Hepatitis_SVM_V2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hepatitis C Detection dengan Support Vector Machine"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.kaggle.com/datasets/fedesoriano/hepatitis-c-dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec \n",
    "from matplotlib.animation import FuncAnimation\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import timeit\n",
    "\n",
    "from sklearn.model_selection import KFold # Library untuk penerapan KFold Validation\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import cross_val_score # Library untuk menampilkan nilai pengujian Cross Validation (nilai return nya berupa array)\n",
    "from sklearn.model_selection import cross_validate # ...\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import GridSearchCV, RandomizedSearchCV\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import confusion_matrix, classification_report # Menampilkan hasil tes\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Memanggil Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Category</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6.93</td>\n",
       "      <td>3.23</td>\n",
       "      <td>106.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>69.0</td>\n",
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       "      <td>70.3</td>\n",
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       "      <td>24.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>11.17</td>\n",
       "      <td>4.80</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>76.5</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>46.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>36.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.84</td>\n",
       "      <td>5.20</td>\n",
       "      <td>86.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>79.3</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>43.2</td>\n",
       "      <td>52.0</td>\n",
       "      <td>30.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>7.33</td>\n",
       "      <td>4.74</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33.8</td>\n",
       "      <td>75.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>39.2</td>\n",
       "      <td>74.1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.15</td>\n",
       "      <td>4.32</td>\n",
       "      <td>76.0</td>\n",
       "      <td>29.9</td>\n",
       "      <td>68.7</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>611</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>62</td>\n",
       "      <td>f</td>\n",
       "      <td>32.0</td>\n",
       "      <td>416.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>110.3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>5.57</td>\n",
       "      <td>6.30</td>\n",
       "      <td>55.7</td>\n",
       "      <td>650.9</td>\n",
       "      <td>68.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>612</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>f</td>\n",
       "      <td>24.0</td>\n",
       "      <td>102.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>44.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.54</td>\n",
       "      <td>3.02</td>\n",
       "      <td>63.0</td>\n",
       "      <td>35.9</td>\n",
       "      <td>71.3</td>\n",
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       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>613</td>\n",
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       "      <td>64</td>\n",
       "      <td>f</td>\n",
       "      <td>29.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>99.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>3.63</td>\n",
       "      <td>66.7</td>\n",
       "      <td>64.2</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>614</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>46</td>\n",
       "      <td>f</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.56</td>\n",
       "      <td>4.20</td>\n",
       "      <td>52.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>615</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>59</td>\n",
       "      <td>f</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.07</td>\n",
       "      <td>5.30</td>\n",
       "      <td>67.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>615 rows × 14 columns</p>\n",
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      ],
      "text/plain": [
       "     Unnamed: 0       Category  Age Sex   ALB    ALP    ALT    AST   BIL  \\\n",
       "0             1  0=Blood Donor   32   m  38.5   52.5    7.7   22.1   7.5   \n",
       "1             2  0=Blood Donor   32   m  38.5   70.3   18.0   24.7   3.9   \n",
       "2             3  0=Blood Donor   32   m  46.9   74.7   36.2   52.6   6.1   \n",
       "3             4  0=Blood Donor   32   m  43.2   52.0   30.6   22.6  18.9   \n",
       "4             5  0=Blood Donor   32   m  39.2   74.1   32.6   24.8   9.6   \n",
       "..          ...            ...  ...  ..   ...    ...    ...    ...   ...   \n",
       "610         611    3=Cirrhosis   62   f  32.0  416.6    5.9  110.3  50.0   \n",
