heart_disease_logistic_regression.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bab00d85-8c88-439a-8085-cac0c4b4a82f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
    "from sklearn.metrics import confusion_matrix, classification_report\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
    "from scipy.stats import chi2_contingency\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "from statsmodels.stats.multicomp import pairwise_tukeyhsd\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "\n",
    "from sklearn.metrics import RocCurveDisplay\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cbde39e0-0c31-49bd-9a95-2bcd4a2edac9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of data is (303, 14)\n",
      "The columns namrs is  Index(['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach',\n",
      "       'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv('heart-disease.csv')\n",
    "print(f'The shape of data is {data.shape}')\n",
    "print(f'The columns namrs is  {data.columns}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fa7e5271-121f-4196-8e10-d3e0976d5eef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e165de8-832f-483e-9fc3-bc655381b42e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "target\n",
       "1    165\n",
       "0    138\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['target'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e9243a9-20e7-42bc-b463-16901c5904c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total unique_numbers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cp</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trestbps</th>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chol</th>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fbs</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>restecg</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>thalach</th>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>exang</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oldpeak</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>slope</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ca</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>thal</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Total unique_numbers \n",
       "age                          41\n",
       "sex                           2\n",
       "cp                            4\n",
       "trestbps                     49\n",
       "chol                        152\n",
       "fbs                           2\n",
       "restecg                       3\n",
       "thalach                      91\n",
       "exang                         2\n",
       "oldpeak                      40\n",
       "slope                         3\n",
       "ca                            5\n",
       "thal                          4\n",
       "target                        2"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_numbers = []\n",
    "for i in data.columns:\n",
    "    x = data[i].value_counts().count()\n",
    "    unique_numbers.append(x)\n",
    "    \n",
    "pd.DataFrame(unique_numbers,index = data.columns,columns=[\"Total unique_numbers \"])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "25e36d1a-e5fa-4d60-9364-136d816d20aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Correlation Matrix')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig , ax = plt.subplots(figsize=(15,12))\n",
