jNbQECAyM3NFU5OTsLZ2VkUFBSIhx9+WNTU1LQ5/4kTJ8Tjjz9u0vfkk0+Kw4cPm/Q98MADorCwUMyYMUMAEH369BGfffaZeOWVVwQA8e9//1uEhoYKAGLOnDni4sWLYsWKFQKA8Pf3F7m5ue3WHBsbK958880OaysuLhYlJSVi5MiRAoCYO3euSEpKUra5oKBAPPLII8qyTz/9tJg4caIAIJKSksTcuXNbjR8ZGSn++c9/CgCiX79+4tatW8Lb21sAEJ9//rl45plnlHlHjRpl839btvYb9zSp0y5fvozDhw9j5cqViI2NxZYtW1BUVHTP4y5cuBBnzpxBeno6AODOnTtYtmwZYmJiAABnzpzBuHHjAADjxo3D3//+dzzxxBPK+y+//PKea1i7di1WrVrVqn/lypWIi4tDfn6+0nf48GFotVqzx66qqkJhYSE8PT0BAJ6enjAYDMr0nJyce6icLI2hSffkL3/5CxYuXIjQ0FCsWbMGANCnTx+Tw/Pw8HCpMQMCAnDx4kWTvqKiIri4uOBXv/oVvvzySyU0g4ODceDAAeXweNy4ccohcXv++Mc/KrXNnDmzzXlSU1MxevRo+Pn5taotKyurw/E/+ugjZfxt27a1mu7j44MHHngAX3/9NQAgISEBx48fx2effYbly5ejb9++HY5PttWtfsKXep76+nrs2rULtbW1aGhoANCyZxgUFNTpMe3s7Nr9SjshBM6fP4+goCA4OzvD0dERdXV1KCoqgp+fH8aNG4f4+PgOx09ISLjrPE1NTfjoo4/w9ttv48iRI23O069fP2RkZMDZ2RmbNm1SxlyxYgX27t3bav5nn30WU6ZMwfDhwxEdHY0ffvgBAJCcnIy0tDSEhIQgLCwMS5cuxWOPPaZ8ntS9cE+T7llzczOam5u7bLzLly9jzJgxJn1DhgxBbW0tamtrcefOHRQWFiIqKkrZ68vMzMRvf/tbDBw4EFeuXOmSOrZu3YpJkyZh0KBBJrWNHj0aQMthdlBQEDZt2gQXF5e7jrdr1y6MGjUKEydORHx8PNzd3ZVpRqMRSUlJmDVrFhobGzFq1Kgu2QbqegxN6na2b9+OCRMmYNq0aQCABx54AOvWrVMO/4GW85rLly/H2bNnAQBnz57F66+/jszMzC6ro7GxEQkJCSZXutesWYM///nPeOSRR5Q+Z2dnqXEzMzOxdetWvP766wBarsb36tVy0Ofu7o7+/fvjxo0b974BZBEMTepy/3tO86fbegDgP//5D0pLS1FaWorU1FQAwLRp05S+0tJSBAYGIiwsDO+88w7y8/ORnZ0NnU6H9evXK+OcOXMGfn5+SmhmZWXB29u7Sy4C/VxiYqISaEDLRZrXX38dW7ZsQV5eHk6fPo0RI0YgJSVFmefn5zT1ej0cHR1bjfu3v/0NixcvhouLC2bOnImcnBx89dVXSEtLw4oVK1BeXt6l20Fdh18NR0QkgXuaREQSePWc7kurVq3C/PnzTfp2796NuLg4G1VE9wsenhMRSeDhORGRBIYmEZEEhiYRkQSGJhGRhP8Dd8t/n8ZsgzQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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e3ul0yul0SpLcbnefagCAvgooNO+44w7/nzs7O9XY2Njn043S09N1+PBhtbW1SZJ27typH/7wh/L5fIqPj5fX61V8fLxaW1v7tH8ACKaAQnPhwoUXbMCjR49q8uTJGjRokL788kvNmDFD7733nk6dOiWHw6EnnnhCDodDpaWlF2xMALhQAvpO02azaefOnfL5fPJ6vdq+fbtsNlufBqyqqtL27dtVXV2tmpoaWSwWbd68Wfn5+Zo5c6bq6uo0c+ZM5efn92n/ABBMAc00CwsLVVRUpNmzZ0uS7r33XhUWFmrWrFl9GvTRRx8964T59vZ2paen92l/ABAqAc00hw8fri1btqirq0tdXV1yuVwaPnx4sGsDgIgTUGi2tbVp/vz5slgsslgsmj9/vk6cOBHs2gAg4gQUmgsXLtScOXPk9Xp17Ngx3XPPPbr//vuDXRsARJyAvtN87LHH5HA4/NeCx8bG6umnn9aiRYuCWRsARJyAZprjxo3rcfOMjz/+WOPHjw9WTQAQsQIKTYvFomHDhvlfx8bG9nhWEABcKgJKvj/+8Y/65z//qe3bt8swDM2ZM0ePP/54sGsDgIgTUGhu3bpV7733nqZPn66oqCjdfffdqq2tDXZtABBxAj7Grq2tJSgBXPL6dGs4ALhUEZoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYEJYQnPo0KF65ZVXVFtbK4/Ho8mTJys2Nlbl5eWqq6tTeXl5j2vdASBShCU0169fr9dee02pqam68cYbVVtbq9zcXFVUVCglJUUVFRXKzc0NR2kAcE4hD80rr7xSN998swoKCiRJp0+f1smTJ5WZmSmXyyVJcrlcysrKCnVpAHBeIQ/Na6+9VsePH1dhYaGqq6vldDo1ePBgjRgxQl6vV5Lk9XoVFxcX6tIA4LxCHprR0dGaMGGCnnvuOU2YMEGnTp0ydSiek5Mjt9stt9stq9UaxEoB4GwhD83m5mY1NzerqqpKkrR9+3ZNmDBBPp9P8fHxkqT4+Hi1trb2ur3T6ZTdbpfdbldbW1vI6gYAKQyh6fP51NTUpJSUFEnSjBkz5PF4VFZWJofDIUlyOBwqLS0NdWkAcF5heWbFr371K23btk0xMTH66KOPdP/998tisaikpESLFi3S0aNHNXv27HCUBgDnFJbQ3L9/v+x2+1n96enpYagGAALHFUEAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmEJoAYAKhCQAmhC00LRaLqqur9de//lWSFBsbq/LyctXV1am8vFzDhg0LV2kA8K3CFpq//vWvVVtb63+dm5uriooKpaSkqKKiwtSz0AEgVMISmjabTbfddpuef/55f19mZqZcLpckyeVyKSsrKxylAcA5hSU0161bp5UrV6q7u9vfN2LECHm9XkmS1+tVXFxcr9vm5OTI7XbL7XbLarWGpF4A+J+Qh+Ztt92m1tZWVVdX92l7p9Mpu90uu92utra2C1wdAJxbyJ97PmXKFN1555366U9/qssvv1xDhgzR1q1b5fP5FB8fL6/Xq/j4eLW2toa6NAA4r5DPNFevXq2RI0cqOTlZ2dnZeuONN3TfffeprKxMDodDkuRwOFRaWhrq0gDgvCLmPM38/HzNnDlTdXV1mjlzpvLz88NdEgCcJeSH51+3d+9e7d27V5LU3t6u9PT0cJYDAOcVMTNNAOgPCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMIHQBAATCE0AMCHkoZmQkKA33nhDHo9HBw4c0IMPPihJio2NVXl5uerq6lReXq5hw4aFujQAOK+Qh2ZnZ6dWrFih66+/XpMnT9bSpUuVmpqq3NxcVVRUKCUlRRUVFcrNzQ11aQBwXiEPTa/Xq3379kmSPv/8c9XW1spmsykzM1Mul0uS5HK5lJWVFerSAOC8wvo0ysTERI0fP17vvvuuRowYIa/XK+lMsMbFxfW6TU5OjhYvXixJslqtIasVAKQw/hB0xRVXaMeOHVq+fLk+++yzgLdzOp2y2+2y2+1qa2sLYoUAcLawhGZ0dLR27Nihbdu26dVXX5Uk+Xw+xcfHS5Li4+PV2toajtIA4JzCEpoFBQWqra3V2rVr/X1lZWVyOBySJIfDodLS0nCUBgDnFPLvNKdMmaIFCxbogw8+8P8gtHr1auXn56ukpESLFi3S0aNHNXv27FCXBgDnFfLQ/Mc//qGoqKhel6Wnp4e4GgAwhyuCAMAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATIi40Lzlllt06NAh1dfXa9WqVeEuBwB6iKjQtFgs2rhxo2699VZdf/31mjt3rlJTU8NdFgD4RVRopqWlqaGhQYcPH9bp06dVXFyszMzMcJcFAH4hfxrludhsNjU1NflfNzc36wc/+EGPdXJycrR48WJJ0pgxY+R2u0NaY39gtVrV1tYW7jKCJtT/zz0HQzpcyF3Mn5e+flYSExO/dVlEhWZvj/Y1DKPHa6fTKafTGaqS+iW32y273R7uMtBP8HkxJ6IOz5ubmzVy5Ej/64SEBLW0tISxIgDoKaJC0+12a/To0UpKStJll12m7OxslZWVhbssAPCLqMPzrq4uLVu2TLt27dKAAQP0wgsvyOPxhLusfmfz5s3hLgH9CJ8Xc6IkGeddCwAgKcIOzwEg0hGaAGACoXmR4TJUBKqgoEA+n081NTXhLqXfMWgXR7NYLEZDQ4ORnJxsXHbZZcb7779vpKamhr0uWmS2qVOnGuPHjzdqamrCXkt/asw0LyJchgozKisr1d7eHu4y+h1C8yLS22WoNpstjBUBFx9C8yISyGWoAL4bQvMiwmWoQPARmhcRLkMFQiPsv0bRLly79dZbjQ8//NBoaGgwVq9eHfZ6aJHbioqKjJaWFqOjo8NoamoyFi5cGPaa+kPjMkoAMIHDcwAwgdAEABMITQAwgdAEABMITQAwgdBERMvKypJhGBozZoykM08JNAxDy5Yt86/z7LPPyuFwSJJKS0t17733+pdt3rxZDz30kCRpz549mjhxoiTp8OHD+uCDD7Rv3z7t27dP69ev14YNG7Rv3z4dPHhQX3zxhX/Zww8/rOLiYv8+r7zySjU0NCgpKSnYbx8RKuznPdFo39Zefvll46233jLWrFljSDISExMNr9dr1NfXG5dddpkhyXj22WcNh8PhX/7RRx8ZQ4cONW666SZj//79RnR0tCHJ2LNnjzFx4kRDknH48GHjqquu6nXMxMTEs+788/bbbxszZswwJBlr167lHNhLuDHTRMS64oorNGXKFC1atEjZ2dn+/uPHj6uiosI/u/y6I0eOaPPmzXryySe1adMmLVu2TJ2dnd+5liVLlmjdunWaOHGiZsyYoaeeeuo77xP9E6GJiJWVlaXXXntN9fX1am9v1/jx4/3L8vPztWLFClksZ3+En376aWVkZOjgwYOqrKz81v3v2bPHfwi+fPnyc9ZSU1OjXbt2qaKiQg8++KBOnz7d5/eF/i2inkYJfN3cuXO1bt06SVJxcbHmzp2rjRs3SpIaGxtVVVWlefPmnbXduHHjFBUVpeuuu05RUVHfeqenn/zkJzpx4kTA9WzcuFG33nqr3nzzTdPvBRcPZpqISN/73vc0ffp0Pf/88zp8+LAefvhh/fznP+9x+7u8vDytWrWqx2wzKipKmzZt0n333af6+notWbLkgtXU3d2t7u7uC7Y/9E+EJiLSPffcoxdffFFJSUlKTk7WNddco8OHDyshIcG/zocffiiPx6Pbb7/d3/fAAw+ovr5ee/fu1W9+8xutXLlSVqs1HG8BFylCExFp7ty5evXVV3v07dixQ6tXr+7R9/jjj/uDdPjw4Vq1apX/FKNjx45p/fr1evLJJ3sd4+vfabpcriC8C1yMuMsRAJjATBMATCA0AcAEQhMATCA0AcAEQhMATCA0AcAEQhMATPg/++nG0bKVx6AAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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AoUlEJIHdQjM1NRU1NTUoKioS27y9vZGdnY3y8nJkZ2fDy8tLnKfRaHDs2DGUlpZi7Nix9iqLiOim2C00t2zZgpiYGIs2jUaDnJwchISEICcnBxqNBgAQGhqKuLg4DBw4EDExMdiwYQNkMm4EE1HnY7dkOnDgAOrr6y3aVCoVtFotAECr1WLChAli+7Zt29DY2IhTp06hoqICERER9iqNiKjDHLo55+vrC6PRCAAwGo3w8fEBACgUClRWVor9DAYDFAqF1TESExOh0+mg0+kgl8vtXzQR0e90in1gFxeXVm2CYP3JwikpKVAqlVAqlTCZTPYujYjIgkNDs6amBn5+fgAAPz8/1NbWAri+Zdm3b1+xn7+/P6qqqhxZGhGRTRwamllZWVCr1QAAtVqN3bt3i+1xcXFwc3NDYGAggoODkZeX58jSiIhs4mqvgdPT0zFq1CjI5XJUVlYiKSkJycnJyMjIQEJCAs6cOYPY2FgAgF6vR0ZGBvR6PZqamjB79my0tLTYqzQiog6zW2hOnTrVantUVJTV9lWrVmHVqlX2KoeI6JboFCeCiIhuFwxNIiIJGJpERBIwNImIJGBoEhFJwNAkIpKAoUlEJIFNobl3716b2oiI7nRt/ri9W7ducHd3h1wuh5eXl3hjjV69eqFPnz4OKZCIqDNpMzRfeuklLFiwAH369MHPP/8shubFixexfv16hxRIRNSZtBma69atw7p16zBnzhx89NFHjqqJiKjTsuna848++gjDhg1DYGAgXF3/b5G0tDS7FUZE1BnZFJqffvop+vXrh8LCQjQ3NwO4fpNghiYR/dnYFJrh4eEYMGCAvWshIur0bPrJUXFxsXjHdSKiPzObtjTlcjn0ej3y8vLw66+/iu0qlcpuhRERdUY2hebKlSvtXAYR0e3BptD87rvvbulKFyxYgBdffBGCIKCoqAgzZsyAu7s7tm/fjsDAQJw6dQqTJ0/G+fPnb+l6iYhulk3HNC9evIgLFy7gwoULaGhoQFNTEy5cuNChFfbp0wfz5s1DeHg4HnzwQXTp0gVxcXHQaDTIyclBSEgIcnJyoNFoOjQ+EZE92RSavXr1gqenJzw9PdGjRw9MmjTppn7s7urqih49eqBLly5wd3dHVVUVVCoVtFotAECr1WLChAkdHp+IyF46dJej3bt3Y/To0R1aYVVVFd5//32cOXMG1dXVuHDhAvbs2QNfX18YjUYAgNFohI+PT4fGJyKyJ5uOaU6cOFH8WyaTITw8HIIgdGiFXl5eUKlUCAoKwvnz57Fjxw7Ex8fbvHxiYiJmzZoF4PpZfSIiR7IpNJ955hnx76amJpw6darDPzeKiorCyZMnYTKZAACZmZl49NFHUVNTAz8/PxiNRvj5+aG2ttbq8ikpKUhJSQEA6HS6DtVARNRRNoXmzJkzb9kKz5w5g8jISPTo0QMNDQ0YM2YMDh06hMuXL0OtVuPdd9+FWq3G7t27b9k6iYhuFZuOaSoUCmRmZqKmpgZGoxE7d+6EQqHo0Arz8vKwc+dO5Ofno6ioCDKZDBs3bkRycjKio6NRXl6O6OhoJCcnd2h8IiJ7smlLc/PmzUhPT0dsbCwA4K9//Ss2b96MsWPHdmilK1eubPWD+fr6ekRFRXVoPCIiR7FpS/Puu+/Gli1b0NzcjObmZmi1Wtx99932ro2IqNOxKTRNJhPi4+Mhk8kgk8kQHx+Puro6e9dGRNTp2BSaM2fOxOTJk2E0GlFdXY3nnnsOM2bMsHdtRESdjk3HNN966y2o1WrxWnBvb2+8//77SEhIsGdtRESdjk1bmg899JDFzTPOnTuHIUOG2KsmIqJOy6bQlMlk8PLyEl97e3tbPCuIiOjPwqbk++CDD/C///0PO3fuhCAImDx5Mt5++21710ZE1OnYFJppaWk4dOgQRo8eDRcXFzz77LMoKSmxd21ERJ2OzfvYJSUlDEoi+tPr0K3hiIj+rBiaREQSMDSJiCRgaBIRScDQJCKSgKFJRCQBQ5OISAKGJhGRBAxNIiIJnBKanp6e2LFjB0pKSqDX6xEZGQlvb29kZ2ejvLwc2dnZFjcIISLqLJwSmh9++CG+/vprhIaGYvDgwSgpKYFGo0FOTg5CQkKQk5MDjUbjjNKIiNrk8ND08PDAiBEjkJqaCgC4du0aLly4AJVKBa1WCwDQarWYMGGCo0sjImqXw0Pzvvvuw9mzZ7F582bk5+cjJSUF7u7u8PX1hdFoBAAYjUb4+PhYXT4xMRE6nQ46nQ5yudyRpRMROT40XV1dERYWho8//hhhYWG4fPmypF3xlJQUKJVKKJVKmEwmO1ZKRNSaw0PTYDDAYDAgLy8PALBz506EhYWhpqYGfn5+AAA/Pz/U1tY6ujQionY5PDRrampQWVmJkJAQAMCYMWOg1+uRlZUFtVoNAFCr1di9e7ejSyMiapdTHvQzd+5cbN26FW5ubjhx4gRmzJgBmUyGjIwMJCQk4MyZM4iNjXVGaUREbXJKaB4+fBhKpbJVe1RUlBOqISKyHa8IIiKSgKFJRCQBQ5OISAKGJhGRBAxNIiIJGJpERBIwNImIJGBoEhFJwNAkIpKAoUlEJAFDk4hIAoYmEZEEDE0iIgkYmkREEjA0iYgkYGgSEUnA0CQikoChSUQkgdNCUyaTIT8/H//+978BAN7e3sjOzkZ5eTmys7Ph5eXlrNKIiG7IaaE5f/58lJSUiK81Gg1ycnIQEhKCnJwcSc9CJyJyFKeEpkKhwFNPPYV//etfYptKpYJWqwUAaLVaTJgwwRmlERG1ySmhuXbtWixZsgQtLS1im6+vL4xGIwDAaDTCx8fH6rKJiYnQ6XTQ6XSQy+UOqZeI6DcOD82nnnoKtbW1yM/P79DyKSkpUCqVUCqVMJlMt7g6IqK2Ofy554899hjGjx+PJ598Et27d0evXr2QlpaGmpoa+Pn5wWg0ws/PD7W1tY4ujYioXQ7f0ly+fDn69u2LoKAgxMXFYd++fZg2bRqysrKgVqsBAGq1Grt373Z0aURE7eo0v9NMTk5GdHQ0ysvLER0djeTkZGeXRETUisN3z39v//792L9/PwCgvr4eUVFRziyHiKhdnWZLk4jodsDQJCKSgKFJRCQBQ5OISAKGJhGRBAxNIiIJGJpERBIwNImIJGBoEhFJwNAkIpKAoUlEJAFDk4hIAoYmEZEEDE0iIgkYmkREEjA0iYgkYGgSEUng8ND09/fHvn37oNfrUVxcjHnz5gEAvL29kZ2djfLycmRnZ8PLy8vRpRERtcvhodnU1IRFixZhwIABiIyMxOzZsxEaGgqNRoOcnByEhIQgJycHGo3G0aUREbXL4aFpNBpRUFAAALh06RJKSkqgUCigUqmg1WoBAFqtFhMmTHB0aURE7XLqg9UCAgIwZMgQ/PTTT/D19YXRaARwPVh9fHysLpOYmIhZs2YBAORyucNqJSICnHgi6K677sKuXbuwYMECmM1mm5dLSUmBUqmEUqmEyWSyY4VERK05JTRdXV2xa9cubN26FZ9//jkAoKamBn5+fgAAPz8/1NbWOqM0IqI2OSU0U1NTUVJSgjVr1ohtWVlZUKvVAAC1Wo3du3c7ozQiojY5/JjmY489hunTp+PIkSPiCaHly5cjOTkZGRkZSEhIwJkzZxAbG+vo0oiI2uXw0Pzhhx/g4uJidV5UVJSDqyEikoZXBBERScDQJCKSgKFJRCQBQ5OISAKGJhGRBAxNIiIJGJpERBIwNImIJGBoEhFJwNAkIpKAoUlEJAFDk4hIAoYmEZEEDE0iIgkYmkREEjA0iYgkYGgSEUnA0CQikqDTheYTTzyB0tJSHDt2DEuXLnV2OUREFjpVaMpkMqxfvx7jxo3DgAEDMGXKFISGhjq7LCIiUacKzYiICFRUVODkyZO4du0atm3bBpVK5eyyiIhEDn8aZVsUCgUqKyvF1waDAY888ohFn8TERMyaNQsAcP/990On0zm0xtuBXC6HyWRydhl24+j/uf6oQ1fncHfy96Wj35WAgIAbzutUoWnt0b6CIFi8TklJQUpKiqNKui3pdDoolUpnl0G3CX5fpOlUu+cGgwF9+/YVX/v7+6OqqsqJFRERWepUoanT6RAcHIzAwEB07doVcXFxyMrKcnZZRESiTrV73tzcjDlz5uCbb75Bly5dsGnTJuj1emeXddvZuHGjs0ug2wi/L9K4ABDa7UVERAA62e45EVFnx9AkIpKAoXmH4WWoZKvU1FTU1NSgqKjI2aXcdgROd8Ykk8mEiooKISgoSOjatatQWFgohIaGOr0uTp1zGj58uDBkyBChqKjI6bXcThO3NO8gvAyVpDhw4ADq6+udXcZth6F5B7F2GapCoXBiRUR3HobmHcSWy1CJ6OYwNO8gvAyVyP4YmncQXoZK5BhOPxvF6dZN48aNE8rKyoSKigph+fLlTq+HU+ed0tPThaqqKqGxsVGorKwUZs6c6fSaboeJl1ESEUnA3XMiIgkYmkREEjA0iYgkYGgSEUnA0CQikoChSR3i6+uLzz77DBUVFTh69Cj+85//IDg4GAEBAa3umpOUlIRFixYBADZv3owTJ06goKAAhYWFGD16tNiva9euWLNmDSoqKlBeXo4vvvjC4jJQQRDw/vvvi68XLVqEpKSkVuv4bV5JSQmKiopQWFiIadOmtXoPv9VSWFiIsrIyaLVa9OnTR5x/8uRJ9O7dGwCwfPlyFBcX4/DhwygoKEBERAQAIDc3F6WlpSgoKEBBQQF27NhhsY7CwkKkp6dbtD3yyCM4ePAgCgoKoNfrxfegVqtRW1srjlVQUIDQ0ND2/hXkYJ3qcRd0+/j888+h1WoxZcoUAMDgwYPh6+trce37jSxevBi7du3CqFGjsHHjRoSEhAAAVq1aBQ8PD4SEhKClpQUvvPACMjMzxcc4X716Fc8++yzeeecd1NXV3XD8l156CdHR0YiIiIDZbEavXr0wYcKENmsBgAULFiA3NxeDBg3CtWvXxD6RkZF4+umnERYWhsbGRvTu3Rtubm7i/Pj4ePz888+txn7ggQcgk8kwYsQIuLu748qVKwAArVaLyZMn48iRI5DJZLj//vvFZbZv3465c+e2+xmS83BLkyR7/PHHce3aNfzzn/8U2w4fPozvv/9e0jg//vijuCXZo0cPzJgxAwsXLkRLSwsAYMuWLfj111/FrdGmpiZs3LgRCxcubHPc5cuX49VXX4XZbAYAXLx4EZ9++mm79axduxZGoxHjxo2zaL/nnntgMpnQ2NgIAKirq0N1dXW7402dOhVpaWnIzs7G+PHjxXYfHx9x+ZaWFpSUlLQ7FnUeDE2SbNCgQVa3rH7Tr18/i13Ml19+2Wq/mJgYfPHFFwCA/v3748yZM2LQ/ebQoUMYOHCg+Hr9+vWIj49Hr169rI7Zs2dPeHh44MSJExLf1XX5+fl44IEHLNqys7PRt29flJWVYf369RgxYoTF/K1bt4rvdfXq1WL7888/j+3bt+Ozzz4Tt8gBYM2aNSgrK0NmZiZmzZqFbt26WSzz+8+ue/fuHXofZD/cPadb7vjx4xgyZIj4+rdjdr957733sHr1avj4+CAyMhLA9Ts0Wbsj0x/bzWYzPv30U8ybNw8NDQ3t9pfK2p2iLl++jKFDh2L48OF4/PHHsX37dmg0Gmi1WgDWd8/Dw8Nx9uxZnDlzBgaDAZs2bYKXlxfOnz+Pt956C1u3bsXYsWMxdepUTJkyBY8//jgA7p7fDrilSZIdPXoUQ4cO7fDyixcvRv/+/fHGG2+IwVNRUYGAgAD07NnTom9YWFirxzivXbsWCQkJuOuuu1qNbTabcfnyZQQFBXWotiFDhljdXW5pacH+/fuxcuVKzJkzB5MmTWpznClTpuCBBx7AyZMncfz4cfTq1ctimRMnTuCTTz7BmDFjMHjwYPzlL3/pUL3keAxNkmzfvn3o1q0bXnzxRbEtPDy81W5rWwRBwIcffgiZTIaxY8fiypUr0Gq1+Pvf/w6Z7PrXctq0aXB3d8e+ffsslj137hwyMjKQkJBgdex33nkH69evh4eHBwDAw8MDiYmJ7dY0d+5c3HPPPfj6668t2kNCQtC/f3/x9cMPP4zTp0/fcBwXFxfExsbioYceQlBQEIKCgqBSqcRd9CeffFLsGxwcjObmZpw/f77d+qhzYGhSh0ycOBHR0dGoqKhAcXExVq5c2aF7d/7tb3/DkiVLAADLli3D1atXUV5ejvLycsTGxmLixIlWl/vggw8gl8utzvv444+Rm5sLnU6HoqIi7N+/Xzxz/UfvvfceCgsLUV5eDqVSKZ7k+r2ePXtCq9Xi6NGjOHz4MAYMGICVK1eK839/THPPnj0YMWIEfvnlF4vP47vvvsOAAQPg5+eHadOmoaysDAUFBUhLS0N8fLx48uuPxzSHDRtm82dJjsG7HBERScAtTSIiCRiaREQSMDSJiCRgaBIRScDQJCKSgKFJRCQBQ5OISIL/Byqzc5QrwpxOAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 360x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in data.columns:\n",
+    "    if data[i].nunique()<=2:\n",
+    "        plt.figure(figsize=(5,4))\n",
+    "        sns.countplot(data[i])\n",
+    "        plt.title(i)\n",
+    "        plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f9712931",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "2ad8f46d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,4))\n",
+    "sns.distplot(data['AGE'], kde=True, color='m')\n",
+    "plt.title(\"AGE\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "434dbffb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x648 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(12,9))\n",
+    "sns.heatmap(data.corr(), annot=True, cmap = \"rainbow\")\n",
+    "plt.title(\"Correleation Heatmap\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "02305d6f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = data.drop(columns=['LUNG_CANCER'])\n",