       "611         612    3=Cirrhosis   64   f  24.0  102.8    2.9   44.4  20.0   \n",
       "612         613    3=Cirrhosis   64   f  29.0   87.3    3.5   99.0  48.0   \n",
       "613         614    3=Cirrhosis   46   f  33.0    NaN   39.0   62.0  20.0   \n",
       "614         615    3=Cirrhosis   59   f  36.0    NaN  100.0   80.0  12.0   \n",
       "\n",
       "       CHE  CHOL   CREA    GGT  PROT  \n",
       "0     6.93  3.23  106.0   12.1  69.0  \n",
       "1    11.17  4.80   74.0   15.6  76.5  \n",
       "2     8.84  5.20   86.0   33.2  79.3  \n",
       "3     7.33  4.74   80.0   33.8  75.7  \n",
       "4     9.15  4.32   76.0   29.9  68.7  \n",
       "..     ...   ...    ...    ...   ...  \n",
       "610   5.57  6.30   55.7  650.9  68.5  \n",
       "611   1.54  3.02   63.0   35.9  71.3  \n",
       "612   1.66  3.63   66.7   64.2  82.0  \n",
       "613   3.56  4.20   52.0   50.0  71.0  \n",
       "614   9.07  5.30   67.0   34.0  68.0  \n",
       "\n",
       "[615 rows x 14 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis = pd.read_csv('data/HepatitisCdata.csv')\n",
    "Hepatitis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Mengcopy Dataset ke variabel baru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
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       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
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       "      <td>9.6</td>\n",
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       "      <td>63.0</td>\n",
       "      <td>35.9</td>\n",
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       "      <td>99.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>3.63</td>\n",
       "      <td>66.7</td>\n",
       "      <td>64.2</td>\n",
       "      <td>82.0</td>\n",
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       "      <th>613</th>\n",
       "      <td>614</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>46</td>\n",
       "      <td>f</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>4.20</td>\n",
       "      <td>52.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>71.0</td>\n",
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       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>615</td>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>59</td>\n",
       "      <td>f</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.07</td>\n",
       "      <td>5.30</td>\n",
       "      <td>67.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>68.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>615 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0       Category  Age Sex   ALB    ALP    ALT    AST   BIL  \\\n",
       "0             1  0=Blood Donor   32   m  38.5   52.5    7.7   22.1   7.5   \n",
       "1             2  0=Blood Donor   32   m  38.5   70.3   18.0   24.7   3.9   \n",
       "2             3  0=Blood Donor   32   m  46.9   74.7   36.2   52.6   6.1   \n",
       "3             4  0=Blood Donor   32   m  43.2   52.0   30.6   22.6  18.9   \n",
       "4             5  0=Blood Donor   32   m  39.2   74.1   32.6   24.8   9.6   \n",
       "..          ...            ...  ...  ..   ...    ...    ...    ...   ...   \n",
       "610         611    3=Cirrhosis   62   f  32.0  416.6    5.9  110.3  50.0   \n",
       "611         612    3=Cirrhosis   64   f  24.0  102.8    2.9   44.4  20.0   \n",
       "612         613    3=Cirrhosis   64   f  29.0   87.3    3.5   99.0  48.0   \n",
       "613         614    3=Cirrhosis   46   f  33.0    NaN   39.0   62.0  20.0   \n",
       "614         615    3=Cirrhosis   59   f  36.0    NaN  100.0   80.0  12.0   \n",
       "\n",
       "       CHE  CHOL   CREA    GGT  PROT  \n",
       "0     6.93  3.23  106.0   12.1  69.0  \n",
       "1    11.17  4.80   74.0   15.6  76.5  \n",
       "2     8.84  5.20   86.0   33.2  79.3  \n",
       "3     7.33  4.74   80.0   33.8  75.7  \n",
       "4     9.15  4.32   76.0   29.9  68.7  \n",
       "..     ...   ...    ...    ...   ...  \n",
       "610   5.57  6.30   55.7  650.9  68.5  \n",
       "611   1.54  3.02   63.0   35.9  71.3  \n",
       "612   1.66  3.63   66.7   64.2  82.0  \n",
       "613   3.56  4.20   52.0   50.0  71.0  \n",
       "614   9.07  5.30   67.0   34.0  68.0  \n",
       "\n",
       "[615 rows x 14 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Copy\n",
    "Hepatitis1 = Hepatitis.copy()\n",
    "Hepatitis1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualisasi Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1440 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = Hepatitis1.copy()\n",
    "fig = plt.figure(figsize = (24,24), dpi = 60)\n",
    "gs = GridSpec(ncols=13, nrows=29, left=0.05, right=0.5, wspace=0.2, hspace=0.1)\n",
    "fig.patch.set_facecolor('#f5f5f5')\n",
    "sns.set_palette(sns.color_palette(['green','purple', 'orange', 'red']))\n",
    "\n",
    "ax1 = fig.add_subplot(gs[:5, :5])\n",
    "ax2 = fig.add_subplot(gs[:5, 8:])\n",
    "ax3 = fig.add_subplot(gs[8:13, :5])\n",
