 Parkinson's Disease Detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2b19841f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn import svm\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "156bec93",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading the data to csv file to pandas Dataframe\n",
    "parkinsons_data = pd.read_csv('parkinsons.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8b3b40cc",
   "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>name</th>\n",
       "      <th>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>...</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>status</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>phon_R01_S01_1</td>\n",
       "      <td>119.992</td>\n",
       "      <td>157.302</td>\n",
       "      <td>74.997</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.00007</td>\n",
       "      <td>0.00370</td>\n",
       "      <td>0.00554</td>\n",
       "      <td>0.01109</td>\n",
       "      <td>0.04374</td>\n",
       "      <td>...</td>\n",
       "      <td>0.06545</td>\n",
       "      <td>0.02211</td>\n",
       "      <td>21.033</td>\n",
       "      <td>1</td>\n",
       "      <td>0.414783</td>\n",
       "      <td>0.815285</td>\n",
       "      <td>-4.813031</td>\n",
       "      <td>0.266482</td>\n",
       "      <td>2.301442</td>\n",
       "      <td>0.284654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>phon_R01_S01_2</td>\n",
       "      <td>122.400</td>\n",
       "      <td>148.650</td>\n",
       "      <td>113.819</td>\n",
       "      <td>0.00968</td>\n",
       "      <td>0.00008</td>\n",
       "      <td>0.00465</td>\n",
       "      <td>0.00696</td>\n",
       "      <td>0.01394</td>\n",
       "      <td>0.06134</td>\n",
       "      <td>...</td>\n",
       "      <td>0.09403</td>\n",
       "      <td>0.01929</td>\n",
       "      <td>19.085</td>\n",
       "      <td>1</td>\n",
       "      <td>0.458359</td>\n",
       "      <td>0.819521</td>\n",
       "      <td>-4.075192</td>\n",
       "      <td>0.335590</td>\n",
       "      <td>2.486855</td>\n",
       "      <td>0.368674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>phon_R01_S01_3</td>\n",
       "      <td>116.682</td>\n",
       "      <td>131.111</td>\n",
       "      <td>111.555</td>\n",
       "      <td>0.01050</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>0.00544</td>\n",
       "      <td>0.00781</td>\n",
       "      <td>0.01633</td>\n",
       "      <td>0.05233</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08270</td>\n",
       "      <td>0.01309</td>\n",
       "      <td>20.651</td>\n",
       "      <td>1</td>\n",
       "      <td>0.429895</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>-4.443179</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>2.342259</td>\n",
       "      <td>0.332634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>phon_R01_S01_4</td>\n",
       "      <td>116.676</td>\n",
       "      <td>137.871</td>\n",
       "      <td>111.366</td>\n",
       "      <td>0.00997</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>0.00502</td>\n",
       "      <td>0.00698</td>\n",
       "      <td>0.01505</td>\n",
       "      <td>0.05492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08771</td>\n",
       "      <td>0.01353</td>\n",
       "      <td>20.644</td>\n",
       "      <td>1</td>\n",
       "      <td>0.434969</td>\n",
       "      <td>0.819235</td>\n",
       "      <td>-4.117501</td>\n",
       "      <td>0.334147</td>\n",
       "      <td>2.405554</td>\n",
       "      <td>0.368975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>phon_R01_S01_5</td>\n",
       "      <td>116.014</td>\n",
       "      <td>141.781</td>\n",
       "      <td>110.655</td>\n",
       "      <td>0.01284</td>\n",
       "      <td>0.00011</td>\n",
       "      <td>0.00655</td>\n",
       "      <td>0.00908</td>\n",
       "      <td>0.01966</td>\n",
       "      <td>0.06425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.10470</td>\n",
       "      <td>0.01767</td>\n",
       "      <td>19.649</td>\n",
       "      <td>1</td>\n",
       "      <td>0.417356</td>\n",
       "      <td>0.823484</td>\n",
       "      <td>-3.747787</td>\n",
       "      <td>0.234513</td>\n",
       "      <td>2.332180</td>\n",
       "      <td>0.410335</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             name  MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
       "0  phon_R01_S01_1      119.992       157.302        74.997         0.00784   \n",
       "1  phon_R01_S01_2      122.400       148.650       113.819         0.00968   \n",
       "2  phon_R01_S01_3      116.682       131.111       111.555         0.01050   \n",
       "3  phon_R01_S01_4      116.676       137.871       111.366         0.00997   \n",
       "4  phon_R01_S01_5      116.014       141.781       110.655         0.01284   \n",
       "\n",
       "   MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  ...  \\\n",