+    "y = data['LUNG_CANCER']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6f15c06c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1    270\n",
+       "0     39\n",
+       "Name: LUNG_CANCER, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d64cac54",
+   "metadata": {},
+   "source": [
+    "### Balancing Unbalanced Dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1600ea75",
+   "metadata": {},
+   "source": [
+    "As our dataset is very small instead on under-sampling we will do over-sampling."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1abd4073",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from imblearn.over_sampling import SMOTE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "5163e0a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Original dataset \n",
+      " 1    270\n",
+      "0     39\n",
+      "Name: LUNG_CANCER, dtype: int64\n",
+      "Resample dataset \n",
+      " 0    270\n",
+      "1    270\n",
+      "Name: LUNG_CANCER, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "smote = SMOTE()\n",
+    "\n",
+    "X_sample, y_sample = smote.fit_resample(X, y)\n",
+    "\n",
+    "print('Original dataset \\n',y.value_counts()) \n",
+    "print('Resample dataset \\n', y_sample.value_counts())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "ea6a93ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "x_train, x_test, y_train , y_test = train_test_split(X_sample,y_sample, test_size=0.15,random_state=101)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "e89d429b",
+   "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>GENDER</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>SMOKING</th>\n",
+       "      <th>YELLOW_FINGERS</th>\n",
+       "      <th>ANXIETY</th>\n",
+       "      <th>PEER_PRESSURE</th>\n",
+       "      <th>CHRONIC DISEASE</th>\n",
+       "      <th>FATIGUE</th>\n",
+       "      <th>ALLERGY</th>\n",
+       "      <th>WHEEZING</th>\n",
+       "      <th>ALCOHOL CONSUMING</th>\n",
+       "      <th>COUGHING</th>\n",
+       "      <th>SHORTNESS OF BREATH</th>\n",
+       "      <th>SWALLOWING DIFFICULTY</th>\n",
+       "      <th>CHEST PAIN</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>230</th>\n",
+       "      <td>1</td>\n",
+       "      <td>78</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>465</th>\n",
+       "      <td>0</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>107</th>\n",
+       "      <td>0</td>\n",
+       "      <td>60</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>346</th>\n",
+       "      <td>0</td>\n",
+       "      <td>56</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
+       "230       1   78        0               1        0              1   \n",
+       "18        0   68        1               1        1              1   \n",
+       "465       0   60        0               0        0              0   \n",
+       "107       0   60        1               1        1              1   \n",
+       "346       0   56        1               1        0              0   \n",
+       "\n",
+       "     CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  \\\n",
+       "230                1         1         0         1                  0   \n",
+       "18                 1         1         0         0                  0   \n",
+       "465                0         0         0         0                  0   \n",
+       "107                1         0         1         1                  1   \n",
+       "346                0         0         0         0                  0   \n",
+       "\n",
+       "     COUGHING  SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  \n",
+       "230         0                    1                      1           1  \n",
+       "18          1                    1                      0           0  \n",
+       "465         0                    0                      0           0  \n",
+       "107         0                    0                      1           1  \n",
+       "346         0                    1                      0           0  "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_test.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "1927b794",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier, GradientBoostingClassifier, AdaBoostClassifier\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.naive_bayes import GaussianNB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "5254f0b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.metrics import classification_report, confusion_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "9a914aac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "models = []\n",