    "ax4 = fig.add_subplot(gs[8:13, 8:])\n",
    "ax5 = fig.add_subplot(gs[16:21, :5])\n",
    "ax6 = fig.add_subplot(gs[16:21, 8:])\n",
    "ax7 = fig.add_subplot(gs[24:, :5])\n",
    "ax8 = fig.add_subplot(gs[24:, 8:])\n",
    "\n",
    "\n",
    "# axes list\n",
    "axes = [ ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8]\n",
    "\n",
    "\n",
    "for ax in axes:\n",
    "    ax.set_facecolor('#f5f5f5')\n",
    "    ax.grid()\n",
    "    \n",
    "    for loc in ['right', 'top']:\n",
    "        ax.spines[loc].set_visible(False)\n",
    "        \n",
    "\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax1 Age v CHE\n",
    "sns.scatterplot(x='Age', y='CHE', hue='Category', data=data, ax=ax1, s=100, alpha=0.75, legend=None)\n",
    "ax1.set_title('Age v CHE', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax2 ALB v ALP\n",
    "sns.scatterplot(x='ALB', y='ALP', hue='Category', data=data, ax=ax2, s=100, alpha=0.75, legend=None)\n",
    "ax2.set_title('ALB v ALP', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax2.set_xlim(10, 70)\n",
    "ax2.set_ylim(0,200)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax3 ALB v CHE\n",
    "sns.scatterplot(x='ALB', y='CHE', hue='Category', data=data, ax=ax3, s=100, alpha=0.75, legend=None)\n",
    "ax3.set_title('ALB v CHE', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax3.set_xlim(10, 70)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax4 ALB v CHOL\n",
    "sns.scatterplot(x='ALB', y='CHOL', hue='Category', data=data, ax=ax4, s=100, alpha=0.75, legend=None)\n",
    "ax4.set_title('ALB v CHOL', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax4.set_xlim(10, 70)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax5 ALP v CHE\n",
    "sns.scatterplot(x='ALP', y='CHE', hue='Category', data=data, ax=ax5, s=100, alpha=0.75, legend=None)\n",
    "ax5.set_title('ALP v CHE', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax5.set_xlim(0, 200)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax6 ALP v CHOL\n",
    "sns.scatterplot(x='ALP', y='CHOL', hue='Category', data=data, ax=ax6, s=100, alpha=0.75, legend=None)\n",
    "ax6.set_title('ALP v CHOL', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax6.set_xlim(0, 200)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax7 ALT v AST\n",
    "sns.scatterplot(x='ALT', y='AST', hue='Category', data=data, ax=ax7, s=100, alpha=0.75, legend=None)\n",
    "ax7.set_title('ALT v AST', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "ax7.set_xlim(0, 175)\n",
    "#-------------------------------------------------------------------------------\n",
    "#ax8 AST v BIL\n",
    "sns.scatterplot(x='AST', y='BIL', hue='Category', data=data, ax=ax8, s=100, alpha=0.75, legend=None)\n",
    "ax8.set_title('ALT v AST', {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "#ax8.set_xlim(0, 175)\n",
    "\n",
    "\n",
    "#-------------------------------------------\n",
    "fig.text(0.1 + 0.04, 0.95, \"Healthy\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'green', 'size':20})\n",
    "fig.text(0.155 + 0.04, 0.95, \"|\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'black', 'size':20})\n",
    "fig.text(0.165 + 0.04, 0.95, \"Hepatitis\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'purple', 'size':20})\n",
    "fig.text(0.23 + 0.04, 0.95, \"|\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'black', 'size':20})\n",
    "fig.text(0.24 + 0.04, 0.95, \"Fibrosis\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'orange', 'size':20})\n",
    "fig.text(0.295 + 0.04, 0.95, \"|\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'black', 'size':20})\n",
    "fig.text(0.305 + 0.04, 0.95, \"Cirrhosis\", \n",
    "         {'font':'Serif', 'weight':'bold','color': 'red', 'size':20})\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = Hepatitis1.copy()\n",
    "fig = plt.figure(figsize = (24,10), dpi = 60)\n",
    "gs = GridSpec(ncols=13, nrows=5, left=0.05, right=0.5, wspace=0.2, hspace=0.1)\n",
    "fig.patch.set_facecolor('#f5f5f5')\n",
    "sns.set_palette(sns.color_palette(['green','purple', 'orange', 'red']))\n",
    "\n",
    "ax1 = fig.add_subplot(gs[:, 0:5])\n",
    "ax2 = fig.add_subplot(gs[:, 8:])\n",
    "\n",
    "axes = [ ax1,ax2]\n",
    "\n",
    "for ax in axes:\n",
    "    ax.axes.get_yaxis().set_visible(False)\n",
    "    ax.set_facecolor('#f5f5f5')\n",
    "    \n",
    "    for loc in ['left', 'right', 'top', 'bottom']:\n",
    "        ax.spines[loc].set_visible(False)\n",
    "\n",
    "#------------------------------------------------------------    \n",
    "#ax1\n",
    "ax1_plot = ax1.pie(data[data.Sex == 'm'].groupby('Category').Category.count().values, \n",
    "                    labels=data.groupby('Category').Category.count().index,\n",
    "                    autopct='%1.1f%%', explode=[0.3,  0.4, 0.1, 0.2, 0.1], \n",
    "                    colors=['orange', 'red', 'green', 'purple'])\n",
    "\n",
    "for piece in ax1_plot[0]:\n",
    "    piece.set_alpha(0.5)\n",
    "\n",
    "for i, text in enumerate(ax1_plot[1]):\n",
    "    text.set_weight('bold')\n",
