GaussianDiscriminantAnalysisApplication.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gaussian Discriminant Analysis Applications"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to learn about Gaussian Discriminant Analysis, read [this](https://github.com/tugrulhkarabulut/Gaussian-Discriminant-Analysis/blob/master/GaussianDiscriminantAnalysisApplication.pdf)\n",
    "\n",
    "Also, you can check out my implementation of the algorithm from [here](https://github.com/tugrulhkarabulut/Gaussian-Discriminant-Analysis/blob/master/GaussianDiscriminantAnalysis.py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from GaussianDiscriminantAnalysis import LinearDiscriminantAnalysis, QuadraticDiscriminantAnalysis\n",
    "# Check the GaussianDiscriminantAnalysis.py for implementations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_test_split(X, ratio):\n",
    "    X_shuffled = np.copy(X)\n",
    "    np.random.shuffle(X_shuffled)\n",
    "    return X_shuffled[:int(len(X_shuffled) * ratio)], X_shuffled[int(len(X_shuffled) * ratio):]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 70: expected 25 fields, saw 26\\nSkipping line 73: expected 25 fields, saw 26\\nSkipping line 370: expected 25 fields, saw 26\\n'\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "    Dataset is from the UCI Machine Learning Repository\n",
    "    https://archive.ics.uci.edu/ml/datasets/Chronic_Kidney_Disease\n",
    "\"\"\"\n",
    "df = pd.read_csv('chronic_kidney_disease.csv', header = None, error_bad_lines=False)\n",
    "df.columns = [\n",
    "    'age',\n",
    "    'bp',\n",
    "    'sp',\n",
    "    'al',\n",
    "    'su',\n",
    "    'rbc',\n",
    "    'pc',\n",
    "    'pcc',\n",
    "    'ba',\n",
    "    'bgr',\n",
    "    'bu',\n",
    "    'sc',\n",
    "    'sod',\n",
    "    'pot',\n",
    "    'hemo',\n",
    "    'pcv',\n",
    "    'wc',\n",
    "    'rc',\n",
    "    'htn',\n",
    "    'dm',\n",
    "    'cad',\n",
    "    'appet',\n",
    "    'pe',\n",
    "    'ane',\n",
    "    'class'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "      <td>4</td>\n",
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       "      <td>normal</td>\n",
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       "      <td>notpresent</td>\n",
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       "      <td>35</td>\n",
       "      <td>7300</td>\n",
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       "      <td>normal</td>\n",
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       "      <td>0</td>\n",
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       "      <td>normal</td>\n",
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       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
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       "      <td>notpresent</td>\n",
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       "      <td>49</td>\n",
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       "      <td>normal</td>\n",
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       "      <td>7200</td>\n",
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       "      <td>notckd</td>\n",
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       "      <td>58</td>\n",
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       "      <td>0</td>\n",
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       "<p>397 rows × 25 columns</p>\n",
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      ],
      "text/plain": [
       "    age  bp     sp al su     rbc        pc         pcc          ba  bgr  ...  \\\n",
       "0    48  80  1.020  1  0       ?    normal  notpresent  notpresent  121  ...   \n",
       "1     7  50  1.020  4  0       ?    normal  notpresent  notpresent    ?  ...   \n",
       "2    62  80  1.010  2  3  normal    normal  notpresent  notpresent  423  ...   \n",
       "3    48  70  1.005  4  0  normal  abnormal     present  notpresent  117  ...   \n",
       "4    51  80  1.010  2  0  normal    normal  notpresent  notpresent  106  ...   \n",
       "..   ..  ..    ... .. ..     ...       ...         ...         ...  ...  ...   \n",
       "392  55  80  1.020  0  0  normal    normal  notpresent  notpresent  140  ...   \n",
       "393  42  70  1.025  0  0  normal    normal  notpresent  notpresent   75  ...   \n",
       "394  12  80  1.020  0  0  normal    normal  notpresent  notpresent  100  ...   \n",
       "395  17  60  1.025  0  0  normal    normal  notpresent  notpresent  114  ...   \n",
       "396  58  80  1.025  0  0  normal    normal  notpresent  notpresent  131  ...   \n",
       "\n",
       "    pcv    wc   rc  htn   dm cad appet   pe  ane   class  \n",
       "0    44  7800  5.2  yes  yes  no  good   no   no     ckd  \n",
       "1    38  6000    ?   no   no  no  good   no   no     ckd  \n",