+    "models.append((\"LR\",LogisticRegression()))\n",
+    "models.append((\"DT\",DecisionTreeClassifier()))\n",
+    "models.append((\"RF\",RandomForestClassifier()))\n",
+    "models.append((\"ET\",ExtraTreesClassifier()))\n",
+    "models.append((\"GB\",GradientBoostingClassifier()))\n",
+    "models.append((\"SVC\",SVC()))\n",
+    "models.append((\"KNN\",KNeighborsClassifier()))\n",
+    "models.append((\"GNB\",GaussianNB()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "73b72bcb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LR\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.97      0.97       230\n",
+      "           1       0.97      0.97      0.97       229\n",
+      "\n",
+      "    accuracy                           0.97       459\n",
+      "   macro avg       0.97      0.97      0.97       459\n",
+      "weighted avg       0.97      0.97      0.97       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.97      0.97        40\n",
+      "           1       0.98      0.98      0.98        41\n",
+      "\n",
+      "    accuracy                           0.98        81\n",
+      "   macro avg       0.98      0.98      0.98        81\n",
+      "weighted avg       0.98      0.98      0.98        81\n",
+      "\n",
+      "[[223   7]\n",
+      " [  8 221]]\n",
+      "[[39  1]\n",
+      " [ 1 40]]\n",
+      "\n",
+      "DT\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      1.00      1.00       230\n",
+      "           1       1.00      1.00      1.00       229\n",
+      "\n",
+      "    accuracy                           1.00       459\n",
+      "   macro avg       1.00      1.00      1.00       459\n",
+      "weighted avg       1.00      1.00      1.00       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.90      0.93      0.91        40\n",
+      "           1       0.93      0.90      0.91        41\n",
+      "\n",
+      "    accuracy                           0.91        81\n",
+      "   macro avg       0.91      0.91      0.91        81\n",
+      "weighted avg       0.91      0.91      0.91        81\n",
+      "\n",
+      "[[230   0]\n",
+      " [  1 228]]\n",
+      "[[37  3]\n",
+      " [ 4 37]]\n",
+      "\n",
+      "RF\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      1.00      1.00       230\n",
+      "           1       1.00      1.00      1.00       229\n",
+      "\n",
+      "    accuracy                           1.00       459\n",
+      "   macro avg       1.00      1.00      1.00       459\n",
+      "weighted avg       1.00      1.00      1.00       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      0.97      0.99        40\n",
+      "           1       0.98      1.00      0.99        41\n",
+      "\n",
+      "    accuracy                           0.99        81\n",
+      "   macro avg       0.99      0.99      0.99        81\n",
+      "weighted avg       0.99      0.99      0.99        81\n",
+      "\n",
+      "[[229   1]\n",
+      " [  0 229]]\n",
+      "[[39  1]\n",
+      " [ 0 41]]\n",
+      "\n",
+      "ET\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      1.00      1.00       230\n",
+      "           1       1.00      1.00      1.00       229\n",
+      "\n",
+      "    accuracy                           1.00       459\n",
+      "   macro avg       1.00      1.00      1.00       459\n",
+      "weighted avg       1.00      1.00      1.00       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      0.93      0.96        40\n",
+      "           1       0.93      1.00      0.96        41\n",
+      "\n",
+      "    accuracy                           0.96        81\n",
+      "   macro avg       0.97      0.96      0.96        81\n",
+      "weighted avg       0.97      0.96      0.96        81\n",
+      "\n",
+      "[[230   0]\n",
+      " [  1 228]]\n",
+      "[[37  3]\n",
+      " [ 0 41]]\n",
+      "\n",
+      "GB\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.99      0.99      0.99       230\n",
+      "           1       0.99      0.99      0.99       229\n",
+      "\n",
