Parkinsons_Disease_Prediction.ipynb

{
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   "source": [
    "# <center>Parkinson's Disease Detection</center>\n",
    "\n",
    "## Overview:\n",
    "Parkinson’s Disease (PD) is a degenerative neurological disorder marked by decreased dopamine levels in the brain. It manifests itself through a deterioration of movement, including the presence of tremors and stiffness. There is commonly a marked effect on speech, including dysarthria (difficulty articulating sounds), hypophonia (lowered volume), and monotone (reduced pitch range). Additionally, cognitive impairments and changes in mood can occur, and risk of\n",
    "dementia is increased.\n",
    "\n",
    "## Dataset Information:\n",
    "\n",
    "Dataset: [Kaggle - Parkinsons Disease Detection](https://www.kaggle.com/datasets/debasisdotcom/parkinson-disease-detection)\n",
    "\n",
    "### Independent Feature:\n",
    "* status - Health status of the subject (one) - Parkinson's, (zero) - healthy\n",
    "### Dependent Features:\n",
    "* MDVP:Fo(Hz) - Average vocal fundamental frequency\n",
    "* MDVP:Fhi(Hz) - Maximum vocal fundamental frequency\n",
    "* MDVP:Flo(Hz) - Minimum vocal fundamental frequency\n",
    "* MDVP:Jitter(%), MDVP:Jitter(Abs), MDVP:RAP, MDVP:PPQ, Jitter:DDP - Several measures of variation in fundamental frequency\n",
    "* MDVP:Shimmer, MDVP:Shimmer(dB), Shimmer:APQ3, Shimmer:APQ5, MDVP:APQ, Shimmer:DDA - Several measures of variation in amplitude\n",
    "* NHR, HNR - Two measures of ratio of noise to tonal components in the voice\n",
    "* RPDE, D2 - Two nonlinear dynamical complexity measures\n",
    "* DFA - Signal fractal scaling exponent\n",
    "* spread1, spread2, PPE - Three nonlinear measures of fundamental frequency variation\n",
    "\n",
    "### Training : Testing :: 156 : 39 :: 80 : 20\n",
    "\n",
    "### Evaluation Metrics Considered:\n",
    "* Accuracy, Precision, Recision, F1 Score, ROC AUC Curve"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f673b002",
   "metadata": {},
   "source": [
    "# 1. Importing Required Libraries\n",
    "* NumPy: For numerical computations and array manipulation.\n",
    "* Pandas: For data manipulation and analysis.\n",
    "* Seaborn: For statistical data visualization.\n",
    "* Matplotlib: For creating plots and visualizations.\n",
    "* Scikit-learn: For machine learning algorithms and evaluation metrics.\n",
    "* XGBoost: For Extreme gradient boosting machine learning.\n",
    "* Catboost: For CatBoosting machine learning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dc18ea86",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split,GridSearchCV\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_curve, roc_auc_score\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, ExtraTreesClassifier"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b387c1",
   "metadata": {},
   "source": [
    "# 2. Data Ingestion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1c31f1a2",
   "metadata": {},
   "outputs": [
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       "<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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>230.978</td>\n",
       "      <td>94.261</td>\n",
       "      <td>0.00459</td>\n",
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       "      <td>0.00259</td>\n",
       "      <td>0.00790</td>\n",
       "      <td>0.04087</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07008</td>\n",
       "      <td>0.02764</td>\n",
       "      <td>19.517</td>\n",
       "      <td>0</td>\n",
       "      <td>0.448439</td>\n",
       "      <td>0.657899</td>\n",
       "      <td>-6.538586</td>\n",
       "      <td>0.121952</td>\n",
       "      <td>2.657476</td>\n",
       "      <td>0.133050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>phon_R01_S50_3</td>\n",
       "      <td>209.516</td>\n",
       "      <td>253.017</td>\n",
       "      <td>89.488</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00331</td>\n",
       "      <td>0.00292</td>\n",
       "      <td>0.00994</td>\n",
       "      <td>0.02751</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04812</td>\n",
       "      <td>0.01810</td>\n",
       "      <td>19.147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.431674</td>\n",
       "      <td>0.683244</td>\n",
       "      <td>-6.195325</td>\n",
       "      <td>0.129303</td>\n",
       "      <td>2.784312</td>\n",
       "      <td>0.168895</td>\n",
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       "      <th>192</th>\n",
       "      <td>phon_R01_S50_4</td>\n",
       "      <td>174.688</td>\n",
       "      <td>240.005</td>\n",
       "      <td>74.287</td>\n",
       "      <td>0.01360</td>\n",
       "      <td>0.00008</td>\n",
       "      <td>0.00624</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.01873</td>\n",
       "      <td>0.02308</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03804</td>\n",
       "      <td>0.10715</td>\n",
       "      <td>17.883</td>\n",