       "0           0.00007   0.00370   0.00554     0.01109       0.04374  ...   \n",
       "1           0.00008   0.00465   0.00696     0.01394       0.06134  ...   \n",
       "2           0.00009   0.00544   0.00781     0.01633       0.05233  ...   \n",
       "3           0.00009   0.00502   0.00698     0.01505       0.05492  ...   \n",
       "4           0.00011   0.00655   0.00908     0.01966       0.06425  ...   \n",
       "\n",
       "   Shimmer:DDA      NHR     HNR  status      RPDE       DFA   spread1  \\\n",
       "0      0.06545  0.02211  21.033       1  0.414783  0.815285 -4.813031   \n",
       "1      0.09403  0.01929  19.085       1  0.458359  0.819521 -4.075192   \n",
       "2      0.08270  0.01309  20.651       1  0.429895  0.825288 -4.443179   \n",
       "3      0.08771  0.01353  20.644       1  0.434969  0.819235 -4.117501   \n",
       "4      0.10470  0.01767  19.649       1  0.417356  0.823484 -3.747787   \n",
       "\n",
       "    spread2        D2       PPE  \n",
       "0  0.266482  2.301442  0.284654  \n",
       "1  0.335590  2.486855  0.368674  \n",
       "2  0.311173  2.342259  0.332634  \n",
       "3  0.334147  2.405554  0.368975  \n",
       "4  0.234513  2.332180  0.410335  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parkinsons_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "309a3365",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(195, 24)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of rows and column\n",
    "parkinsons_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4fc4821b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 195 entries, 0 to 194\n",
      "Data columns (total 24 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   name              195 non-null    object \n",
      " 1   MDVP:Fo(Hz)       195 non-null    float64\n",
      " 2   MDVP:Fhi(Hz)      195 non-null    float64\n",
      " 3   MDVP:Flo(Hz)      195 non-null    float64\n",
      " 4   MDVP:Jitter(%)    195 non-null    float64\n",
      " 5   MDVP:Jitter(Abs)  195 non-null    float64\n",
      " 6   MDVP:RAP          195 non-null    float64\n",
      " 7   MDVP:PPQ          195 non-null    float64\n",
      " 8   Jitter:DDP        195 non-null    float64\n",
      " 9   MDVP:Shimmer      195 non-null    float64\n",
      " 10  MDVP:Shimmer(dB)  195 non-null    float64\n",
      " 11  Shimmer:APQ3      195 non-null    float64\n",
      " 12  Shimmer:APQ5      195 non-null    float64\n",
      " 13  MDVP:APQ          195 non-null    float64\n",
      " 14  Shimmer:DDA       195 non-null    float64\n",
      " 15  NHR               195 non-null    float64\n",
      " 16  HNR               195 non-null    float64\n",
      " 17  status            195 non-null    int64  \n",
      " 18  RPDE              195 non-null    float64\n",
      " 19  DFA               195 non-null    float64\n",
      " 20  spread1           195 non-null    float64\n",
      " 21  spread2           195 non-null    float64\n",
      " 22  D2                195 non-null    float64\n",
      " 23  PPE               195 non-null    float64\n",
      "dtypes: float64(22), int64(1), object(1)\n",
      "memory usage: 36.7+ KB\n"
     ]
    }
   ],
   "source": [
    "#getting more information about datasets\n",
    "parkinsons_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "aa4c69a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name                0\n",
       "MDVP:Fo(Hz)         0\n",
       "MDVP:Fhi(Hz)        0\n",
       "MDVP:Flo(Hz)        0\n",
       "MDVP:Jitter(%)      0\n",
       "MDVP:Jitter(Abs)    0\n",
       "MDVP:RAP            0\n",
       "MDVP:PPQ            0\n",
       "Jitter:DDP          0\n",
       "MDVP:Shimmer        0\n",
       "MDVP:Shimmer(dB)    0\n",
       "Shimmer:APQ3        0\n",
       "Shimmer:APQ5        0\n",
       "MDVP:APQ            0\n",
       "Shimmer:DDA         0\n",
       "NHR                 0\n",
       "HNR                 0\n",
       "status              0\n",
       "RPDE                0\n",
       "DFA                 0\n",
       "spread1             0\n",
       "spread2             0\n",
       "D2                  0\n",
       "PPE                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for missing value in each some\n",
    "parkinsons_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "536adb10",
   "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>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>MDVP:Shimmer(dB)</th>\n",
       "      <th>...</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>status</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>154.228641</td>\n",
       "      <td>197.104918</td>\n",
       "      <td>116.324631</td>\n",
       "      <td>0.006220</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>0.003306</td>\n",
       "      <td>0.003446</td>\n",
       "      <td>0.009920</td>\n",
       "      <td>0.029709</td>\n",
       "      <td>0.282251</td>\n",
       "      <td>...</td>\n",
       "      <td>0.046993</td>\n",
       "      <td>0.024847</td>\n",