+      "    accuracy                           0.99       459\n",
+      "   macro avg       0.99      0.99      0.99       459\n",
+      "weighted avg       0.99      0.99      0.99       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.98      1.00      0.99        40\n",
+      "           1       1.00      0.98      0.99        41\n",
+      "\n",
+      "    accuracy                           0.99        81\n",
+      "   macro avg       0.99      0.99      0.99        81\n",
+      "weighted avg       0.99      0.99      0.99        81\n",
+      "\n",
+      "[[227   3]\n",
+      " [  3 226]]\n",
+      "[[40  0]\n",
+      " [ 1 40]]\n",
+      "\n",
+      "SVC\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.61      0.77      0.68       230\n",
+      "           1       0.69      0.52      0.59       229\n",
+      "\n",
+      "    accuracy                           0.64       459\n",
+      "   macro avg       0.65      0.64      0.64       459\n",
+      "weighted avg       0.65      0.64      0.64       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.60      0.82      0.69        40\n",
+      "           1       0.73      0.46      0.57        41\n",
+      "\n",
+      "    accuracy                           0.64        81\n",
+      "   macro avg       0.67      0.64      0.63        81\n",
+      "weighted avg       0.67      0.64      0.63        81\n",
+      "\n",
+      "[[177  53]\n",
+      " [111 118]]\n",
+      "[[33  7]\n",
+      " [22 19]]\n",
+      "\n",
+      "KNN\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.92      0.98      0.95       230\n",
+      "           1       0.98      0.92      0.95       229\n",
+      "\n",
+      "    accuracy                           0.95       459\n",
+      "   macro avg       0.95      0.95      0.95       459\n",
+      "weighted avg       0.95      0.95      0.95       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.93      1.00      0.96        40\n",
+      "           1       1.00      0.93      0.96        41\n",
+      "\n",
+      "    accuracy                           0.96        81\n",
+      "   macro avg       0.97      0.96      0.96        81\n",
+      "weighted avg       0.97      0.96      0.96        81\n",
+      "\n",
+      "[[225   5]\n",
+      " [ 19 210]]\n",
+      "[[40  0]\n",
+      " [ 3 38]]\n",
+      "\n",
+      "GNB\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.96      0.85      0.90       230\n",
+      "           1       0.87      0.96      0.91       229\n",
+      "\n",
+      "    accuracy                           0.91       459\n",
+      "   macro avg       0.91      0.91      0.91       459\n",
+      "weighted avg       0.91      0.91      0.91       459\n",
+      "\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      0.90      0.95        40\n",
+      "           1       0.91      1.00      0.95        41\n",
+      "\n",
+      "    accuracy                           0.95        81\n",
+      "   macro avg       0.96      0.95      0.95        81\n",
+      "weighted avg       0.96      0.95      0.95        81\n",
+      "\n",
+      "[[196  34]\n",
+      " [  9 220]]\n",
+      "[[36  4]\n",
+      " [ 0 41]]\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, model in models:\n",
+    "    model.fit(x_train, y_train)\n",
+    "    train_pred = model.predict(x_train)\n",
+    "    test_pred = model.predict(x_test)\n",
+    "    print(name)\n",
+    "    print(classification_report(y_train,train_pred))\n",
+    "    print(classification_report(y_test,test_pred))\n",
+    "    \n",
+    "    print(confusion_matrix(y_train,train_pred))\n",
+    "    print(confusion_matrix(y_test,test_pred))\n",
+    "    print('')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb780941",
+   "metadata": {},
+   "source": [
+    "Lets choose gradined boosting, random forest and KNN for further comparision"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "97e71a16",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model1 = GradientBoostingClassifier()\n",
+    "model2 = RandomForestClassifier()\n",
+    "model3 = KNeighborsClassifier()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "c03f3eaa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model1.fit(x_train,y_train)\n",
+    "model2.fit(x_train,y_train)\n",
+    "model3.fit(x_train,y_train)\n",
+    "\n",
+    "pred_prob1 = model1.predict_proba(x_test)\n",