    "    text.set_size(14)\n",
    "\n",
    "for i, text in enumerate(ax1_plot[2]):\n",
    "    text.set_weight('bold')\n",
    "    text.set_size(12)\n",
    "\n",
    "    \n",
    "fig.text(0.1, 0.75, 'Laki-Laki',  {'font':'Serif', 'weight':'bold','color': 'black', 'size':25})\n",
    "#------------------------------------------------------------    \n",
    "#ax2\n",
    "ax2_plot = ax2.pie(data[data.Sex == 'f'].groupby('Category').Category.count().values, \n",
    "                    labels=data.groupby('Category').Category.count().index,\n",
    "                    autopct='%1.1f%%', explode=[0.3,  0.4, 0.1, 0.2,0.1], \n",
    "                    colors=['orange', 'red', 'green', 'purple'])\n",
    "\n",
    "for piece in ax2_plot[0]:\n",
    "    piece.set_alpha(0.5)\n",
    "\n",
    "for i, text in enumerate(ax2_plot[1]):\n",
    "    text.set_weight('bold')\n",
    "    text.set_size(14)\n",
    "\n",
    "for i, text in enumerate(ax2_plot[2]):\n",
    "    text.set_weight('bold')\n",
    "    text.set_size(12)\n",
    "\n",
    "fig.text(0.38, 0.75, 'Perempuan',  {'font':'Serif', 'weight':'bold','color': 'black', 'size':25}) \n",
    "#--------------------------------\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>Category</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6.93</td>\n",
       "      <td>3.23</td>\n",
       "      <td>106.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>38.5</td>\n",
       "      <td>70.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>11.17</td>\n",
       "      <td>4.80</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>76.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>46.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>36.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.84</td>\n",
       "      <td>5.20</td>\n",
       "      <td>86.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>79.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>43.2</td>\n",
       "      <td>52.0</td>\n",
       "      <td>30.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>7.33</td>\n",
       "      <td>4.74</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33.8</td>\n",
       "      <td>75.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>39.2</td>\n",
       "      <td>74.1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.15</td>\n",
       "      <td>4.32</td>\n",
       "      <td>76.0</td>\n",
       "      <td>29.9</td>\n",
       "      <td>68.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>62</td>\n",
       "      <td>f</td>\n",
       "      <td>32.0</td>\n",
       "      <td>416.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>110.3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>5.57</td>\n",
       "      <td>6.30</td>\n",
       "      <td>55.7</td>\n",
       "      <td>650.9</td>\n",
       "      <td>68.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>f</td>\n",
       "      <td>24.0</td>\n",
       "      <td>102.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>44.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.54</td>\n",
       "      <td>3.02</td>\n",
       "      <td>63.0</td>\n",
       "      <td>35.9</td>\n",
       "      <td>71.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>f</td>\n",
       "      <td>29.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>99.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>3.63</td>\n",
       "      <td>66.7</td>\n",
       "      <td>64.2</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>46</td>\n",
       "      <td>f</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.56</td>\n",
       "      <td>4.20</td>\n",
       "      <td>52.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>3=Cirrhosis</td>\n",
       "      <td>59</td>\n",
       "      <td>f</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.07</td>\n",
       "      <td>5.30</td>\n",
       "      <td>67.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>615 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Category  Age Sex   ALB    ALP    ALT    AST   BIL    CHE  CHOL  \\\n",
       "0    0=Blood Donor   32   m  38.5   52.5    7.7   22.1   7.5   6.93  3.23   \n",
       "1    0=Blood Donor   32   m  38.5   70.3   18.0   24.7   3.9  11.17  4.80   \n",
       "2    0=Blood Donor   32   m  46.9   74.7   36.2   52.6   6.1   8.84  5.20   \n",
       "3    0=Blood Donor   32   m  43.2   52.0   30.6   22.6  18.9   7.33  4.74   \n",
       "4    0=Blood Donor   32   m  39.2   74.1   32.6   24.8   9.6   9.15  4.32   \n",
       "..             ...  ...  ..   ...    ...    ...    ...   ...    ...   ...   \n",
       "610    3=Cirrhosis   62   f  32.0  416.6    5.9  110.3  50.0   5.57  6.30   \n",
       "611    3=Cirrhosis   64   f  24.0  102.8    2.9   44.4  20.0   1.54  3.02   \n",
       "612    3=Cirrhosis   64   f  29.0   87.3    3.5   99.0  48.0   1.66  3.63   \n",
       "613    3=Cirrhosis   46   f  33.0    NaN   39.0   62.0  20.0   3.56  4.20   \n",
       "614    3=Cirrhosis   59   f  36.0    NaN  100.0   80.0  12.0   9.07  5.30   \n",
       "\n",