       "      <td>0</td>\n",
       "      <td>0.407567</td>\n",
       "      <td>0.655683</td>\n",
       "      <td>-6.787197</td>\n",
       "      <td>0.158453</td>\n",
       "      <td>2.679772</td>\n",
       "      <td>0.131728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>phon_R01_S50_5</td>\n",
       "      <td>198.764</td>\n",
       "      <td>396.961</td>\n",
       "      <td>74.904</td>\n",
       "      <td>0.00740</td>\n",
       "      <td>0.00004</td>\n",
       "      <td>0.00370</td>\n",
       "      <td>0.00390</td>\n",
       "      <td>0.01109</td>\n",
       "      <td>0.02296</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03794</td>\n",
       "      <td>0.07223</td>\n",
       "      <td>19.020</td>\n",
       "      <td>0</td>\n",
       "      <td>0.451221</td>\n",
       "      <td>0.643956</td>\n",
       "      <td>-6.744577</td>\n",
       "      <td>0.207454</td>\n",
       "      <td>2.138608</td>\n",
       "      <td>0.123306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>phon_R01_S50_6</td>\n",
       "      <td>214.289</td>\n",
       "      <td>260.277</td>\n",
       "      <td>77.973</td>\n",
       "      <td>0.00567</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00295</td>\n",
       "      <td>0.00317</td>\n",
       "      <td>0.00885</td>\n",
       "      <td>0.01884</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03078</td>\n",
       "      <td>0.04398</td>\n",
       "      <td>21.209</td>\n",
       "      <td>0</td>\n",
       "      <td>0.462803</td>\n",
       "      <td>0.664357</td>\n",
       "      <td>-5.724056</td>\n",
       "      <td>0.190667</td>\n",
       "      <td>2.555477</td>\n",
       "      <td>0.148569</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>195 rows × 24 columns</p>\n",
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      ],
      "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",
       "190  phon_R01_S50_2      174.188       230.978        94.261         0.00459   \n",
       "191  phon_R01_S50_3      209.516       253.017        89.488         0.00564   \n",
       "192  phon_R01_S50_4      174.688       240.005        74.287         0.01360   \n",
       "193  phon_R01_S50_5      198.764       396.961        74.904         0.00740   \n",
       "194  phon_R01_S50_6      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",
       "     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",
       "190      0.07008  0.02764  19.517       0  0.448439  0.657899 -6.538586   \n",
       "191      0.04812  0.01810  19.147       0  0.431674  0.683244 -6.195325   \n",
       "192      0.03804  0.10715  17.883       0  0.407567  0.655683 -6.787197   \n",
       "193      0.03794  0.07223  19.020       0  0.451221  0.643956 -6.744577   \n",
       "194      0.03078  0.04398  21.209       0  0.462803  0.664357 -5.724056   \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",
       "190  0.121952  2.657476  0.133050  \n",
       "191  0.129303  2.784312  0.168895  \n",
       "192  0.158453  2.679772  0.131728  \n",
       "193  0.207454  2.138608  0.123306  \n",
       "194  0.190667  2.555477  0.148569  \n",
       "\n",
       "[195 rows x 24 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('Data/parkinsons.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9ebb54c",
   "metadata": {},
   "source": [
    "# 3. Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "aed2b12e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "363be441",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(195, 24)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9317a35e",
   "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": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dd58f492",
   "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": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d6999376",
   "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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "10487b74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "status\n",
       "1    147\n",
       "0     48\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"status\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46d89b2e",
   "metadata": {},
   "source": [
    "# 4. Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bc9aad6",
   "metadata": {},
   "source": [
    "### 4.1 Removing Unnecessary Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bb46e38b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(\"name\",axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42bfddd7",
   "metadata": {},
   "source": [
    "### 4.2 Feature Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ee71cf06",
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_columns = []\n",
    "numerical_columns = []\n",
    "\n",
    "for col in df.columns:\n",
    "    if df[col].dtype == 'object':\n",
    "        categorical_columns.append(col)\n",
    "    else:\n",