       "      <td>21.885974</td>\n",
       "      <td>0.753846</td>\n",
       "      <td>0.498536</td>\n",
       "      <td>0.718099</td>\n",
       "      <td>-5.684397</td>\n",
       "      <td>0.226510</td>\n",
       "      <td>2.381826</td>\n",
       "      <td>0.206552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>41.390065</td>\n",
       "      <td>91.491548</td>\n",
       "      <td>43.521413</td>\n",
       "      <td>0.004848</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.002968</td>\n",
       "      <td>0.002759</td>\n",
       "      <td>0.008903</td>\n",
       "      <td>0.018857</td>\n",
       "      <td>0.194877</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030459</td>\n",
       "      <td>0.040418</td>\n",
       "      <td>4.425764</td>\n",
       "      <td>0.431878</td>\n",
       "      <td>0.103942</td>\n",
       "      <td>0.055336</td>\n",
       "      <td>1.090208</td>\n",
       "      <td>0.083406</td>\n",
       "      <td>0.382799</td>\n",
       "      <td>0.090119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>88.333000</td>\n",
       "      <td>102.145000</td>\n",
       "      <td>65.476000</td>\n",
       "      <td>0.001680</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000680</td>\n",
       "      <td>0.000920</td>\n",
       "      <td>0.002040</td>\n",
       "      <td>0.009540</td>\n",
       "      <td>0.085000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013640</td>\n",
       "      <td>0.000650</td>\n",
       "      <td>8.441000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.256570</td>\n",
       "      <td>0.574282</td>\n",
       "      <td>-7.964984</td>\n",
       "      <td>0.006274</td>\n",
       "      <td>1.423287</td>\n",
       "      <td>0.044539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>117.572000</td>\n",
       "      <td>134.862500</td>\n",
       "      <td>84.291000</td>\n",
       "      <td>0.003460</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.001860</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.016505</td>\n",
       "      <td>0.148500</td>\n",
       "      <td>...</td>\n",
       "      <td>0.024735</td>\n",
       "      <td>0.005925</td>\n",
       "      <td>19.198000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.421306</td>\n",
       "      <td>0.674758</td>\n",
       "      <td>-6.450096</td>\n",
       "      <td>0.174351</td>\n",
       "      <td>2.099125</td>\n",
       "      <td>0.137451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>148.790000</td>\n",
       "      <td>175.829000</td>\n",
       "      <td>104.315000</td>\n",
       "      <td>0.004940</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.002500</td>\n",
       "      <td>0.002690</td>\n",
       "      <td>0.007490</td>\n",
       "      <td>0.022970</td>\n",
       "      <td>0.221000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038360</td>\n",
       "      <td>0.011660</td>\n",
       "      <td>22.085000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.495954</td>\n",
       "      <td>0.722254</td>\n",
       "      <td>-5.720868</td>\n",
       "      <td>0.218885</td>\n",
       "      <td>2.361532</td>\n",
       "      <td>0.194052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>182.769000</td>\n",
       "      <td>224.205500</td>\n",
       "      <td>140.018500</td>\n",
       "      <td>0.007365</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>0.003835</td>\n",
       "      <td>0.003955</td>\n",
       "      <td>0.011505</td>\n",
       "      <td>0.037885</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.060795</td>\n",
       "      <td>0.025640</td>\n",
       "      <td>25.075500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.587562</td>\n",
       "      <td>0.761881</td>\n",
       "      <td>-5.046192</td>\n",
       "      <td>0.279234</td>\n",
       "      <td>2.636456</td>\n",
       "      <td>0.252980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>260.105000</td>\n",
       "      <td>592.030000</td>\n",
       "      <td>239.170000</td>\n",
       "      <td>0.033160</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>0.021440</td>\n",
       "      <td>0.019580</td>\n",
       "      <td>0.064330</td>\n",
       "      <td>0.119080</td>\n",
       "      <td>1.302000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.169420</td>\n",
       "      <td>0.314820</td>\n",
       "      <td>33.047000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.685151</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>-2.434031</td>\n",
       "      <td>0.450493</td>\n",
       "      <td>3.671155</td>\n",
       "      <td>0.527367</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
       "count   195.000000    195.000000    195.000000      195.000000   \n",
       "mean    154.228641    197.104918    116.324631        0.006220   \n",
       "std      41.390065     91.491548     43.521413        0.004848   \n",