       "2    31  7500    ?   no  yes  no  poor   no  yes     ckd  \n",
       "3    32  6700  3.9  yes   no  no  poor  yes  yes     ckd  \n",
       "4    35  7300  4.6   no   no  no  good   no   no     ckd  \n",
       "..   ..   ...  ...  ...  ...  ..   ...  ...  ...     ...  \n",
       "392  47  6700  4.9   no   no  no  good   no   no  notckd  \n",
       "393  54  7800  6.2   no   no  no  good   no   no  notckd  \n",
       "394  49  6600  5.4   no   no  no  good   no   no  notckd  \n",
       "395  51  7200  5.9   no   no  no  good   no   no  notckd  \n",
       "396  53  6800  6.1   no   no  no  good   no   no  notckd  \n",
       "\n",
       "[397 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
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       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>ckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>61</td>\n",
       "      <td>80</td>\n",
       "      <td>1.015</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>abnormal</td>\n",
       "      <td>abnormal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>173</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>9200</td>\n",
       "      <td>3.2</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>poor</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>ckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>55</td>\n",
       "      <td>80</td>\n",
       "      <td>1.020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>6700</td>\n",
       "      <td>4.9</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>good</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>notckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>42</td>\n",
       "      <td>70</td>\n",
       "      <td>1.025</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>75</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>7800</td>\n",
       "      <td>6.2</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>good</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>notckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>12</td>\n",
       "      <td>80</td>\n",
       "      <td>1.020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>49</td>\n",
       "      <td>6600</td>\n",
       "      <td>5.4</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>good</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>notckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>17</td>\n",
       "      <td>60</td>\n",
       "      <td>1.025</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>114</td>\n",
       "      <td>...</td>\n",
       "      <td>51</td>\n",
       "      <td>7200</td>\n",
       "      <td>5.9</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>good</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>notckd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>58</td>\n",
       "      <td>80</td>\n",
       "      <td>1.025</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>normal</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>notpresent</td>\n",
       "      <td>131</td>\n",
       "      <td>...</td>\n",
       "      <td>53</td>\n",
       "      <td>6800</td>\n",
       "      <td>6.1</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>good</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>notckd</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    age  bp     sp al su       rbc        pc         pcc          ba  bgr  \\\n",
       "3    48  70  1.005  4  0    normal  abnormal     present  notpresent  117   \n",
       "9    53  90  1.020  2  0  abnormal  abnormal     present  notpresent   70   \n",
       "11   63  70  1.010  3  0  abnormal  abnormal     present  notpresent  380   \n",
       "14   68  80  1.010  3  2    normal  abnormal     present     present  157   \n",
       "20   61  80  1.015  2  0  abnormal  abnormal  notpresent  notpresent  173   \n",
       "..   ..  ..    ... .. ..       ...       ...         ...         ...  ...   \n",
       "392  55  80  1.020  0  0    normal    normal  notpresent  notpresent  140   \n",
       "393  42  70  1.025  0  0    normal    normal  notpresent  notpresent   75   \n",
       "394  12  80  1.020  0  0    normal    normal  notpresent  notpresent  100   \n",
       "395  17  60  1.025  0  0    normal    normal  notpresent  notpresent  114   \n",
       "396  58  80  1.025  0  0    normal    normal  notpresent  notpresent  131   \n",
       "\n",
       "     ... pcv     wc   rc  htn   dm  cad appet   pe  ane   class  \n",
       "3    ...  32   6700  3.9  yes   no   no  poor  yes  yes     ckd  \n",
       "9    ...  29  12100  3.7  yes  yes   no  poor   no  yes     ckd  \n",
       "11   ...  32   4500  3.8  yes  yes   no  poor  yes   no     ckd  \n",
       "14   ...  16  11000  2.6  yes  yes  yes  poor  yes   no     ckd  \n",