    "        numerical_columns.append(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "dd8b8f2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Numerical Features:  ['MDVP:Fo(Hz)', 'MDVP:Fhi(Hz)', 'MDVP:Flo(Hz)', 'MDVP:Jitter(%)', 'MDVP:Jitter(Abs)', 'MDVP:RAP', 'MDVP:PPQ', 'Jitter:DDP', 'MDVP:Shimmer', 'MDVP:Shimmer(dB)', 'Shimmer:APQ3', 'Shimmer:APQ5', 'MDVP:APQ', 'Shimmer:DDA', 'NHR', 'HNR', 'status', 'RPDE', 'DFA', 'spread1', 'spread2', 'D2', 'PPE']\n",
      "\n",
      "Categorical Features:  []\n"
     ]
    }
   ],
   "source": [
    "print(\"Numerical Features: \",numerical_columns)\n",
    "\n",
    "print(\"\\nCategorical Features: \",categorical_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1afdbbeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "discrete_features=[feature for feature in numerical_columns if len(df[feature].unique())<25]\n",
    "continuous_features=[feature for feature in numerical_columns if feature not in discrete_features]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac4e5966",
   "metadata": {},
   "source": [
    "### 4.3 Training and Testing Data Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f107ebe2",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=df.drop(labels=['status'],axis=1)\n",
    "y=df['status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dfa42266",
   "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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>0.426</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02971</td>\n",
       "      <td>0.06545</td>\n",
       "      <td>0.02211</td>\n",
       "      <td>21.033</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>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>0.626</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04368</td>\n",
       "      <td>0.09403</td>\n",
       "      <td>0.01929</td>\n",
       "      <td>19.085</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>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>0.482</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03590</td>\n",
       "      <td>0.08270</td>\n",
       "      <td>0.01309</td>\n",
       "      <td>20.651</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>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>0.517</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03772</td>\n",
       "      <td>0.08771</td>\n",
       "      <td>0.01353</td>\n",
       "      <td>20.644</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>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>0.584</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04465</td>\n",
       "      <td>0.10470</td>\n",
       "      <td>0.01767</td>\n",
       "      <td>19.649</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",
       "    <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>190</th>\n",
       "      <td>174.188</td>\n",
       "      <td>230.978</td>\n",
       "      <td>94.261</td>\n",
       "      <td>0.00459</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00263</td>\n",
       "      <td>0.00259</td>\n",
       "      <td>0.00790</td>\n",
       "      <td>0.04087</td>\n",
       "      <td>0.405</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02745</td>\n",
       "      <td>0.07008</td>\n",
       "      <td>0.02764</td>\n",
       "      <td>19.517</td>\n",
       "      <td>0.448439</td>\n",
       "      <td>0.657899</td>\n",
       "      <td>-6.538586</td>\n",
       "      <td>0.121952</td>\n",
       "      <td>2.657476</td>\n",
       "      <td>0.133050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>209.516</td>\n",
       "      <td>253.017</td>\n",
       "      <td>89.488</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00331</td>\n",
       "      <td>0.00292</td>\n",
       "      <td>0.00994</td>\n",
       "      <td>0.02751</td>\n",
       "      <td>0.263</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01879</td>\n",
       "      <td>0.04812</td>\n",
       "      <td>0.01810</td>\n",
       "      <td>19.147</td>\n",
       "      <td>0.431674</td>\n",
       "      <td>0.683244</td>\n",
       "      <td>-6.195325</td>\n",
       "      <td>0.129303</td>\n",
       "      <td>2.784312</td>\n",
       "      <td>0.168895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>174.688</td>\n",
       "      <td>240.005</td>\n",
       "      <td>74.287</td>\n",
       "      <td>0.01360</td>\n",
       "      <td>0.00008</td>\n",
       "      <td>0.00624</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.01873</td>\n",
       "      <td>0.02308</td>\n",
       "      <td>0.256</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01667</td>\n",
       "      <td>0.03804</td>\n",
       "      <td>0.10715</td>\n",
       "      <td>17.883</td>\n",
       "      <td>0.407567</td>\n",
       "      <td>0.655683</td>\n",
       "      <td>-6.787197</td>\n",
       "      <td>0.158453</td>\n",
       "      <td>2.679772</td>\n",
       "      <td>0.131728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>198.764</td>\n",
       "      <td>396.961</td>\n",
       "      <td>74.904</td>\n",