       "min      88.333000    102.145000     65.476000        0.001680   \n",
       "25%     117.572000    134.862500     84.291000        0.003460   \n",
       "50%     148.790000    175.829000    104.315000        0.004940   \n",
       "75%     182.769000    224.205500    140.018500        0.007365   \n",
       "max     260.105000    592.030000    239.170000        0.033160   \n",
       "\n",
       "       MDVP:Jitter(Abs)    MDVP:RAP    MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
       "count        195.000000  195.000000  195.000000  195.000000    195.000000   \n",
       "mean           0.000044    0.003306    0.003446    0.009920      0.029709   \n",
       "std            0.000035    0.002968    0.002759    0.008903      0.018857   \n",
       "min            0.000007    0.000680    0.000920    0.002040      0.009540   \n",
       "25%            0.000020    0.001660    0.001860    0.004985      0.016505   \n",
       "50%            0.000030    0.002500    0.002690    0.007490      0.022970   \n",
       "75%            0.000060    0.003835    0.003955    0.011505      0.037885   \n",
       "max            0.000260    0.021440    0.019580    0.064330      0.119080   \n",
       "\n",
       "       MDVP:Shimmer(dB)  ...  Shimmer:DDA         NHR         HNR      status  \\\n",
       "count        195.000000  ...   195.000000  195.000000  195.000000  195.000000   \n",
       "mean           0.282251  ...     0.046993    0.024847   21.885974    0.753846   \n",
       "std            0.194877  ...     0.030459    0.040418    4.425764    0.431878   \n",
       "min            0.085000  ...     0.013640    0.000650    8.441000    0.000000   \n",
       "25%            0.148500  ...     0.024735    0.005925   19.198000    1.000000   \n",
       "50%            0.221000  ...     0.038360    0.011660   22.085000    1.000000   \n",
       "75%            0.350000  ...     0.060795    0.025640   25.075500    1.000000   \n",
       "max            1.302000  ...     0.169420    0.314820   33.047000    1.000000   \n",
       "\n",
       "             RPDE         DFA     spread1     spread2          D2         PPE  \n",
       "count  195.000000  195.000000  195.000000  195.000000  195.000000  195.000000  \n",
       "mean     0.498536    0.718099   -5.684397    0.226510    2.381826    0.206552  \n",
       "std      0.103942    0.055336    1.090208    0.083406    0.382799    0.090119  \n",
       "min      0.256570    0.574282   -7.964984    0.006274    1.423287    0.044539  \n",
       "25%      0.421306    0.674758   -6.450096    0.174351    2.099125    0.137451  \n",
       "50%      0.495954    0.722254   -5.720868    0.218885    2.361532    0.194052  \n",
       "75%      0.587562    0.761881   -5.046192    0.279234    2.636456    0.252980  \n",
       "max      0.685151    0.825288   -2.434031    0.450493    3.671155    0.527367  \n",
       "\n",
       "[8 rows x 23 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting some statistical measure about data\n",
    "parkinsons_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ce89850c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    147\n",
       "0     48\n",
       "Name: status, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#distribution of target variable\n",
    "parkinsons_data['status'].value_counts()\n",
    "\n",
    "# 1 -- parkinsons positive \n",
    "# 0 -- parkinsons Negative (Healthy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1e27184b",
   "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>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>MDVP:Shimmer(dB)</th>\n",
       "      <th>...</th>\n",
       "      <th>MDVP:APQ</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>status</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>181.937771</td>\n",
       "      <td>223.636750</td>\n",
       "      <td>145.207292</td>\n",
       "      <td>0.003866</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.001925</td>\n",
       "      <td>0.002056</td>\n",
       "      <td>0.005776</td>\n",
       "      <td>0.017615</td>\n",
       "      <td>0.162958</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013305</td>\n",
       "      <td>0.028511</td>\n",
       "      <td>0.011483</td>\n",
       "      <td>24.678750</td>\n",
       "      <td>0.442552</td>\n",
       "      <td>0.695716</td>\n",
       "      <td>-6.759264</td>\n",
       "      <td>0.160292</td>\n",
       "      <td>2.154491</td>\n",
       "      <td>0.123017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>145.180762</td>\n",
       "      <td>188.441463</td>\n",
       "      <td>106.893558</td>\n",
       "      <td>0.006989</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.003757</td>\n",
       "      <td>0.003900</td>\n",
       "      <td>0.011273</td>\n",
       "      <td>0.033658</td>\n",
       "      <td>0.321204</td>\n",
       "      <td>...</td>\n",
       "      <td>0.027600</td>\n",
       "      <td>0.053027</td>\n",
       "      <td>0.029211</td>\n",
       "      <td>20.974048</td>\n",
