Lung Cancer Prediction.ipynb

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   "attachments": {},
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   "id": "08115f95",
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   "source": [
    "# Lung Cancer Prediction\n",
    "___\n",
    "### Use Case\n",
    "We have been employed as an ML Engineer in a Hospital (P-Health), upon reaching there we noticed that our company spends a lot of money and resources running tests and examinations on patients to see if they have lung cancer or not.\n",
    "\n",
    "We have proposed that we can build a ML model that can predict the patient that have higher chances of having cancer, of course we our model won't be 100% sure if someone has or not, but we would create one that predicts if someone that has lung cancer more\n",
    "___\n",
    "\n",
    "* Type of Machine Learning Method\n",
    "    * Supervised Learning\n",
    "        * Classification\n",
    "            * Random Forest\n",
    "                * Accuracy - 95.16 %\n",
    "                * F1 Score - 97.35%\n",
    "                * Recall - 100%\n",
    "            * SVM\n",
    "                * Accuracy - 88.71 %\n",
    "                * F1 Score - 94.02%\n",
    "            * KNN\n",
    "                * Accuracy - 91.16 %\n",
    "                * F1 Score - 95.35%\n",
    "___\n",
    "\n",
    "### Steps to Solve Problem\n",
    "* Import Dataset\n",
    "* Exploratory Data Analysis\n",
    "* Feature Engineering\n",
    "    * Data Cleaning\n",
    "    * Missing Data Imputation\n",
    "    * Feature Encoding\n",
    "* Model Build\n",
    "    * Train / Test Data split\n",
    "    * Model Initiation and Fitting\n",
    "    * Test predictions\n",
    "* Model Perfromance\n",
    "    * MAE\n",
    "    * R^2 score\n",
    "    * Case Prediction\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a49f7fe",
   "metadata": {},
   "source": [
    "## Import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4454e8ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd # for data manipulation\n",
    "import numpy as np # for numerical analysis\n",
    "\n",
    "# For plottling graphs\n",
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# for saving tools\n",
    "import joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4e6889cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting Plotting Settings\n",
    "%matplotlib inline\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "328739de",
   "metadata": {},
   "source": [
    "Import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "581b2d58",
   "metadata": {},
   "outputs": [],
   "source": [
    "cancer = pd.read_csv(\"survey lung cancer.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a1d7b3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
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       "    }\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",
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       "      <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",
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       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <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",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>NO</td>\n",
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       "    <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",
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      ],
      "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking First 5 rows of data\n",
    "cancer.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c41822f1",
   "metadata": {},
   "source": [
    "Checking basic information about the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8c4c8c08",
   "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', 'LUNG_CANCER'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking columns in the dataset\n",
    "cancer.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2f1234c8",
   "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": [
    "# no missing data\n",
    "cancer.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efc301b3",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fb298ee",
   "metadata": {},
   "source": [
    "Mapping the Values of 2 to Yes (1) and 1 to No (0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "951bbc09",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's map the 2 - Y, 1- no\n",
    "mapper = {\n",
    "    1 : 0,\n",
    "    2 : 1\n",
    "}\n",
    "\n",
    "# extracting features that need mapping\n",
    "mapped_columns = [column for column in cancer.columns if cancer[column].dtype == \"int64\"][1:]\n",
    "\n",
    "# Mapping these features\n",
    "for column in mapped_columns:\n",
    "    cancer[column] = cancer[column].map(mapper)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf5c8efa",
   "metadata": {},
   "source": [
    "Mapping Lung Cancer for Yes for 1, No for 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "47d02665",
   "metadata": {},
   "outputs": [],
   "source": [
    "# turn target Y- 1, n-0\n",
    "mapper = {\n",
    "    \"NO\" : 0,\n",
    "    \"YES\" : 1\n",
    "}\n",
    "cancer[\"LUNG_CANCER\"] = cancer[\"LUNG_CANCER\"].map(mapper)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf5c8efa",
   "metadata": {},
   "source": [
    "Mapping Gender for Male for 1, Female for 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e9e5ffdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# turn target Y- 1, n-0\n",
    "mapper = {\n",
    "    \"F\" : 0,\n",
    "    \"M\" : 1\n",
    "}\n",
    "cancer[\"GENDER\"] = cancer[\"GENDER\"].map(mapper)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d426e665",
   "metadata": {},
   "source": [
    "#### Data Shuffle and Split\n",
    "It is good pratice to split the dataset before preprocessing to avoid data leakage, shuffling the data adds randomness which can boost model performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6b1acbf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Shuffling the data\n",
    "cancer = cancer.sample(frac=1).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6d71ebb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Splitting the data into train and test data\n",
    "from sklearn.model_selection import train_test_split\n",
    "X = cancer.drop(\"LUNG_CANCER\", axis=1) \n",
    "y = cancer[\"LUNG_CANCER\"]\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=51)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f3b191e",
   "metadata": {},
   "source": [
    "#### Missing data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ffcfb76",
   "metadata": {},
   "source": [
    "There is no missing data in the features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "472d99f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GENDER                   0\n",
       "AGE                      0\n",
       "SMOKING                  0\n",
       "YELLOW_FINGERS           0\n",
       "ANXIETY                  0\n",
       "PEER_PRESSURE            0\n",
       "CHRONIC DISEASE          0\n",
       "FATIGUE                  0\n",
       "ALLERGY                  0\n",
       "WHEEZING                 0\n",
       "ALCOHOL CONSUMING        0\n",
       "COUGHING                 0\n",
       "SHORTNESS OF BREATH      0\n",
       "SWALLOWING DIFFICULTY    0\n",
       "CHEST PAIN               0\n",
       "LUNG_CANCER              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check total of missing values\n",
    "cancer.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "184dc968",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation\n",
    "plt.figure(figsize=[10,8])\n",
    "sns.heatmap(cancer.corr(), cbar=False, annot=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c28a866",
   "metadata": {},
   "source": [
    "### Model Building"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a859280",
   "metadata": {},
   "source": [
    "#### Preprocessing Test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2d564ad7",
   "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>255</th>\n",
       "      <td>0</td>\n",
       "      <td>77</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>1</td>\n",
       "      <td>73</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>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>0</td>\n",