+    "pred_prob2 = model2.predict_proba(x_test)\n",
+    "pred_prob3 = model3.predict_proba(x_test)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "0c6ac834",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.metrics import roc_curve\n",
+    "\n",
+    "fpr1, tpr1, thresh1 = roc_curve(y_test, pred_prob1[:,1], pos_label=1)\n",
+    "fpr2, tpr2, thresh2 = roc_curve(y_test, pred_prob2[:,1], pos_label=1)\n",
+    "fpr3, tpr3, thresh3 = roc_curve(y_test, pred_prob3[:,1], pos_label=1)\n",
+    "\n",
+    "random_probs = [0 for i in range(len(y_test))]\n",
+    "p_fpr, p_tpr, _ = roc_curve(y_test, random_probs, pos_label=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "d1e3cb8f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.0 , 1.0 , 0.9981707317073171\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import roc_auc_score\n",
+    "auc_score1 = roc_auc_score(y_test, pred_prob1[:,1])\n",
+    "auc_score2 = roc_auc_score(y_test, pred_prob2[:,1])\n",
+    "auc_score3 = roc_auc_score(y_test, pred_prob3[:,1])\n",
+    "\n",
+    "print(auc_score1,\",\", auc_score2,\",\" ,auc_score3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "addda377",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(fpr1, tpr1, linestyle='--',color='r', label='Gradient Boosting')\n",
+    "plt.plot(fpr2, tpr2, linestyle='--',color='yellow', label='Random Forest')\n",
+    "plt.plot(fpr3, tpr3, linestyle='--',color='green', label='KNN')\n",
+    "plt.plot(p_fpr, p_tpr, linestyle='-', color='blue')\n",
+    "plt.title('ROC curve')\n",
+    "plt.xlabel('False Positive Rate')\n",
+    "plt.ylabel('True Positive rate')\n",
+    "plt.legend(loc='best')\n",
+    "plt.show();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24f9fa83",
+   "metadata": {},
+   "source": [
+    "From above three random forest performs better."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "b2aedd43",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "RandomForestClassifier()"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model = RandomForestClassifier()\n",
+    "model.fit(x_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "301a0dad",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9876543209876543\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pickle\n",
+    "pickle_out = open(\"lung_cancer.pkl\",\"wb\")\n",
+    "pickle.dump(model,pickle_out)\n",
+    "loaded_model = pickle.load(open(\"lung_cancer.pkl\",\"rb\"))\n",
+    "result = loaded_model.score(x_test,y_test)\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "6b7478f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['GENDER', 'AGE', 'SMOKING', 'YELLOW_FINGERS', 'ANXIETY',\n",
+       "       'PEER_PRESSURE', 'CHRONIC DISEASE', 'FATIGUE ', 'ALLERGY ', 'WHEEZING',\n",
+       "       'ALCOHOL CONSUMING', 'COUGHING', 'SHORTNESS OF BREATH',\n",
+       "       'SWALLOWING DIFFICULTY', 'CHEST PAIN'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_test.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "9ffc2f54",
+   "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>GENDER</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>SMOKING</th>\n",
+       "      <th>YELLOW_FINGERS</th>\n",
+       "      <th>ANXIETY</th>\n",
+       "      <th>PEER_PRESSURE</th>\n",
+       "      <th>CHRONIC DISEASE</th>\n",
+       "      <th>FATIGUE</th>\n",
+       "      <th>ALLERGY</th>\n",
+       "      <th>WHEEZING</th>\n",
+       "      <th>ALCOHOL CONSUMING</th>\n",
+       "      <th>COUGHING</th>\n",
+       "      <th>SHORTNESS OF BREATH</th>\n",
+       "      <th>SWALLOWING DIFFICULTY</th>\n",
+       "      <th>CHEST PAIN</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>230</th>\n",
+       "      <td>1</td>\n",
+       "      <td>78</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>465</th>\n",
+       "      <td>0</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>107</th>\n",
+       "      <td>0</td>\n",
+       "      <td>60</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>346</th>\n",
+       "      <td>0</td>\n",
+       "      <td>56</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>336</th>\n",
+       "      <td>0</td>\n",
+       "      <td>56</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>279</th>\n",
+       "      <td>0</td>\n",
+       "      <td>59</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0</td>\n",