       "      CREA    GGT  PROT  \n",
       "0    106.0   12.1  69.0  \n",
       "1     74.0   15.6  76.5  \n",
       "2     86.0   33.2  79.3  \n",
       "3     80.0   33.8  75.7  \n",
       "4     76.0   29.9  68.7  \n",
       "..     ...    ...   ...  \n",
       "610   55.7  650.9  68.5  \n",
       "611   63.0   35.9  71.3  \n",
       "612   66.7   64.2  82.0  \n",
       "613   52.0   50.0  71.0  \n",
       "614   67.0   34.0  68.0  \n",
       "\n",
       "[615 rows x 13 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Hapus kolom unnamed, karena tidak digunakan\n",
    "Hepatitis1 = Hepatitis1.drop(columns = 'Unnamed: 0')\n",
    "Hepatitis1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(615, 13)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 615 entries, 0 to 614\n",
      "Data columns (total 13 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   Category  615 non-null    object \n",
      " 1   Age       615 non-null    int64  \n",
      " 2   Sex       615 non-null    object \n",
      " 3   ALB       614 non-null    float64\n",
      " 4   ALP       597 non-null    float64\n",
      " 5   ALT       614 non-null    float64\n",
      " 6   AST       615 non-null    float64\n",
      " 7   BIL       615 non-null    float64\n",
      " 8   CHE       615 non-null    float64\n",
      " 9   CHOL      605 non-null    float64\n",
      " 10  CREA      615 non-null    float64\n",
      " 11  GGT       615 non-null    float64\n",
      " 12  PROT      614 non-null    float64\n",
      "dtypes: float64(10), int64(1), object(2)\n",
      "memory usage: 62.6+ KB\n"
     ]
    }
   ],
   "source": [
    "Hepatitis1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\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>Category</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6.93</td>\n",
       "      <td>3.23</td>\n",
       "      <td>106.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>38.5</td>\n",
       "      <td>70.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>11.17</td>\n",
       "      <td>4.80</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>76.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>46.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>36.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.84</td>\n",
       "      <td>5.20</td>\n",
       "      <td>86.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>79.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>43.2</td>\n",
       "      <td>52.0</td>\n",
       "      <td>30.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>7.33</td>\n",
       "      <td>4.74</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33.8</td>\n",
       "      <td>75.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0=Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>m</td>\n",
       "      <td>39.2</td>\n",
       "      <td>74.1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.15</td>\n",
       "      <td>4.32</td>\n",
       "      <td>76.0</td>\n",
       "      <td>29.9</td>\n",
       "      <td>68.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category  Age Sex   ALB   ALP   ALT   AST   BIL    CHE  CHOL   CREA  \\\n",
       "0  0=Blood Donor   32   m  38.5  52.5   7.7  22.1   7.5   6.93  3.23  106.0   \n",
       "1  0=Blood Donor   32   m  38.5  70.3  18.0  24.7   3.9  11.17  4.80   74.0   \n",
       "2  0=Blood Donor   32   m  46.9  74.7  36.2  52.6   6.1   8.84  5.20   86.0   \n",
       "3  0=Blood Donor   32   m  43.2  52.0  30.6  22.6  18.9   7.33  4.74   80.0   \n",
       "4  0=Blood Donor   32   m  39.2  74.1  32.6  24.8   9.6   9.15  4.32   76.0   \n",
       "\n",
       "    GGT  PROT  \n",
       "0  12.1  69.0  \n",
       "1  15.6  76.5  \n",
       "2  33.2  79.3  \n",
       "3  33.8  75.7  \n",
       "4  29.9  68.7  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Memisah kolom category "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "Hepatitis1[[\"Label\", \"Category\"]] = (  \n",
    "    Hepatitis1[\"Category\"]           \n",
    "    .str                         \n",
    "    .split(\"=\", expand=True)                               \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Mengubah nilai pad fitur 'Sex' menjadi 1 untuk male dan 0 untuk female"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>Category</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6.93</td>\n",
       "      <td>3.23</td>\n",
       "      <td>106.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>38.5</td>\n",
       "      <td>70.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>11.17</td>\n",
       "      <td>4.80</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>76.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>46.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>36.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.84</td>\n",
       "      <td>5.20</td>\n",
       "      <td>86.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>79.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>43.2</td>\n",
       "      <td>52.0</td>\n",