    "\n",
    "sns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n",
    "plt.title('Correlation Matrix')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fc558f3-341b-49a3-8f04-d684919d3b1d",
   "metadata": {},
   "source": [
    "we use Analysis of Variance (ANOVA) to determine the relationship between a categorical dependent variable (target) and several continuous independent variables (age, trestbps, chol, thalach, oldpeak). ANOVA helps us test whether there are significant differences in the means of these continuous variables across the categories of the target variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "097a48ec-a6cb-4dfc-854a-9f1942be95af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Shiraz1\\AppData\\Local\\Temp\\ipykernel_11768\\3182827332.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  p_value = anova_table['PR(>F)'][0]\n",
      "C:\\Users\\Shiraz1\\AppData\\Local\\Temp\\ipykernel_11768\\3182827332.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  p_value = anova_table['PR(>F)'][0]\n",
      "C:\\Users\\Shiraz1\\AppData\\Local\\Temp\\ipykernel_11768\\3182827332.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  p_value = anova_table['PR(>F)'][0]\n",
      "C:\\Users\\Shiraz1\\AppData\\Local\\Temp\\ipykernel_11768\\3182827332.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  p_value = anova_table['PR(>F)'][0]\n",
      "C:\\Users\\Shiraz1\\AppData\\Local\\Temp\\ipykernel_11768\\3182827332.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  p_value = anova_table['PR(>F)'][0]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>Variable</th>\n",
       "      <th>ANOVA p-value</th>\n",
       "      <th>Significant</th>\n",
       "      <th>Tukey's HSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>age</td>\n",
       "      <td>7.524801e-05</td>\n",
       "      <td>True</td>\n",
       "      <td>Multiple Comparison of Means - Tukey HSD, FWER...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>trestbps</td>\n",
       "      <td>1.154606e-02</td>\n",
       "      <td>True</td>\n",
       "      <td>Multiple Comparison of Means - Tukey HSD, FWER...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chol</td>\n",
       "      <td>1.387903e-01</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>thalach</td>\n",
       "      <td>1.697338e-14</td>\n",
       "      <td>True</td>\n",
       "      <td>Multiple Comparison of Means - Tukey HSD, FWER...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>oldpeak</td>\n",
       "      <td>4.085346e-15</td>\n",
       "      <td>True</td>\n",
       "      <td>Multiple Comparison of Means - Tukey HSD, FWER...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Variable  ANOVA p-value  Significant  \\\n",
       "0       age   7.524801e-05         True   \n",
       "1  trestbps   1.154606e-02         True   \n",
       "2      chol   1.387903e-01        False   \n",
       "3   thalach   1.697338e-14         True   \n",
       "4   oldpeak   4.085346e-15         True   \n",
       "\n",
       "                                         Tukey's HSD  \n",
       "0  Multiple Comparison of Means - Tukey HSD, FWER...  \n",
       "1  Multiple Comparison of Means - Tukey HSD, FWER...  \n",
       "2                                               None  \n",
       "3  Multiple Comparison of Means - Tukey HSD, FWER...  \n",