       "      <td>0.516816</td>\n",
       "      <td>0.725408</td>\n",
       "      <td>-5.333420</td>\n",
       "      <td>0.248133</td>\n",
       "      <td>2.456058</td>\n",
       "      <td>0.233828</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
       "status                                                            \n",
       "0        181.937771    223.636750    145.207292        0.003866   \n",
       "1        145.180762    188.441463    106.893558        0.006989   \n",
       "\n",
       "        MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
       "status                                                                   \n",
       "0               0.000023  0.001925  0.002056    0.005776      0.017615   \n",
       "1               0.000051  0.003757  0.003900    0.011273      0.033658   \n",
       "\n",
       "        MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA       NHR        HNR  \\\n",
       "status                    ...                                               \n",
       "0               0.162958  ...  0.013305     0.028511  0.011483  24.678750   \n",
       "1               0.321204  ...  0.027600     0.053027  0.029211  20.974048   \n",
       "\n",
       "            RPDE       DFA   spread1   spread2        D2       PPE  \n",
       "status                                                              \n",
       "0       0.442552  0.695716 -6.759264  0.160292  2.154491  0.123017  \n",
       "1       0.516816  0.725408 -5.333420  0.248133  2.456058  0.233828  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping the data based on the target value\n",
    "parkinsons_data.groupby('status').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "09d70bed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data preprocessing\n",
    "# Seprating the features and Target\n",
    "\n",
    "X = parkinsons_data.drop(columns=['name','status'], axis=1)\n",
    "Y = parkinsons_data['status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "60504873",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
      "0        119.992       157.302        74.997         0.00784   \n",
      "1        122.400       148.650       113.819         0.00968   \n",
      "2        116.682       131.111       111.555         0.01050   \n",
      "3        116.676       137.871       111.366         0.00997   \n",
      "4        116.014       141.781       110.655         0.01284   \n",
      "..           ...           ...           ...             ...   \n",
      "190      174.188       230.978        94.261         0.00459   \n",
      "191      209.516       253.017        89.488         0.00564   \n",
      "192      174.688       240.005        74.287         0.01360   \n",
      "193      198.764       396.961        74.904         0.00740   \n",
      "194      214.289       260.277        77.973         0.00567   \n",
      "\n",
      "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
      "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
      "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
      "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
      "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
      "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
      "..                ...       ...       ...         ...           ...   \n",
      "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
      "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
      "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
      "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
      "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
      "\n",
      "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
      "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
      "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
      "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
      "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
      "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
      "..                ...  ...       ...          ...      ...     ...       ...   \n",
      "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
      "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
      "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
      "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
      "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
      "\n",
      "          DFA   spread1   spread2        D2       PPE  \n",
      "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
      "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
      "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
      "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
      "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
      "..        ...       ...       ...       ...       ...  \n",
      "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
      "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
      "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