       "20   ...  24   9200  3.2  yes  yes  yes  poor  yes  yes     ckd  \n",
       "..   ...  ..    ...  ...  ...  ...  ...   ...  ...  ...     ...  \n",
       "392  ...  47   6700  4.9   no   no   no  good   no   no  notckd  \n",
       "393  ...  54   7800  6.2   no   no   no  good   no   no  notckd  \n",
       "394  ...  49   6600  5.4   no   no   no  good   no   no  notckd  \n",
       "395  ...  51   7200  5.9   no   no   no  good   no   no  notckd  \n",
       "396  ...  53   6800  6.1   no   no   no  good   no   no  notckd  \n",
       "\n",
       "[157 rows x 25 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.replace({'?': np.nan}, inplace=True)\n",
    "df.dropna(inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age'] = df['age'].astype('int')\n",
    "df['bp'] = df['bp'].astype('int')\n",
    "df['pcv'] = df['pcv'].astype('int')\n",
    "df['wc'] = df['wc'].astype('int')\n",
    "df['rc'] = df['rc'].astype('float')\n",
    "\n",
    "df['class'] = df['class'].astype('category')\n",
    "df['class'] = df['class'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\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>bp</th>\n",
       "      <th>pcv</th>\n",
       "      <th>wc</th>\n",
       "      <th>rc</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.00000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>49.401274</td>\n",
       "      <td>74.076433</td>\n",
       "      <td>41.891720</td>\n",
       "      <td>8464.33121</td>\n",
       "      <td>4.892357</td>\n",
       "      <td>0.726115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15.427190</td>\n",
       "      <td>11.206421</td>\n",
       "      <td>9.128414</td>\n",
       "      <td>3133.46316</td>\n",
       "      <td>1.022600</td>\n",
       "      <td>0.447378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3800.00000</td>\n",
       "      <td>2.100000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>6500.00000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>7800.00000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>60.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>9700.00000</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>83.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>26400.00000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age          bp         pcv           wc          rc       class\n",
       "count  157.000000  157.000000  157.000000    157.00000  157.000000  157.000000\n",
       "mean    49.401274   74.076433   41.891720   8464.33121    4.892357    0.726115\n",
       "std     15.427190   11.206421    9.128414   3133.46316    1.022600    0.447378\n",
       "min      6.000000   50.000000    9.000000   3800.00000    2.100000    0.000000\n",
       "25%     39.000000   60.000000   37.000000   6500.00000    4.500000    0.000000\n",
       "50%     50.000000   80.000000   44.000000   7800.00000    5.000000    1.000000\n",
       "75%     60.000000   80.000000   48.000000   9700.00000    5.600000    1.000000\n",
       "max     83.000000  110.000000   54.000000  26400.00000    8.000000    1.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\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>age</th>\n",
       "      <th>bp</th>\n",
       "      <th>pcv</th>\n",
       "      <th>wc</th>\n",
       "      <th>rc</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.084286</td>\n",
       "      <td>-0.242078</td>\n",
       "      <td>0.148446</td>\n",
       "      <td>-0.243401</td>\n",
       "      <td>-0.314621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bp</th>\n",
       "      <td>0.084286</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.352838</td>\n",
       "      <td>0.009644</td>\n",
       "      <td>-0.228845</td>\n",
       "      <td>-0.325676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pcv</th>\n",
       "      <td>-0.242078</td>\n",
       "      <td>-0.352838</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.351894</td>\n",
       "      <td>0.739774</td>\n",
       "      <td>0.827751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wc</th>\n",
       "      <td>0.148446</td>\n",
       "      <td>0.009644</td>\n",
       "      <td>-0.351894</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.272358</td>\n",
       "      <td>-0.410786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rc</th>\n",
       "      <td>-0.243401</td>\n",
       "      <td>-0.228845</td>\n",
       "      <td>0.739774</td>\n",
       "      <td>-0.272358</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.721208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <td>-0.314621</td>\n",
       "      <td>-0.325676</td>\n",
       "      <td>0.827751</td>\n",
       "      <td>-0.410786</td>\n",
       "      <td>0.721208</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            age        bp       pcv        wc        rc     class\n",