       "      <td>30.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>7.33</td>\n",
       "      <td>4.74</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33.8</td>\n",
       "      <td>75.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>39.2</td>\n",
       "      <td>74.1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.15</td>\n",
       "      <td>4.32</td>\n",
       "      <td>76.0</td>\n",
       "      <td>29.9</td>\n",
       "      <td>68.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>416.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>110.3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>5.57</td>\n",
       "      <td>6.30</td>\n",
       "      <td>55.7</td>\n",
       "      <td>650.9</td>\n",
       "      <td>68.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>102.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>44.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.54</td>\n",
       "      <td>3.02</td>\n",
       "      <td>63.0</td>\n",
       "      <td>35.9</td>\n",
       "      <td>71.3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>99.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>3.63</td>\n",
       "      <td>66.7</td>\n",
       "      <td>64.2</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.56</td>\n",
       "      <td>4.20</td>\n",
       "      <td>52.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.07</td>\n",
       "      <td>5.30</td>\n",
       "      <td>67.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>615 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category  Age  Sex   ALB    ALP    ALT    AST   BIL    CHE  CHOL  \\\n",
       "0    Blood Donor   32    1  38.5   52.5    7.7   22.1   7.5   6.93  3.23   \n",
       "1    Blood Donor   32    1  38.5   70.3   18.0   24.7   3.9  11.17  4.80   \n",
       "2    Blood Donor   32    1  46.9   74.7   36.2   52.6   6.1   8.84  5.20   \n",
       "3    Blood Donor   32    1  43.2   52.0   30.6   22.6  18.9   7.33  4.74   \n",
       "4    Blood Donor   32    1  39.2   74.1   32.6   24.8   9.6   9.15  4.32   \n",
       "..           ...  ...  ...   ...    ...    ...    ...   ...    ...   ...   \n",
       "610    Cirrhosis   62    0  32.0  416.6    5.9  110.3  50.0   5.57  6.30   \n",
       "611    Cirrhosis   64    0  24.0  102.8    2.9   44.4  20.0   1.54  3.02   \n",
       "612    Cirrhosis   64    0  29.0   87.3    3.5   99.0  48.0   1.66  3.63   \n",
       "613    Cirrhosis   46    0  33.0    NaN   39.0   62.0  20.0   3.56  4.20   \n",
       "614    Cirrhosis   59    0  36.0    NaN  100.0   80.0  12.0   9.07  5.30   \n",
       "\n",
       "      CREA    GGT  PROT Label  \n",
       "0    106.0   12.1  69.0     0  \n",
       "1     74.0   15.6  76.5     0  \n",
       "2     86.0   33.2  79.3     0  \n",
       "3     80.0   33.8  75.7     0  \n",
       "4     76.0   29.9  68.7     0  \n",
       "..     ...    ...   ...   ...  \n",
       "610   55.7  650.9  68.5     3  \n",
       "611   63.0   35.9  71.3     3  \n",
       "612   66.7   64.2  82.0     3  \n",
       "613   52.0   50.0  71.0     3  \n",
       "614   67.0   34.0  68.0     3  \n",
       "\n",
       "[615 rows x 14 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1 = Hepatitis1.replace({'Sex' : {'m': 1, 'f': 0}})\n",
    "Hepatitis1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Category     0\n",
       "Age          0\n",
       "Sex          0\n",
       "ALB          1\n",
       "ALP         18\n",
       "ALT          1\n",
       "AST          0\n",
       "BIL          0\n",
       "CHE          0\n",
       "CHOL        10\n",
       "CREA         0\n",
       "GGT          0\n",
       "PROT         1\n",
       "Label        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">Menghapus data yang terdapat nilai null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>Category</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ALB</th>\n",
       "      <th>ALP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AST</th>\n",
       "      <th>BIL</th>\n",
       "      <th>CHE</th>\n",
       "      <th>CHOL</th>\n",
       "      <th>CREA</th>\n",
       "      <th>GGT</th>\n",
       "      <th>PROT</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6.93</td>\n",
       "      <td>3.23</td>\n",
       "      <td>106.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>38.5</td>\n",
       "      <td>70.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>11.17</td>\n",
       "      <td>4.80</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>76.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>46.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>36.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.84</td>\n",
       "      <td>5.20</td>\n",
       "      <td>86.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>79.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>43.2</td>\n",
       "      <td>52.0</td>\n",
       "      <td>30.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>7.33</td>\n",