       "      <td>0.00740</td>\n",
       "      <td>0.00004</td>\n",
       "      <td>0.00370</td>\n",
       "      <td>0.00390</td>\n",
       "      <td>0.01109</td>\n",
       "      <td>0.02296</td>\n",
       "      <td>0.241</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01588</td>\n",
       "      <td>0.03794</td>\n",
       "      <td>0.07223</td>\n",
       "      <td>19.020</td>\n",
       "      <td>0.451221</td>\n",
       "      <td>0.643956</td>\n",
       "      <td>-6.744577</td>\n",
       "      <td>0.207454</td>\n",
       "      <td>2.138608</td>\n",
       "      <td>0.123306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>214.289</td>\n",
       "      <td>260.277</td>\n",
       "      <td>77.973</td>\n",
       "      <td>0.00567</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00295</td>\n",
       "      <td>0.00317</td>\n",
       "      <td>0.00885</td>\n",
       "      <td>0.01884</td>\n",
       "      <td>0.190</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01373</td>\n",
       "      <td>0.03078</td>\n",
       "      <td>0.04398</td>\n",
       "      <td>21.209</td>\n",
       "      <td>0.462803</td>\n",
       "      <td>0.664357</td>\n",
       "      <td>-5.724056</td>\n",
       "      <td>0.190667</td>\n",
       "      <td>2.555477</td>\n",
       "      <td>0.148569</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>195 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     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]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db157898",
   "metadata": {},
   "source": [
    "### 4.4 Checking for Feature Multi-Collinearity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5c494f98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(x.corr(),annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5870a0ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "def correlation(dataset,threshold):\n",
    "    col_corr=set()\n",
    "    corr_matrix=df.corr()\n",
    "    for i in range(len(corr_matrix.columns)):\n",
    "        for j in range(i):\n",
    "            if abs(corr_matrix.iloc[i,j])>threshold:\n",
    "                colname=corr_matrix.columns[i]\n",
    "                col_corr.add(colname)\n",
    "    return col_corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "16fac78d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'MDVP:Jitter(Abs)', 'Shimmer:APQ5', 'MDVP:APQ', 'PPE', 'MDVP:PPQ', 'NHR', 'Jitter:DDP', 'MDVP:RAP', 'Shimmer:APQ3', 'Shimmer:DDA', 'spread1', 'HNR', 'MDVP:Shimmer(dB)', 'MDVP:Shimmer'}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_features=correlation(x,0.7)\n",
    "print(corr_features)\n",
    "len(set(corr_features))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b4c3a0ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=x.drop(corr_features,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e0bb7fb5",
   "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>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>119.992</td>\n",
       "      <td>157.302</td>\n",
       "      <td>74.997</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.414783</td>\n",
       "      <td>0.815285</td>\n",
       "      <td>0.266482</td>\n",
       "      <td>2.301442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>122.400</td>\n",
       "      <td>148.650</td>\n",
       "      <td>113.819</td>\n",
       "      <td>0.00968</td>\n",
       "      <td>0.458359</td>\n",
       "      <td>0.819521</td>\n",
       "      <td>0.335590</td>\n",
       "      <td>2.486855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>116.682</td>\n",
       "      <td>131.111</td>\n",
       "      <td>111.555</td>\n",
       "      <td>0.01050</td>\n",
       "      <td>0.429895</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>2.342259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>116.676</td>\n",
       "      <td>137.871</td>\n",
       "      <td>111.366</td>\n",
       "      <td>0.00997</td>\n",
       "      <td>0.434969</td>\n",
       "      <td>0.819235</td>\n",
       "      <td>0.334147</td>\n",
       "      <td>2.405554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>116.014</td>\n",
       "      <td>141.781</td>\n",
       "      <td>110.655</td>\n",
       "      <td>0.01284</td>\n",
       "      <td>0.417356</td>\n",
       "      <td>0.823484</td>\n",
       "      <td>0.234513</td>\n",
       "      <td>2.332180</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>174.188</td>\n",
       "      <td>230.978</td>\n",
       "      <td>94.261</td>\n",
       "      <td>0.00459</td>\n",
       "      <td>0.448439</td>\n",
       "      <td>0.657899</td>\n",
       "      <td>0.121952</td>\n",
       "      <td>2.657476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>209.516</td>\n",
       "      <td>253.017</td>\n",
       "      <td>89.488</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.431674</td>\n",
       "      <td>0.683244</td>\n",
       "      <td>0.129303</td>\n",