      "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
      "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
      "\n",
      "[195 rows x 22 columns]\n"
     ]
    }
   ],
   "source": [
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d3ee6c86",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      1\n",
      "1      1\n",
      "2      1\n",
      "3      1\n",
      "4      1\n",
      "      ..\n",
      "190    0\n",
      "191    0\n",
      "192    0\n",
      "193    0\n",
      "194    0\n",
      "Name: status, Length: 195, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d530259a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#splitting the data into training data and test data\n",
    "X_train , X_test , Y_train , Y_test = train_test_split(X , Y , test_size = 0.2 ,random_state=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f5fc090f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(195, 22) (156, 22) (39, 22)\n"
     ]
    }
   ],
   "source": [
    "print(X.shape , X_train.shape, X_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bd8ccae3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data Standarization\n",
    "scaler = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8deef242",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "StandardScaler()"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler.fit(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3186ed26",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = scaler.transform(X_train)\n",
    "\n",
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "42331867",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.63239631 -0.02731081 -0.87985049 ... -0.97586547 -0.55160318\n",
      "   0.07769494]\n",
      " [-1.05512719 -0.83337041 -0.9284778  ...  0.3981808  -0.61014073\n",
      "   0.39291782]\n",
      " [ 0.02996187 -0.29531068 -1.12211107 ... -0.43937044 -0.62849605\n",
      "  -0.50948408]\n",
      " ...\n",
      " [-0.9096785  -0.6637302  -0.160638   ...  1.22001022 -0.47404629\n",
      "  -0.2159482 ]\n",
      " [-0.35977689  0.19731822 -0.79063679 ... -0.17896029 -0.47272835\n",
      "   0.28181221]\n",
      " [ 1.01957066  0.19922317 -0.61914972 ... -0.716232    1.23632066\n",
      "  -0.05829386]]\n"
     ]
    }
   ],
   "source": [
    "print(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "a163ea6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Model training \n",
    "#SVM = Support vector Machine Model\n",
    "\n",
    "model = svm.SVC(kernel='linear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2ee0f6de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(kernel='linear')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Training the SVM model with training data\n",
    "\n",
    "model.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c711fd73",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Model Evaluation\n",
    "#Accuracy Score\n",
    "\n",
    "X_train_prediction = model.predict(X_train)\n",
    "training_data_accuracy = accuracy_score(Y_train, X_train_prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c94fac91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy Score of training data :  0.8846153846153846\n"
     ]
    }
   ],
   "source": [
    "print('Accuracy Score of training data : ',training_data_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "49c46162",
   "metadata": {},
   "outputs": [],
   "source": [
    "# accuracy score on training data\n",
    "X_test_prediction = model.predict(X_test)\n",
    "test_data_accuracy = accuracy_score(Y_test, X_test_prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "be419ff4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy score of test data :  0.8717948717948718\n"
     ]
    }
   ],
   "source": [
    "print('Accuracy score of test data : ',test_data_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c20ecf4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\n",
      "The Person does not have Parkinsons Disease\n"
     ]
    }
   ],
   "source": [
    "#Building predictive system\n",
    "\n",
    "\n",
    "input_data = (197.07600,206.89600,192.05500,0.00289,0.00001,0.00166,0.00168,0.00498,0.01098,0.09700,0.00563,0.00680,0.00802,0.01689,0.00339,26.77500,0.422229,0.741367,-7.348300,0.177551,1.743867,0.085569)\n",
    "\n",
    "# changing input data to a numpy array\n",
    "input_data_as_numpy_array = np.asarray(input_data)\n",
    "\n",
    "# reshape the numpy array\n",
    "input_data_reshaped = input_data_as_numpy_array.reshape(1,-1)\n",
    "\n",
    "# standardize the data\n",
    "std_data = scaler.transform(input_data_reshaped)\n",
    "\n",
    "prediction = model.predict(std_data)\n",
    "print(prediction)\n",
    "\n",
    "\n",
    "if (prediction[0] == 0):\n",
    "  print(\"The Person does not have Parkinsons Disease\")\n",
    "\n",
    "else:\n",
    "  print(\"The Person has Parkinsons\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21baa3c9",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}