       "      <td>4.74</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33.8</td>\n",
       "      <td>75.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Blood Donor</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>39.2</td>\n",
       "      <td>74.1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.15</td>\n",
       "      <td>4.32</td>\n",
       "      <td>76.0</td>\n",
       "      <td>29.9</td>\n",
       "      <td>68.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>46.4</td>\n",
       "      <td>15.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.26</td>\n",
       "      <td>3.98</td>\n",
       "      <td>56.0</td>\n",
       "      <td>49.7</td>\n",
       "      <td>80.6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>51.3</td>\n",
       "      <td>19.6</td>\n",
       "      <td>285.8</td>\n",
       "      <td>40.0</td>\n",
       "      <td>5.77</td>\n",
       "      <td>4.51</td>\n",
       "      <td>136.1</td>\n",
       "      <td>101.1</td>\n",
       "      <td>70.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>416.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>110.3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>5.57</td>\n",
       "      <td>6.30</td>\n",
       "      <td>55.7</td>\n",
       "      <td>650.9</td>\n",
       "      <td>68.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>102.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>44.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.54</td>\n",
       "      <td>3.02</td>\n",
       "      <td>63.0</td>\n",
       "      <td>35.9</td>\n",
       "      <td>71.3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>Cirrhosis</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>99.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>3.63</td>\n",
       "      <td>66.7</td>\n",
       "      <td>64.2</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>589 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category  Age  Sex   ALB    ALP   ALT    AST   BIL    CHE  CHOL  \\\n",
       "0    Blood Donor   32    1  38.5   52.5   7.7   22.1   7.5   6.93  3.23   \n",
       "1    Blood Donor   32    1  38.5   70.3  18.0   24.7   3.9  11.17  4.80   \n",
       "2    Blood Donor   32    1  46.9   74.7  36.2   52.6   6.1   8.84  5.20   \n",
       "3    Blood Donor   32    1  43.2   52.0  30.6   22.6  18.9   7.33  4.74   \n",
       "4    Blood Donor   32    1  39.2   74.1  32.6   24.8   9.6   9.15  4.32   \n",
       "..           ...  ...  ...   ...    ...   ...    ...   ...    ...   ...   \n",
       "608    Cirrhosis   58    0  34.0   46.4  15.0  150.0   8.0   6.26  3.98   \n",
       "609    Cirrhosis   59    0  39.0   51.3  19.6  285.8  40.0   5.77  4.51   \n",
       "610    Cirrhosis   62    0  32.0  416.6   5.9  110.3  50.0   5.57  6.30   \n",
       "611    Cirrhosis   64    0  24.0  102.8   2.9   44.4  20.0   1.54  3.02   \n",
       "612    Cirrhosis   64    0  29.0   87.3   3.5   99.0  48.0   1.66  3.63   \n",
       "\n",
       "      CREA    GGT  PROT Label  \n",
       "0    106.0   12.1  69.0     0  \n",
       "1     74.0   15.6  76.5     0  \n",
       "2     86.0   33.2  79.3     0  \n",
       "3     80.0   33.8  75.7     0  \n",
       "4     76.0   29.9  68.7     0  \n",
       "..     ...    ...   ...   ...  \n",
       "608   56.0   49.7  80.6     3  \n",
       "609  136.1  101.1  70.5     3  \n",
       "610   55.7  650.9  68.5     3  \n",
       "611   63.0   35.9  71.3     3  \n",
       "612   66.7   64.2  82.0     3  \n",
       "\n",
       "[589 rows x 14 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1.dropna(inplace=True)\n",
    "Hepatitis1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Category    0\n",
       "Age         0\n",
       "Sex         0\n",
       "ALB         0\n",
       "ALP         0\n",
       "ALT         0\n",
       "AST         0\n",
       "BIL         0\n",
       "CHE         0\n",
       "CHOL        0\n",
       "CREA        0\n",
       "GGT         0\n",
       "PROT        0\n",
       "Label       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hepatitis1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = Hepatitis1.drop(['Category','Label'], axis=1)\n",
    "y = Hepatitis1['Category']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Untuk mengambil nilai dari masing-masing fold, maka menggunakan *cross_val_score*. Parameter sebagai berikut :\n",
    "* estimator : metode klasifikasi yang digunakan untuk memprediksi\n",
    "* x : fitur\n",
    "* y : kelas\n",
    "* scoring : nilai yang digunakan sebagai pengukuran evaluasi, diantaranya \"accuracy\", \"precision\", \"recall\"\n",
    "* cv : metode cross validation yang digunakan\n",
    "\n",
    "---\n",
    "Sumber :\n",
    "* https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_score.html\n",
    "* https://scikit-learn.org/stable/modules/model_evaluation.html\n",
    "\n",
    "*KFold* merupakan library yang digunakan untuk menguji klasifikasi menggunakan metode Cross Validation. Parameter yang digunakan sebagai berikut :\n",
    "* n_split : total fold yang digunakan; default = 5\n",