       "4  Multiple Comparison of Means - Tukey HSD, FWER...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "results = []\n",
    "\n",
    "numeric_vars = ['age', 'trestbps', 'chol', 'thalach', 'oldpeak']  \n",
    "\n",
    "for var in numeric_vars:\n",
    "    model = smf.ols(f'{var} ~ C(target)', data=data).fit()\n",
    "    \n",
    "    anova_table = sm.stats.anova_lm(model, typ=2)\n",
    "    p_value = anova_table['PR(>F)'][0]\n",
    "    \n",
    "    result = {\n",
    "        'Variable': var,\n",
    "        'ANOVA p-value': p_value,\n",
    "        'Significant': p_value < 0.05\n",
    "    }\n",
    "    \n",
    "    if p_value < 0.05:\n",
    "        tukey = pairwise_tukeyhsd(endog=data[var], groups=data['target'], alpha=0.05)\n",
    "        tukey_results = tukey.summary().as_text()\n",
    "        \n",
    "        result['Tukey\\'s HSD'] = tukey_results\n",
    "    else:\n",
    "        result['Tukey\\'s HSD'] = None\n",
    "    \n",
    "    results.append(result)\n",
    "\n",
    "results_df = pd.DataFrame(results)\n",
    "results_df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d68d9e65-c6c1-4ab5-8f00-6d23c224bb9d",
   "metadata": {},
   "source": [
    " In this section, we use the Chi-square test to examine the relationship between independent categorical variables and the target variable, which is also a categorical variable.\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c2872a74-1254-40cb-969c-2334b25a0f05",
   "metadata": {},
   "outputs": [],
   "source": [
    "categoric_var = ['sex' , 'cp' , 'fbs' , 'restecg' , 'exang' , 'slope' , 'ca' , 'thal' , 'target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "963d49d1-b962-42b8-9300-31c3a9e69d50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Variable</th>\n",
       "      <th>Chi-square value</th>\n",
       "      <th>P-value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sex</td>\n",
       "      <td>22.717227</td>\n",
       "      <td>1.876778e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cp</td>\n",
       "      <td>81.686428</td>\n",
       "      <td>1.334304e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fbs</td>\n",
       "      <td>0.106273</td>\n",
       "      <td>7.444281e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>restecg</td>\n",
       "      <td>10.023092</td>\n",
       "      <td>6.660599e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>exang</td>\n",
       "      <td>55.944550</td>\n",
       "      <td>7.454409e-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>slope</td>\n",
       "      <td>47.506897</td>\n",
       "      <td>4.830682e-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ca</td>\n",
       "      <td>74.366631</td>\n",
       "      <td>2.712470e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>thal</td>\n",
       "      <td>85.303740</td>\n",
       "      <td>2.233351e-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>target</td>\n",
       "      <td>298.981398</td>\n",
       "      <td>5.491510e-67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Variable  Chi-square value       P-value\n",
       "0      sex         22.717227  1.876778e-06\n",
       "1       cp         81.686428  1.334304e-17\n",
       "2      fbs          0.106273  7.444281e-01\n",
       "3  restecg         10.023092  6.660599e-03\n",
       "4    exang         55.944550  7.454409e-14\n",