       "age    1.000000  0.084286 -0.242078  0.148446 -0.243401 -0.314621\n",
       "bp     0.084286  1.000000 -0.352838  0.009644 -0.228845 -0.325676\n",
       "pcv   -0.242078 -0.352838  1.000000 -0.351894  0.739774  0.827751\n",
       "wc     0.148446  0.009644 -0.351894  1.000000 -0.272358 -0.410786\n",
       "rc    -0.243401 -0.228845  0.739774 -0.272358  1.000000  0.721208\n",
       "class -0.314621 -0.325676  0.827751 -0.410786  0.721208  1.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = df[['age', 'wc', 'rc', 'class']].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data, test_data = train_test_split(data, ratio=0.8)\n",
    "\n",
    "X_train = train_data[:, :3]\n",
    "y_train = train_data[:, -1]\n",
    "\n",
    "X_test = test_data[:, :3]\n",
    "y_test = test_data[:, -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_linear = LinearDiscriminantAnalysis()\n",
    "model_linear.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model_linear.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1,\n",
       "       1, 1, 0, 1, 1, 0, 1, 1, 1, 1])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 7)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test==0].size, y_pred[y_pred == 0].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23, 25)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test==1].size, y_pred[y_pred == 1].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9375"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test == y_pred].size / y_test.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_quad = QuadraticDiscriminantAnalysis()\n",
    "model_quad.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model_quad.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 8)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test==0].size, y_pred[y_pred == 0].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23, 24)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test==1].size, y_pred[y_pred == 1].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.96875"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test == y_pred].size / y_test.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .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>STG</th>\n",
       "      <th>SCG</th>\n",
       "      <th>STR</th>\n",
       "      <th>LPR</th>\n",
       "      <th>PEG</th>\n",
       "      <th>UNS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>very_low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.08</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.90</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.33</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.10</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.30</td>\n",
       "      <td>Middle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.08</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.24</td>\n",
       "      <td>Low</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>0.61</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.58</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>0.78</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.60</td>\n",
       "      <td>Middle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>0.54</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.77</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.26</td>\n",
       "      <td>Middle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>0.66</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.74</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>258 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      STG   SCG   STR   LPR   PEG       UNS\n",
       "0    0.00  0.00  0.00  0.00  0.00  very_low\n",
       "1    0.08  0.08  0.10  0.24  0.90      High\n",
       "2    0.06  0.06  0.05  0.25  0.33       Low\n",
       "3    0.10  0.10  0.15  0.65  0.30    Middle\n",
       "4    0.08  0.08  0.08  0.98  0.24       Low\n",
       "..    ...   ...   ...   ...   ...       ...\n",
       "253  0.61  0.78  0.69  0.92  0.58      High\n",
       "254  0.78  0.61  0.71  0.19  0.60    Middle\n",
       "255  0.54  0.82  0.71  0.29  0.77      High\n",
       "256  0.50  0.75  0.81  0.61  0.26    Middle\n",
       "257  0.66  0.90  0.76  0.87  0.74      High\n",
       "\n",
       "[258 rows x 6 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "    Dataset is from the UCI Machine Learning Repository\n",
    "    https://archive.ics.uci.edu/ml/datasets/User+Knowledge+Modeling\n",
    "\"\"\"\n",
    "df_exam = pd.read_excel('exam_data_.xls')\n",
    "df_exam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_exam.columns = ['STG', 'SCG', 'STR', 'LPR', 'PEG', 'UNS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_exam['UNS'] = df_exam['UNS'].astype('category')\n",