+       "      <td>61</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>195</th>\n",
+       "      <td>1</td>\n",
+       "      <td>69</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>81 rows × 15 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
+       "230       1   78        0               1        0              1   \n",
+       "18        0   68        1               1        1              1   \n",
+       "465       0   60        0               0        0              0   \n",
+       "107       0   60        1               1        1              1   \n",
+       "346       0   56        1               1        0              0   \n",
+       "..      ...  ...      ...             ...      ...            ...   \n",
+       "336       0   56        0               0        0              0   \n",
+       "279       0   59        0               1        1              1   \n",
+       "363       0   62        0               0        0              0   \n",
+       "19        0   61        0               0        0              0   \n",
+       "195       1   69        0               1        1              0   \n",
+       "\n",
+       "     CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  \\\n",
+       "230                1         1         0         1                  0   \n",
+       "18                 1         1         0         0                  0   \n",
+       "465                0         0         0         0                  0   \n",
+       "107                1         0         1         1                  1   \n",
+       "346                0         0         0         0                  0   \n",
+       "..               ...       ...       ...       ...                ...   \n",
+       "336                0         0         0         0                  0   \n",
+       "279                0         0         1         1                  0   \n",
+       "363                0         0         0         0                  0   \n",
+       "19                 1         1         0         0                  0   \n",
+       "195                0         0         0         1                  1   \n",
+       "\n",
+       "     COUGHING  SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  \n",
+       "230         0                    1                      1           1  \n",
+       "18          1                    1                      0           0  \n",
+       "465         0                    0                      0           0  \n",
+       "107         0                    0                      1           1  \n",
+       "346         0                    1                      0           0  \n",
+       "..        ...                  ...                    ...         ...  \n",
+       "336         0                    1                      1           0  \n",
+       "279         1                    0                      1           0  \n",
+       "363         0                    1                      0           0  \n",
+       "19          0                    1                      0           0  \n",
+       "195         1                    1                      1           0  \n",
+       "\n",
+       "[81 rows x 15 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "d4529c5c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GENDER 2\n",
+      "AGE 25\n",
+      "SMOKING 2\n",
+      "YELLOW_FINGERS 2\n",
+      "ANXIETY 2\n",
+      "PEER_PRESSURE 2\n",
+      "CHRONIC DISEASE 2\n",
+      "FATIGUE  2\n",
+      "ALLERGY  2\n",
+      "WHEEZING 2\n",
+      "ALCOHOL CONSUMING 2\n",
+      "COUGHING 2\n",
+      "SHORTNESS OF BREATH 2\n",
+      "SWALLOWING DIFFICULTY 2\n",
+      "CHEST PAIN 2\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in x_test.columns:\n",
+    "    print(f\"{i} {x_test[i].nunique()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "15152293",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "230    1\n",
+       "18     1\n",
+       "465    0\n",
+       "107    1\n",
+       "346    0\n",
+       "      ..\n",
+       "336    0\n",
+       "279    1\n",
+       "363    0\n",
+       "19     0\n",
+       "195    1\n",
+       "Name: LUNG_CANCER, Length: 81, dtype: int64"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8a9b7bab",
+   "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": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}