       "5    slope         47.506897  4.830682e-11\n",
       "6       ca         74.366631  2.712470e-15\n",
       "7     thal         85.303740  2.233351e-18\n",
       "8   target        298.981398  5.491510e-67"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "results = []\n",
    "\n",
    "for var in categoric_var:\n",
    "    contingency_table = pd.crosstab(data[var], data['target'])\n",
    "    \n",
    "    chi2, p, _, _ = chi2_contingency(contingency_table)\n",
    "    \n",
    "    results.append({\n",
    "        'Variable': var,\n",
    "        'Chi-square value': chi2,\n",
    "        'P-value': p\n",
    "    })\n",
    "\n",
    "results_df_chi = pd.DataFrame(results)\n",
    "results_df_chi\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0d5d8a3d-5536-4f3e-8459-57b766f0b8a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data[['thal', 'ca', 'slope', 'exang', 'cp', 'sex', 'oldpeak', 'age', 'thalach']]\n",
    "\n",
    "y = data['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "249359ef-4e51-4321-9c19-aef4f50deb8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Ratio: 50% | Accuracy: 82.24%\n",
      "Training Ratio: 60% | Accuracy: 81.97%\n",
      "Training Ratio: 70% | Accuracy: 82.42%\n",
      "Training Ratio: 80% | Accuracy: 86.89%\n",
      "Training Ratio: 90% | Accuracy: 83.87%\n"
     ]
    }
   ],
   "source": [
    "ratios = [0.5, 0.6, 0.7, 0.8, 0.9]\n",
    "results = []\n",
    "\n",
    "for ratio in ratios:\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=1-ratio, random_state=42)\n",
    "    \n",
    "    scaler = StandardScaler()\n",
    "    X_train_scaled = scaler.fit_transform(X_train)\n",
    "    X_test_scaled = scaler.transform(X_test)\n",
    "    \n",
    "    clf = LogisticRegression(max_iter=200).fit(X_train_scaled, y_train)\n",
    "    \n",
    "    y_pred = clf.predict(X_test_scaled)\n",
    "    \n",
    "    accuracy = accuracy_score(y_test, y_pred)\n",
    "    results.append((ratio * 100, accuracy * 100))\n",
    "    print(f\"Training Ratio: {ratio*100:.0f}% | Accuracy: {accuracy*100:.2f}%\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a7afc44c-a790-4eee-beed-675f269edd02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "training_ratios, accuracies = zip(*results)\n",
    "plt.plot(training_ratios, accuracies, marker='o', linestyle='-')\n",
    "plt.title('Accuracy vs Training Ratio')\n",
    "plt.xlabel('Training Ratio (%)')\n",
    "plt.ylabel('Accuracy (%)')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8d36770-2a78-4099-803c-f1f6bfb6b0a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "scaler = StandardScaler()\n",
    "X_train_scaled = scaler.fit_transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)\n",
    "\n",
    "clf = LogisticRegression(max_iter=200).fit(X_train_scaled, y_train)\n",
    "\n",
    "y_pred = clf.predict(X_test_scaled)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cab68135-ffd7-4910-a9fd-586933706e49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Performance Metrics:\n",
      "Accuracy: 0.8689\n",
      "Precision: 0.8750\n",
      "Recall: 0.8750\n",
      "F1-Score: 0.8750\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
    "\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "precision = precision_score(y_test, y_pred)\n",
    "recall = recall_score(y_test, y_pred)\n",
    "f1 = f1_score(y_test, y_pred)\n",