    "df_exam['UNS'] = df_exam['UNS'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\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>STG</th>\n",
       "      <th>SCG</th>\n",
       "      <th>STR</th>\n",
       "      <th>LPR</th>\n",
       "      <th>PEG</th>\n",
       "      <th>UNS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>STG</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.081035</td>\n",
       "      <td>0.040841</td>\n",
       "      <td>0.099543</td>\n",
       "      <td>0.206359</td>\n",
       "      <td>-0.074570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SCG</th>\n",
       "      <td>0.081035</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.083732</td>\n",
       "      <td>0.097816</td>\n",
       "      <td>0.182792</td>\n",
       "      <td>-0.210050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STR</th>\n",
       "      <td>0.040841</td>\n",
       "      <td>0.083732</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.036481</td>\n",
       "      <td>0.120779</td>\n",
       "      <td>-0.060510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LPR</th>\n",
       "      <td>0.099543</td>\n",
       "      <td>0.097816</td>\n",
       "      <td>0.036481</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.269574</td>\n",
       "      <td>-0.263670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEG</th>\n",
       "      <td>0.206359</td>\n",
       "      <td>0.182792</td>\n",
       "      <td>0.120779</td>\n",
       "      <td>-0.269574</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.488249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNS</th>\n",
       "      <td>-0.074570</td>\n",
       "      <td>-0.210050</td>\n",
       "      <td>-0.060510</td>\n",
       "      <td>-0.263670</td>\n",
       "      <td>-0.488249</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          STG       SCG       STR       LPR       PEG       UNS\n",
       "STG  1.000000  0.081035  0.040841  0.099543  0.206359 -0.074570\n",
       "SCG  0.081035  1.000000  0.083732  0.097816  0.182792 -0.210050\n",
       "STR  0.040841  0.083732  1.000000  0.036481  0.120779 -0.060510\n",
       "LPR  0.099543  0.097816  0.036481  1.000000 -0.269574 -0.263670\n",
       "PEG  0.206359  0.182792  0.120779 -0.269574  1.000000 -0.488249\n",
       "UNS -0.074570 -0.210050 -0.060510 -0.263670 -0.488249  1.000000"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_exam.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = df_exam[['STG', 'SCG', 'STR', 'LPR', 'PEG', 'UNS']].values\n",
    "\n",
    "train_data, test_data = train_test_split(data, ratio=0.8)\n",
    "\n",
    "X_train = train_data[:, :-1]\n",
    "y_train = train_data[:, -1]\n",
    "\n",
    "X_test = test_data[:, :-1]\n",
    "y_test = test_data[:, -1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "GDA makes stronger modeling assumptions about the data than does logistic regression. It turns out that when these modeling assumptions are correct, then GDA will find better fits to the data, and is a better model. Specifically, when $p(x|y)$ is indeed gaussian (with shared Σ), then GDA is asymptotically efficient.\n",
    "If we see the distributions of $p(x|y)$ for all classes for y, we will have a better perspective."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n",
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "pxydf = {}\n",
    "pxydf[3] = df_exam[df_exam['UNS'] == 3]\n",
    "del pxydf[3]['UNS']\n",
    "pxydf[2] = df_exam[df_exam['UNS']== 2]\n",
    "del pxydf[2]['UNS']\n",
    "pxydf[1] = df_exam[df_exam['UNS']== 1]\n",
    "del pxydf[1]['UNS']\n",
    "pxydf[0] = df_exam[df_exam['UNS']== 0]\n",
    "del pxydf[0]['UNS']\n",
    "\n",
    "for j in range(len(pxydf)): \n",
    "    i=1\n",
    "    fig = plt.figure(figsize=(15,15))\n",
    "    for columns in pxydf[i].columns:\n",
    "        fig.add_subplot(3,2,i)\n",
    "        i = i+1\n",
    "        fig.set_figheight(15)\n",
    "        fig.set_figwidth(15)\n",
    "        sns.distplot(pxydf[j][[columns]], hist=False, rug=True)\n",
    "        plt.title(columns+str(i))\n",
    "        plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_exam = LinearDiscriminantAnalysis()\n",
    "model_exam.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model_exam.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9230769230769231"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_pred == y_test].size / y_test.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_quad = QuadraticDiscriminantAnalysis()\n",
    "model_quad.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model_quad.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9615384615384616"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[y_test == y_pred].size / y_test.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}