titanic_survival_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "84fb7e60-97bd-42f9-8cd0-2e6b74b16f5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "b346b0f2-021d-43e4-84a0-b4f5200b8a15",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./datas/titanic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "8389e4d8-1c0e-413a-ac7d-dcb09e482418",
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   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
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       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
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       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
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       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
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       "      <td>C85</td>\n",
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       "      <td>Heikkinen, Miss. Laina</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
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       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
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       "      <td>Allen, Mr. William Henry</td>\n",
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       "      <td>35.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
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       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Moran, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330877</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
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       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>McCarthy, Mr. Timothy J</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17463</td>\n",
       "      <td>51.8625</td>\n",
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       "      <td>Palsson, Master. Gosta Leonard</td>\n",
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       "      <td>9</td>\n",
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       "      <td>3</td>\n",
       "      <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
       "      <td>female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>347742</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
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       "      <td>1</td>\n",
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       "      <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
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       "      <td>237736</td>\n",
       "      <td>30.0708</td>\n",
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       "      <td>C</td>\n",
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      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "5            6         0       3   \n",
       "6            7         0       1   \n",
       "7            8         0       3   \n",
       "8            9         1       3   \n",
       "9           10         1       2   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "5                                   Moran, Mr. James    male   NaN      0   \n",
       "6                            McCarthy, Mr. Timothy J    male  54.0      0   \n",
       "7                     Palsson, Master. Gosta Leonard    male   2.0      3   \n",
       "8  Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0      0   \n",
       "9                Nasser, Mrs. Nicholas (Adele Achem)  female  14.0      1   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  \n",
       "5      0            330877   8.4583   NaN        Q  \n",
       "6      0             17463  51.8625   E46        S  \n",
       "7      1            349909  21.0750   NaN        S  \n",
       "8      2            347742  11.1333   NaN        S  \n",
       "9      0            237736  30.0708   NaN        C  "
      ]
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     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "3b02b1fb-84a5-4524-9ca9-2085c30e136d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId      0\n",
       "Survived         0\n",
       "Pclass           0\n",
       "Name             0\n",
       "Sex              0\n",
       "Age            177\n",
       "SibSp            0\n",
       "Parch            0\n",
       "Ticket           0\n",
       "Fare             0\n",
       "Cabin          687\n",
       "Embarked         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "35751ec2-e657-4b15-91f9-bb6b458dda93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.0"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Age.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "f71ebdac-4003-4bfa-9f06-b7a7d3aa2c01",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.fillna(df.Age.mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "5965966c-095f-4194-9536-05aecb7c933f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['PassengerId','Name', 'Cabin','Ticket', 'Embarked'], axis = 1,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "1be7ee85-7ef7-40ce-af31-47e178cd6d56",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "   Survived  Pclass     Sex   Age  SibSp  Parch     Fare\n",
       "0         0       3    male  22.0      1      0   7.2500\n",
       "1         1       1  female  38.0      1      0  71.2833\n",
       "2         1       3  female  26.0      0      0   7.9250\n",
       "3         1       1  female  35.0      1      0  53.1000\n",
       "4         0       3    male  35.0      0      0   8.0500"
      ]
     },
     "execution_count": 82,
     "metadata": {},
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   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "72e5240a-0ac6-4dbb-a3ea-563bf6a10b07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Sex'], dtype='object')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_data = data_train.select_dtypes(include=['object']).columns\n",
    "categorical_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "fff97138-d00d-4eeb-9911-132bd0859c1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "le = LabelEncoder()"
   ]
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   "cell_type": "code",
   "execution_count": 85,
   "id": "67b0ca92-5b33-4ece-be17-41faad903ed2",
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       "      <td>32.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass        Age  SibSp  Parch     Fare  Sex_le\n",
       "0           0       3  22.000000      1      0   7.2500       1\n",
       "1           1       1  38.000000      1      0  71.2833       0\n",
       "2           1       3  26.000000      0      0   7.9250       0\n",
       "3           1       1  35.000000      1      0  53.1000       0\n",
       "4           0       3  35.000000      0      0   8.0500       1\n",
       "..        ...     ...        ...    ...    ...      ...     ...\n",
       "886         0       2  27.000000      0      0  13.0000       1\n",
       "887         1       1  19.000000      0      0  30.0000       0\n",
       "888         0       3  29.699118      1      2  23.4500       0\n",
       "889         1       1  26.000000      0      0  30.0000       1\n",
       "890         0       3  32.000000      0      0   7.7500       1\n",
       "\n",
       "[891 rows x 7 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for cat_data in categorical_data:\n",
    "    df[cat_data+\"_le\"] = le.fit_transform(df[cat_data])\n",
    "    df.drop([cat_data], axis = 1, inplace = True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "b93f3bec-1dcf-4752-8cc3-9caf1d7fd89a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "712"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train, data_test, target_train, target_test = train_test_split(df[['Pclass','Sex_le','Age','SibSp','Parch','Fare']],df.Survived, test_size = 0.2)\n",
    "len(data_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "9c56ec7c-ade6-46cf-bcab-23fe76f142b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([21.,  9., 32., 39., 77., 32., 18., 15.,  7.,  7.]),\n",
       " array([ 0.75 ,  6.975, 13.2  , 19.425, 25.65 , 31.875, 38.1  , 44.325,\n",
       "        50.55 , 56.775, 63.   ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data_train[data_train['Sex_le'] == 0]['Age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "cd3a9f08-6497-4d4c-b302-7db5e2cd6bac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 22.,  16.,  90., 190.,  54.,  36.,  24.,  14.,   7.,   2.]),\n",
       " array([ 0.42 ,  8.378, 16.336, 24.294, 32.252, 40.21 , 48.168, 56.126,\n",
       "        64.084, 72.042, 80.   ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data_train[data_train['Sex_le'] == 1]['Age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "63b039fc-636e-46e6-a4e4-ba3d92e7ca07",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = DecisionTreeClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "c8a18369-8156-4ec3-8953-cf1f9f371b3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier()"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(data_train, target_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "8a21e6b7-0a8a-4197-aba7-82f98a90ac8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.776536312849162"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(data_test, target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "487be3ab-294f-4dd3-a82b-17620b07966c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0,\n",
       "       0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0,\n",
       "       0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1,\n",
       "       1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0,\n",
       "       0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1,\n",
       "       0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0,\n",
       "       0, 1, 0])"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "10f793b4-118a-4b64-a066-37b98a9a3554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[92, 20],\n",
       "       [20, 47]])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted = model.predict(data_test)\n",
    "cm = confusion_matrix(target_test, predicted)\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "d39bb5c2-7ee7-41e2-981a-deacaf547101",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "2311b638-ad38-45d9-bc76-ba9d77d742b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = RandomForestClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "ac74b79d-fd38-4e5b-bfb9-1bb264a0074f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier()"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(data_train, target_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "6205f41a-9709-4de2-98ab-7740a82eb685",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7932960893854749"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(data_test, target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "94e2d3bf-70a3-453f-940e-c3f886546d9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[94, 18],\n",
       "       [19, 48]])"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted = model.predict(data_test)\n",
    "cm = confusion_matrix(target_test, predicted)\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40b4fc16-4d33-4ced-90e1-200313c798d6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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