    "\n",
    "print(f\"Model Performance Metrics:\")\n",
    "\n",
    "print(f\"Accuracy: {accuracy:.4f}\")\n",
    "\n",
    "print(f\"Precision: {precision:.4f}\")\n",
    "\n",
    "print(f\"Recall: {recall:.4f}\")\n",
    "\n",
    "print(f\"F1-Score: {f1:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "733e2282-4bfb-4b43-82ea-6475e6d3eb28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x22435667d50>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dAACwsWhd7EZrHQAAG6MiBwA4g+mytmAtQityEjkAwBGidY6c1joAADZGRQ4AcAYeCAMAgH1F66p1vxL522+/7fcJb7311hoHAwAAAuNXIh80aJBfJ3O5XPJ4PFbiAQAgdCK0PW6FX4ncMIxQxwEAQEhFa2vd0qr1srKyYMUBAEBomUHYIlDAidzj8Wj27Nlq2rSpkpKS9Pnnn0uSpk6dqhdffDHoAQIAgIsLOJE//vjjysvL0xNPPKH4+HjveIcOHfTCCy8ENTgAAILHFYQt8gScyJcsWaI///nPGjp0qGJjY73jnTt31t69e4MaHAAAQUNrvcrRo0eVnZ1dbdwwDFVWVgYlKAAA4J+AE3n79u21adOmauOvv/66rrrqqqAEBQBA0EVpRR7wk92mTZumnJwcHT16VIZh6M0331R+fr6WLFmi1atXhyJGAACsi9K3nwVckQ8cOFCrVq3Se++9p7p162ratGnas2ePVq1apV/84hehiBEAAFxEjZ61fuONN2rt2rXBjgUAgJCJ1teY1vilKTt27NCePXskVc2bd+3aNWhBAQAQdLz9rMqRI0d0xx136MMPP1S9evUkSadOndLPfvYzLV++XM2aNQt2jAAA4CICniO/++67VVlZqT179ujkyZM6efKk9uzZI8MwdPfdd4ciRgAArDu/2M3KFoECrsg3bNigLVu2qE2bNt6xNm3a6JlnntGNN94Y1OAAAAgWl1m1WTk+EgWcyDMzMy/44BePx6OMjIygBAUAQNBF6Rx5wK31J598UmPHjtWOHTu8Yzt27NC4ceP0hz/8IajBAQCAH+dXRV6/fn25XN/PDZSWlqpbt26Ki6s6/Ny5c4qLi9Ndd92lQYMGhSRQAAAsidIHwviVyOfNmxfiMAAACLEoba37lchzcnJCHQcAAKiBGj8QRpLKyspUUVHhM5aSkmIpIAAAQiJKK/KAF7uVlpZqzJgxaty4serWrav69ev7bAAARKQofftZwIl80qRJev/997Vw4UK53W698MILmjlzpjIyMrRkyZJQxAgAAC4i4Nb6qlWrtGTJEvXq1UvDhw/XjTfeqOzsbGVlZWnp0qUaOnRoKOIEAMCaKF21HnBFfvLkSbVq1UpS1Xz4yZMnJUk33HCDNm7cGNzoAAAIkvNPdrOyRaKAE3mrVq20f/9+SVLbtm312muvSaqq1M+/RAUAANSOgBP58OHD9cknn0iSJk+erAULFighIUHjx4/XQw89FPQAAQAIiihd7BbwHPn48eO9f+7Tp4/27t2rnTt3Kjs7W506dQpqcAAA4MdZuo9ckrKyspSVlRWMWAAACBmXLL79LGiRBJdfiXz+/Pl+n/D++++vcTAAACAwfiXyuXPn+nUyl8sVlkT+4lWtFOe6rNavC9SGd4/tDncIQMgUnzFUv3UtXSxKbz/zK5GfX6UOAIBt8YhWAAAQaSwvdgMAwBaitCInkQMAHMHq09mi5sluAAAgclCRAwCcIUpb6zWqyDdt2qQ777xT3bt319GjRyVJr7zyijZv3hzU4AAACJoofURrwIn8jTfeUL9+/ZSYmKiPP/5Y5eXlkqTTp09rzpw5QQ8QAABcXMCJ/LHHHtOiRYv0/PPP67LLvn8Iy/XXX69du3YFNTgAAIIlWl9jGvAceX5+vnr06FFtPDU1VadOnQpGTAAABF+UPtkt4Io8PT1dBQUF1cY3b96sVq1aBSUoAACCjjnyKiNHjtS4ceO0fft2uVwuHTt2TEuXLtXEiRM1atSoUMQIAIDtbNy4UbfccosyMjLkcrm0cuVKn++HDRsml8vls/Xv3z/g6wTcWp88ebIMw9BNN92ks2fPqkePHnK73Zo4caLGjh0bcAAAANSG2n4gTGlpqTp37qy77rpLgwcPvuA+/fv31+LFi72f3W53wHEFnMhdLpceffRRPfTQQyooKFBJSYnat2+vpKSkgC8OAECtCdJ95MXFxT7Dbrf7ggl4wIABGjBgwI+e0u12Kz093UJQFp7sFh8fr/bt2+u6664jiQMAHCMzM1OpqaneLTc3t8bnWr9+vRo3bqw2bdpo1KhR+vrrrwM+R8AVee/eveVyXXzl3vvvvx9wEAAAhJzVW8i+O/bw4cNKSUnxDtekHS5VtdUHDx6sli1bqrCwUI888ogGDBigrVu3KjY21u/zBJzIu3Tp4vO5srJSu3fv1meffaacnJxATwcAQO0IUms9JSXFJ5HX1O233+79c8eOHdWpUyddccUVWr9+vW666Sa/zxNwIp87d+4Fx2fMmKGSkpJATwcAACS1atVKDRs2VEFBQUCJPGhvP7vzzjv10ksvBet0AAAEV4TfR37kyBF9/fXXatKkSUDHBe3tZ1u3blVCQkKwTgcAQFDV9u1nJSUlPg9Q279/v3bv3q0GDRqoQYMGmjlzpoYMGaL09HQVFhZq0qRJys7OVr9+/QK6TsCJ/If3wpmmqePHj2vHjh2aOnVqoKcDACAq7dixQ7179/Z+njBhgiQpJydHCxcu1KeffqqXX35Zp06dUkZGhvr27avZs2cHvHgu4ESemprq8zkmJkZt2rTRrFmz1Ldv30BPBwBAVOrVq5dM8+Jl/LvvvhuU6wSUyD0ej4YPH66OHTuqfv36QQkAAIBaEaRV65EmoMVusbGx6tu3L285AwDYTrS+xjTgVesdOnTQ559/HopYAABAgAJO5I899pgmTpyo1atX6/jx4youLvbZAACIWBF665kVfs+Rz5o1Sw8++KBuvvlmSdKtt97q86hW0zTlcrnk8XiCHyUAAFZF6Ry534l85syZuvfee/XBBx+EMh4AABAAvxP5+SX0PXv2DFkwAACESm0/EKa2BHT72Y+99QwAgIjm9Na6JLVu3fqSyfzkyZOWAgIAAP4LKJHPnDmz2pPdAACwA1rrqnp3auPGjUMVCwAAoROlrXW/7yNnfhwAgMgT8Kp1AABsKUorcr8TuWEYoYwDAICQYo4cAAA7i9KKPOBnrQMAgMhBRQ4AcIYorchJ5AAAR4jWOXJa6wAA2BgVOQDAGWitAwBgX7TWAQBAxKEiBwA4A611AABsLEoTOa11AABsjIocAOAIru82K8dHIhI5AMAZorS1TiIHADgCt58BAICIQ0UOAHAGWusAANhchCZjK2itAwBgY1TkAABHiNbFbiRyAIAzROkcOa11AABsjIocAOAItNYBALAzWusAACDSUJEDAByB1joAAHYWpa11EjkAwBmiNJEzRw4AgI1RkQMAHIE5cgAA7IzWOgAAiDRU5AAAR3CZplxmzctqK8eGEokcAOAMtNYBAECkoSIHADgCq9YBALAzWusAACDSUJEDAByB1joAAHYWpa11EjkAwBGitSJnjhwAABujIgcAOAOtdQAA7C1S2+NW0FoHAMDGqMgBAM5gmlWbleMjEIkcAOAIrFoHAAARh4ocAOAMrFoHAMC+XEbVZuX4SERrHQAAG6MiR8BuG1OkEY+c0IrnG2rR9KbhDgcI2PJnGuvDd+rpcIFb8QmG2l9zViMePabM7HLvPie/iNMLszO0a2OyzpbEKPOKct0+rkg3/sfpMEYOS6K0tU5FjoC07nxW/3HnSX3+j4RwhwLU2Kdbk3TLsK80b/U+5S4vlOec9MgdV6js7Pf/JT55f3MdLnRrRt5+Pfd+vq6/+bTm/HcLFfw9MYyRw4rzq9atbJEorIl848aNuuWWW5SRkSGXy6WVK1eGMxxcQkIdjx5+9qDmPdRMZ07HhjscoMbmLPtcfX99Ui3alOmKn5TpwXmH9MXReO379Psk/c8ddTXwrq/U9qqzapJVod88UKS6qR6ffWAz5+8jt7IF4FI5zjRNTZs2TU2aNFFiYqL69Omjffv2BfxjhTWRl5aWqnPnzlqwYEE4w4Cfxsw5qo/WpejjTcnhDgUIqtLiql9Mk+t5vGPtrynVhrfrqfibWBmGtH5lPVWUudTpZyXhChM2c6kc98QTT2j+/PlatGiRtm/frrp166pfv34qKysL6DphnSMfMGCABgwY4Pf+5eXlKi//fg6ruLg4FGHhAnoO/EbZHb/V2JuvDHcoQFAZhrRoelP95NoStWj7/X+gjz53UHPuzdL/+UlHxcaZcicamv7iATVtWRHGaGFFsB4I88Pc43a75Xa7q+3/YznONE3NmzdPv/vd7zRw4EBJ0pIlS5SWlqaVK1fq9ttv9zsuW82R5+bmKjU11btlZmaGOyRHaJRRoVGzjul/xjRXZbmt/skAl/TsI810cG+ipiw86DP+8hPpKimO1e9fLdAzf8vXkHu+0OP3ttD+PawPsS0zCJukzMxMn1yUm5sbcCj79+/XiRMn1KdPH+9YamqqunXrpq1btwZ0LlutWp8yZYomTJjg/VxcXEwyrwXZnb5V/UbntODdf3nHYuOkjj8t1a3Dv9J/tugkw3CFMUKgZp59pKm2r03RUysK1Cij0jt+7EC83l7cSM99sFct2lRV6Vf8pEx/356kt/Maatz/HAlXyIgAhw8fVkpKivfzharxSzlx4oQkKS0tzWc8LS3N+52/bJXIL9a+QGjt3pSke3q39hl7cO5hHS5I0GsLGpHEYTumKS14tKm2rEnVk68XKL25b7u8/NuqzlNMjG8fNjbWlBmhDwXBpQWrtZ6SkuKTyMONPiku6dvSWB3MT/TZys7G6Mw3VeOA3Tz7SDO9/2YDTV5wUIlJhk5+EaeTX8Sp/NuqX0ozs8uU0bJcT0/K1N6P6+jYgXi9vqiRdm1M1s/6cx+5bdXyqvUfk56eLkkqKiryGS8qKvJ+5y9bVeQAEAyrX24oSXpoiO/izQfnHlLfX59U3GXSY68U6sU5GZqe01LflsYoo2WFJj59SNfddCYcISPKtGzZUunp6Vq3bp26dOkiqWq6ePv27Ro1alRA5wprIi8pKVFBQYH38/79+7V79241aNBAzZs3D2NkuJRJv8oOdwhAjb17bPcl92naqkLTXjgQ8lhQe2r7NaaXynEPPPCAHnvsMV155ZVq2bKlpk6dqoyMDA0aNCig64Q1ke/YsUO9e/f2fj6/kC0nJ0d5eXlhigoAEJVq+RGtl8pxkyZNUmlpqe655x6dOnVKN9xwg9asWaOEhMDujAhrIu/Vq5fMIM45AAAQKS6V41wul2bNmqVZs2ZZug5z5AAAR6jt1nptIZEDAJzBMKs2K8dHIBI5AMAZeI0pAACINFTkAABHcMniHHnQIgkuEjkAwBmsPp0tQu+yorUOAICNUZEDAByB288AALAzVq0DAIBIQ0UOAHAEl2nKZWHBmpVjQ4lEDgBwBuO7zcrxEYjWOgAANkZFDgBwBFrrAADYWZSuWieRAwCcgSe7AQCASENFDgBwBJ7sBgCAndFaBwAAkYaKHADgCC6jarNyfCQikQMAnIHWOgAAiDRU5AAAZ+CBMAAA2Fe0PqKV1joAADZGRQ4AcIYoXexGIgcAOIMpa+8Uj8w8TiIHADgDc+QAACDiUJEDAJzBlMU58qBFElQkcgCAM0TpYjda6wAA2BgVOQDAGQxJLovHRyASOQDAEVi1DgAAIg4VOQDAGaJ0sRuJHADgDFGayGmtAwBgY1TkAABniNKKnEQOAHAGbj8DAMC+uP0MAABEHCpyAIAzMEcOAICNGabkspCMjchM5LTWAQCwMSpyAIAz0FoHAMDOLCZyRWYip7UOAICNUZEDAJyB1joAADZmmLLUHmfVOgAACDYqcgCAM5hG1Wbl+AhEIgcAOANz5AAA2Bhz5AAAINJQkQMAnIHWOgAANmbKYiIPWiRBRWsdAAAboyIHADgDrXUAAGzMMCRZuBfciMz7yGmtAwBgY1TkAABnoLUOAICNRWkip7UOAICNUZEDAJyBR7QCAGBfpmlY3gIxY8YMuVwun61t27ZB/7moyAEAzmCa1qrqGsyR/+QnP9F7773n/RwXF/y0SyIHACAAxcXFPp/dbrfcbvcF942Li1N6enpI46G1DgBwhvOr1q1skjIzM5WamurdcnNzL3rJffv2KSMjQ61atdLQoUN16NChoP9YVOQAAGcwDMll4els382RHz58WCkpKd7hi1Xj3bp1U15entq0aaPjx49r5syZuvHGG/XZZ58pOTm55nH8AIkcAIAApKSk+CTyixkwYID3z506dVK3bt2UlZWl1157TSNGjAhaPCRyAIAzmBZvP7P4QJh69eqpdevWKigosHSeH2KOHADgCKZhWN6sKCkpUWFhoZo0aRKkn6gKiRwAgBCYOHGiNmzYoAMHDmjLli365S9/qdjYWN1xxx1BvQ6tdQCAM9Rya/3IkSO644479PXXX6tRo0a64YYbtG3bNjVq1KjmMVwAiRwA4AyGKblqL5EvX7685tcKAK11AABsjIocAOAMpinJyn3kkfnSFBI5AMARTMOUaaG1bpLIAQAII9OQtYrc2u1nocIcOQAANkZFDgBwBFrrAADYWZS21m2dyM//dnROlZbu8QciWfGZyPzPAwiG4pKqf9+1Ue1azRXnVBm8YILI1on8zJkzkqTNeifMkQChU791uCMAQu/MmTNKTU0Nybnj4+OVnp6uzSes54r09HTFx8cHIargcZmR2vT3g2EYOnbsmJKTk+VyucIdjiMUFxcrMzOz2vt4gWjAv+/aZ5qmzpw5o4yMDMXEhG79dVlZmSoqKiyfJz4+XgkJCUGIKHhsXZHHxMSoWbNm4Q7Dkfx9Hy9gR/z7rl2hqsT/XUJCQsQl4GDh9jMAAGyMRA4AgI2RyBEQt9ut6dOny+12hzsUIOj49w07svViNwAAnI6KHAAAGyORAwBgYyRyAABsjEQOAICNkcjhtwULFqhFixZKSEhQt27d9NFHH4U7JCAoNm7cqFtuuUUZGRlyuVxauXJluEMC/EYih19effVVTZgwQdOnT9euXbvUuXNn9evXT1988UW4QwMsKy0tVefOnbVgwYJwhwIEjNvP4Jdu3brp2muv1bPPPiup6jn3mZmZGjt2rCZPnhzm6IDgcblcWrFihQYNGhTuUAC/UJHjkioqKrRz50716dPHOxYTE6M+ffpo69atYYwMAEAixyV99dVX8ng8SktL8xlPS0vTiRMnwhQVAEAikQMAYGskclxSw4YNFRsbq6KiIp/xoqIipaenhykqAIBEIocf4uPj1bVrV61bt847ZhiG1q1bp+7du4cxMgBAXLgDgD1MmDBBOTk5uuaaa3Tddddp3rx5Ki0t1fDhw8MdGmBZSUmJCgoKvJ/379+v3bt3q0GDBmrevHkYIwMujdvP4Ldnn31WTz75pE6cOKEuXbpo/vz56tatW7jDAixbv369evfuXW08JydHeXl5tR8QEAASOQAANsYcOQAANkYiBwDAxkjkAADYGIkcAAAbI5EDAGBjJHIAAGyMRA4AgI2RyAEAsDESOWDRsGHDNGjQIO/nXr166YEHHqj1ONavXy+Xy6VTp05ddB+Xy6WVK1f6fc4ZM2aoS5culuI6cOCAXC6Xdu/ebek8AC6MRI6oNGzYMLlcLrlcLsXHxys7O1uzZs3SuXPnQn7tN998U7Nnz/ZrX3+SLwD8GF6agqjVv39/LV68WOXl5XrnnXc0evRoXXbZZZoyZUq1fSsqKhQfHx+U6zZo0CAo5wEAf1CRI2q53W6lp6crKytLo0aNUp8+ffT2229L+r4d/vjjjysjI0Nt2rSRJB0+fFi33Xab6tWrpwYNGmjgwIE6cOCA95wej0cTJkxQvXr1dPnll2vSpEn64esKfthaLy8v18MPP6zMzEy53W5lZ2frxRdf1IEDB7wv6qhfv75cLpeGDRsmqeo1sbm5uWrZsqUSExPVuXNnvf766z7Xeeedd9S6dWslJiaqd+/ePnH66+GHH1br1q1Vp04dtWrVSlOnTlVlZWW1/Z577jllZmaqTp06uu2223T69Gmf71944QW1a9dOCQkJatu2rf70pz8FHAuAmiGRwzESExNVUVHh/bxu3Trl5+dr7dq1Wr16tSorK9WvXz8lJydr06ZN+vDDD5WUlKT+/ft7j3vqqaeUl5enl156SZs3b9bJkye1YsWKH73ub3/7W/3lL3/R/PnztWfPHj333HNKSkpSZmam3njjDUlSfn6+jh8/rqefflqSlJubqyVLlmjRokX6xz/+ofHjx+vOO+/Uhg0bJFX9wjF48GDdcsst2r17t+6++25Nnjw54L+T5ORk5eXl6Z///KeefvppPf/885o7d67PPgUFBXrttde0atUqrVmzRh9//LHuu+8+7/dLly7VtGnT9Pjjj2vPnj2aM2eOpk6dqpdffjngeADUgAlEoZycHHPgwIGmaZqmYRjm2rVrTbfbbU6cONH7fVpamlleXu495pVXXjHbtGljGobhHSsvLzcTExPNd9991zRN02zSpIn5xBNPeL+vrKw0mzVr5r2WaZpmz549zXHjxpmmaZr5+fmmJHPt2rUXjPODDz4wJZnffPONd6ysrMysU6eOuWXLFp99R4wYYd5xxx2maZrmlClTzPbt2/t8//DDD1c71w9JMlesWHHR75988kmza9eu3s/Tp083Y2NjzSNHjnjH/va3v5kxMTHm8ePHTdM0zSuuuMJctmyZz3lmz55tdu/e3TRN09y/f78pyfz4448vel0ANcccOaLW6tWrlZSUpMrKShmGod/85jeaMWOG9/uOHTv6zIt/8sknKigoUHJyss95ysrKVFhYqNOnT+v48eM+72CPi4vTNddcU629ft7u3bsVGxurnj17+h13QUGBzp49q1/84hc+4xUVFbrqqqskSXv27Kn2Lvju3bv7fY3zXn31Vc2fP1+FhYUqKSnRuXPnlJKS4rNP8+bN1bRpU5/rGIah/Px8JScnq7CwUCNGjNDIkSO9+5w7d06pqakBxwMgcCRyRK3evXtr4cKFio+PV0ZGhuLifP+5161b1+dzSUmJunbtqqVLl1Y7V6NGjWoUQ2JiYsDHlJSUSJL++te/+iRQqWreP1i2bt2qoUOHaubMmerXr59SU1O1fPlyPfXUUwHH+vzzz1f7xSI2NjZosQK4OBI5olbdunWVnZ3t9/5XX321Xn31VTVu3LhaVXpekyZNtH37dvXo0UNSVeW5c+dOXX311Rfcv2PHjjIMQxs2bFCfPn2qfX++I+DxeLxj7du3l9vt1qFDhy5aybdr1867cO+8bdu2XfqH/DdbtmxRVlaWHn30Ue/YwYMHq+136NAhHTt2TBkZGd7rxMTEqE2bNkpLS1NGRoY+//xzDR06NKDrAwgOFrsB3xk6dKgaNmyogQMHatOmTdq/f7/Wr1+v+++/X0eOHJEkjRs3Tr///e+1cuVK7d27V/fdd9+P3gPeokUL5eTk6K677tLKlSu953zttdckSVlZWXK5XFq9erW+/PJLlZSUKDk5WRMnTtT48eP18ssvq7CwULt27dIzzzzjXUB27733at++fXrooYeUn5+vZcuWKS8vL6Cf98orr9ShQ4e0fPlyFRYWav78+RdcuJeQkKCcnBx98skn2rRpk+6//37ddtttSk9PlyTNnDlTubm5mj9/vv71r3/p73//uxYvXqw//vGPAcUDoGZI5MB36tSpo40bN6p58+YaPHiw2rVrpxEjRqisrMxboT/44IP6r//6L+Xk5Kh79+5KTk7WL3/5yx8978KFC/WrX/1K9913n9q2bauRI0eqtLRUktS0aVPNnDlTkydPVlpamsaMGSNJmj17tqZOnarc3Fy1a9dO/fv311//+le1bNlSUtW89RtvvKGVK1eqc+fOWrRokebMmRPQz3vrrbdq/PjxGjNmjLp06aItW7Zo6tSp1fbLzs7W4MGDdfPNN6tv377q1KmTz+1ld999t1544QUtXrxYHTt2VM+ePZWXl+eNFUBoucyLrdIBAAARj4ocAAAbI5EDAGBjJHIAAGyMRA4AgI2RyAEAsDESOQAANkYiBwDAxkjkAADYGIkcAAAbI5EDAGBjJHIAAGzs/wO6q5mICsZrGgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