    "* shuffle : parameter apakah setiap fold diacak atau tidak; default = False\n",
    "* random_state : digunakan apabila shuffle = True, sebagai penanda *randomness* dari setiap fold, jika tidak diisi bisa mengakibatkan nilai akurasi berubah setiap kali running\n",
    "\n",
    "---\n",
    "Sumber : https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = timeit.default_timer()\n",
    "# define kfold for cross validation\n",
    "kfold = KFold(n_splits=5, shuffle=True, random_state=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Klasifikasi SVM menggunakan Cross Validation\n",
    "svm = SVC()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# membagi data menjadi data training:testing\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nilai akurasi tiap fold: [0.94736842 0.92553191 0.92553191 0.92553191 0.88297872]\n",
      "Nilai akurasi rata-rata: 0.9213885778275476\n"
     ]
    }
   ],
   "source": [
    "cv_score_svm = cross_val_score(svm, X_train, y_train, cv=kfold, scoring=\"accuracy\")\n",
    "\n",
    "print('Nilai akurasi tiap fold: {}'.format(cv_score_svm))\n",
    "print('Nilai akurasi rata-rata: {}'.format(cv_score_svm.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameter terbaik: {'kernel': 'linear'} \n",
      "dengan nilai akurasi pada data training: 0.9426203807390816\n"
     ]
    }
   ],
   "source": [
    "\n",
    "params = {\n",
    "        'kernel': ['linear', 'poly', 'rbf']\n",
    "        }\n",
    "\n",
    "svm_classifierCV = GridSearchCV(SVC(), params, cv= kfold, scoring= 'accuracy')\n",
    "svm_classifierCV.fit(X_train,y_train)\n",
    "\n",
    "# print parameter terbaik\n",
    "print('Parameter terbaik: {0} \\ndengan nilai akurasi pada data training: {1}'.format(svm_classifierCV.best_params_, svm_classifierCV.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     precision    recall  f1-score   support\n",
      "\n",
      "        Blood Donor       0.98      1.00      0.99       109\n",
      "          Cirrhosis       0.67      0.67      0.67         3\n",
      "           Fibrosis       0.00      0.00      0.00         2\n",
      "          Hepatitis       0.00      0.00      0.00         2\n",
      "suspect Blood Donor       0.00      0.00      0.00         2\n",
      "\n",
      "           accuracy                           0.94       118\n",
      "          macro avg       0.33      0.33      0.33       118\n",
      "       weighted avg       0.92      0.94      0.93       118\n",
      "\n",
      "Waktu eksekusi:  1.254171260000021\n"
     ]
    }
   ],
   "source": [
    "pred = svm_classifierCV.predict(X_test)\n",
    "print(classification_report(y_test, pred))\n",
    "stop = timeit.default_timer()\n",
    "print('Waktu eksekusi: ', stop - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Repeated holdout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     precision    recall  f1-score   support\n",
      "\n",
      "        Blood Donor       0.97      1.00      0.99       109\n",
      "          Cirrhosis       0.67      0.67      0.67         3\n",
      "           Fibrosis       0.00      0.00      0.00         2\n",
      "          Hepatitis       0.00      0.00      0.00         2\n",
      "suspect Blood Donor       0.00      0.00      0.00         2\n",
      "\n",
      "           accuracy                           0.94       118\n",
      "          macro avg       0.33      0.33      0.33       118\n",
      "       weighted avg       0.92      0.94      0.93       118\n",
      "\n",
      "Waktu eksekusi:  0.030251782000050298\n"
     ]
    }
   ],
   "source": [
    "start2 = timeit.default_timer()\n",
    "svm = SVC()\n",
    "# untuk melakukan training, data harus disesuaikan dengan model, hal ini bisa dilakukan dengan menggunakan metode .fit (berlaku untuk semua model)\n",
    "svm.fit(X_train, y_train)\n",
    "\n",
    "# untuk mengetahui confusion matrix, bisa menggunakan library classification report dengan sebelumnya melakukan proses prediksi menggunakan metode .predict\n",
    "predict = svm.predict(X_test)\n",
    "print(classification_report(y_test, predict))\n",
    "stop2 = timeit.default_timer()\n",
    "print('Waktu eksekusi: ', stop2 - start2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = SVC(C=0.1, kernel='linear')\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "# Membuat prediksi\n",
    "predictions = model.predict(X_test)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[109,   0,   0,   0,   0],\n",
       "       [  0,   2,   1,   0,   0],\n",
       "       [  0,   0,   1,   1,   0],\n",
       "       [  0,   1,   0,   1,   0],\n",
       "       [  2,   0,   0,   0,   0]])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm = confusion_matrix(y_test, predictions)\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm, annot=True, cmap=\"viridis\" ,fmt='g')\n",
    "plt.title('Confusion matrix')\n",
    "plt.xlabel('Actual label')\n",
    "plt.ylabel('Predicted label')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
  },
  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}