       "      <td>77</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>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>1</td>\n",
       "      <td>58</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>1</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
       "255       0   77        0               0        0              1   \n",
       "166       0   61        0               1        0              1   \n",
       "57        1   73        0               0        0              0   \n",
       "211       0   77        0               1        1              1   \n",
       "149       1   58        1               0        0              0   \n",
       "\n",
       "     CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  \\\n",
       "255                1         1         0         0                  1   \n",
       "166                0         1         0         0                  0   \n",
       "57                 1         0         1         0                  1   \n",
       "211                1         1         1         1                  0   \n",
       "149                0         0         1         1                  1   \n",
       "\n",
       "     COUGHING  SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  \n",
       "255         1                    1                      1           0  \n",
       "166         1                    1                      0           1  \n",
       "57          1                    1                      1           1  \n",
       "211         1                    1                      1           1  \n",
       "149         1                    0                      0           1  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking first 5 rows of data\n",
    "X_test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bfef538",
   "metadata": {},
   "source": [
    "#### Random Forest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cd6b898",
   "metadata": {},
   "source": [
    "Import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6e838566",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8d6490f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "bagger = RandomForestClassifier(random_state=51, n_jobs=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0128eab",
   "metadata": {},
   "source": [
    "Train model and make predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e44e467e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(max_depth=3, max_leaf_nodes=5, max_samples=5, n_jobs=-1,\n",
       "                       random_state=51)</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 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 sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(max_depth=3, max_leaf_nodes=5, max_samples=5, n_jobs=-1,\n",
       "                       random_state=51)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier(max_depth=3, max_leaf_nodes=5, max_samples=5, n_jobs=-1,\n",
       "                       random_state=51)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bagger.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cd9d8b27",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = bagger.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b936ac69",
   "metadata": {},
   "source": [
    "#### RF Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b155c448",
   "metadata": {},
   "outputs": [],
   "source": [
    "# libraries to check performance\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, f1_score,  recall_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fe2d192",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy is 95.16 %\n",
      "The f1 score is 97.35 %\n",
      "The recall is 100.00 %\n"
     ]
    }
   ],
   "source": [
    "print(f\"The accuracy is {accuracy_score(y_test, predictions) * 100:.2f} %\")\n",
    "print(f\"The f1 score is {f1_score(y_test, predictions) * 100:.2f} %\") \n",
    "print(f\"The recall is {recall_score(y_test, predictions) * 100:.2f} %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95cfba32",
   "metadata": {},
   "source": [
    "Confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3baf6cb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(confusion_matrix(y_test, predictions), annot=True, cbar=False);\n",
    "# TN   FP\n",
    "# FN*   TP - Recall"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf0624a",
   "metadata": {},
   "source": [
    "### SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abc07327",
   "metadata": {},
   "source": [
    "Import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "7e2359a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5c668d03",
   "metadata": {},
   "outputs": [],
   "source": [
    "svm = SVC()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5bb59ac",
   "metadata": {},
   "source": [
    "Train model and make predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ba155529",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC()</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 sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVC</label><div class=\"sk-toggleable__content\"><pre>SVC()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svm.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a187d8bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = svm.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f00b133b",
   "metadata": {},
   "source": [
    "#### SVM Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5f175591",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy is 88.71 %\n",
      "The f1 score is 94.02 %\n",
      "The recall is 100.00 %\n"
     ]
    }
   ],
   "source": [
    "print(f\"The accuracy is {accuracy_score(y_test, predictions) * 100:.2f} %\")\n",
    "print(f\"The f1 score is {f1_score(y_test, predictions) * 100:.2f} %\") \n",
    "print(f\"The recall is {recall_score(y_test, predictions) * 100:.2f} %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6f19240",
   "metadata": {},
   "source": [
    "Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d23a3b25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(confusion_matrix(y_test, predictions), annot=True, cbar=False);\n",
    "# TN   FP\n",
    "# FN*   TP - Recall"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b69aa8",
   "metadata": {},
   "source": [
    "### KNN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c822e20",
   "metadata": {},
   "source": [
    "Import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "62457e4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "83882d80",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = KNeighborsClassifier()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67afaa45",
   "metadata": {},
   "source": [
    "Train model and make predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a73278c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier()</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 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 sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "KNeighborsClassifier()"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b01261d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb956439",
   "metadata": {},
   "source": [
    "#### KNN Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "95050946",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy is 91.94 %\n",
      "The f1 score is 95.65 %\n",
      "The recall is 100.00 %\n"
     ]
    }
   ],
   "source": [
    "print(f\"The accuracy is {accuracy_score(y_test, predictions) * 100:.2f} %\")\n",
    "print(f\"The f1 score is {f1_score(y_test, predictions) * 100:.2f} %\") \n",
    "print(f\"The recall is {recall_score(y_test, predictions) * 100:.2f} %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b854d888",
   "metadata": {},
   "source": [
    "Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f80d687a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(confusion_matrix(y_test, predictions), annot=True, cbar=False);\n",
    "# TN   FP\n",
    "# FN*   TP - Recall"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2f21ab3",
   "metadata": {},
   "source": [
    "Saving The Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "92aeaa39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['model_joblib']"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# joblib.dump(bagger, \"model_joblib\")"
   ]
  }
 ],
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   "language": "python",
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