    "\n",
    "cm = confusion_matrix(y_test, y_pred, labels=clf.classes_)\n",
    "\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=clf.classes_)\n",
    "\n",
    "disp.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8d094bb9-25a7-470b-9a10-c7ef73add3dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ROC = RocCurveDisplay.from_predictions(y_test, y_pred)\n",
    "plt.savefig('roc_curve.png')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fad13093-7006-40c6-81d2-03d5d57f7834",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b6aff27-183c-49f9-8ae7-58b818e0d742",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1cbfba7-b7dc-4c7b-845d-9ffe4a4f7855",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "079d8e15-9a12-4ac0-91fe-0a70e91819be",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "357b5b51-c31b-4027-9b5e-3628774a66fc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d84678d-13d6-4dc2-9c4b-1bd7dc1f1d61",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c978b0ab-436a-4498-b73f-f9d5fb89c064",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d953cb55-b213-44e1-b975-b8ed65dd7f7b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bf252bd-4288-4cd5-9b9d-306d690299b8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e0859ac-e99b-40fb-8adb-6e2c30c44e5e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6275b66c-24b2-4756-b1f4-279da2941077",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d1ca078-0731-4b58-807d-f7e7e983d33b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d8a773d-1b4f-4594-a66e-4bd349cc6219",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4db8595a-205a-4653-8cca-cc7884754512",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5f6607df-f303-4eac-882c-4f6b22af630c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "508cb767-0f6e-4cd1-9f60-a0f1ff3bf36e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0605c69-f302-4142-9969-5098c93f2290",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2800ddc-d66e-49dd-9dc9-13aa4169efb9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ded04742-2f85-43b8-82bf-7a39018f010a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "865b3b96-6127-4639-84b2-ad0b5d299671",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "325e3058-5904-4c45-ba2c-f15fe9769d4e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "188a8e89-f2d9-4652-ba8d-57dba903e37f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08a878ec-bc87-4489-866b-17814cca5522",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1315b3c0-d066-46a8-b7c8-a0885aba44b6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55c541eb-7f88-4078-a7cd-7daea14791fc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d63caecd-ec88-4431-bf6b-ece43aec582e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd643f6e-4a61-4cc3-8337-3994c34ea3ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f241faa7-96cd-4da8-8614-772bf13d33cb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03257eae-2925-4700-93ba-828c1963f939",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a55456d-38c5-443a-ab21-9f23c27b1707",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
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}