       "      <td>2.784312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>174.688</td>\n",
       "      <td>240.005</td>\n",
       "      <td>74.287</td>\n",
       "      <td>0.01360</td>\n",
       "      <td>0.407567</td>\n",
       "      <td>0.655683</td>\n",
       "      <td>0.158453</td>\n",
       "      <td>2.679772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>198.764</td>\n",
       "      <td>396.961</td>\n",
       "      <td>74.904</td>\n",
       "      <td>0.00740</td>\n",
       "      <td>0.451221</td>\n",
       "      <td>0.643956</td>\n",
       "      <td>0.207454</td>\n",
       "      <td>2.138608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>214.289</td>\n",
       "      <td>260.277</td>\n",
       "      <td>77.973</td>\n",
       "      <td>0.00567</td>\n",
       "      <td>0.462803</td>\n",
       "      <td>0.664357</td>\n",
       "      <td>0.190667</td>\n",
       "      <td>2.555477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>195 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)      RPDE  \\\n",
       "0        119.992       157.302        74.997         0.00784  0.414783   \n",
       "1        122.400       148.650       113.819         0.00968  0.458359   \n",
       "2        116.682       131.111       111.555         0.01050  0.429895   \n",
       "3        116.676       137.871       111.366         0.00997  0.434969   \n",
       "4        116.014       141.781       110.655         0.01284  0.417356   \n",
       "..           ...           ...           ...             ...       ...   \n",
       "190      174.188       230.978        94.261         0.00459  0.448439   \n",
       "191      209.516       253.017        89.488         0.00564  0.431674   \n",
       "192      174.688       240.005        74.287         0.01360  0.407567   \n",
       "193      198.764       396.961        74.904         0.00740  0.451221   \n",
       "194      214.289       260.277        77.973         0.00567  0.462803   \n",
       "\n",
       "          DFA   spread2        D2  \n",
       "0    0.815285  0.266482  2.301442  \n",
       "1    0.819521  0.335590  2.486855  \n",
       "2    0.825288  0.311173  2.342259  \n",
       "3    0.819235  0.334147  2.405554  \n",
       "4    0.823484  0.234513  2.332180  \n",
       "..        ...       ...       ...  \n",
       "190  0.657899  0.121952  2.657476  \n",
       "191  0.683244  0.129303  2.784312  \n",
       "192  0.655683  0.158453  2.679772  \n",
       "193  0.643956  0.207454  2.138608  \n",
       "194  0.664357  0.190667  2.555477  \n",
       "\n",
       "[195 rows x 8 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a2d3776b",
   "metadata": {},
   "outputs": [],
   "source": [
    "x.rename(columns={\n",
    "    'MDVP:Fo(Hz)': 'MDVPFO',\n",
    "    'MDVP:Fhi(Hz)': 'MDVPFHI',\n",
    "    'MDVP:Flo(Hz)': 'MDVPFLO',\n",
    "    'MDVP:Jitter(%)': 'MDVPJ'\n",
    "}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d27e1057",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>MDVPFO</th>\n",
       "      <th>MDVPFHI</th>\n",
       "      <th>MDVPFLO</th>\n",
       "      <th>MDVPJ</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>119.992</td>\n",
       "      <td>157.302</td>\n",
       "      <td>74.997</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.414783</td>\n",
       "      <td>0.815285</td>\n",
       "      <td>0.266482</td>\n",
       "      <td>2.301442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>122.400</td>\n",
       "      <td>148.650</td>\n",
       "      <td>113.819</td>\n",
       "      <td>0.00968</td>\n",
       "      <td>0.458359</td>\n",
       "      <td>0.819521</td>\n",
       "      <td>0.335590</td>\n",
       "      <td>2.486855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>116.682</td>\n",
       "      <td>131.111</td>\n",
       "      <td>111.555</td>\n",
       "      <td>0.01050</td>\n",
       "      <td>0.429895</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>2.342259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>116.676</td>\n",
       "      <td>137.871</td>\n",
       "      <td>111.366</td>\n",
       "      <td>0.00997</td>\n",
       "      <td>0.434969</td>\n",
       "      <td>0.819235</td>\n",
       "      <td>0.334147</td>\n",
       "      <td>2.405554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>116.014</td>\n",
       "      <td>141.781</td>\n",
       "      <td>110.655</td>\n",
       "      <td>0.01284</td>\n",
       "      <td>0.417356</td>\n",
       "      <td>0.823484</td>\n",
       "      <td>0.234513</td>\n",
       "      <td>2.332180</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>174.188</td>\n",
       "      <td>230.978</td>\n",
       "      <td>94.261</td>\n",
       "      <td>0.00459</td>\n",
       "      <td>0.448439</td>\n",
       "      <td>0.657899</td>\n",
       "      <td>0.121952</td>\n",
       "      <td>2.657476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>209.516</td>\n",
       "      <td>253.017</td>\n",
       "      <td>89.488</td>\n",
       "      <td>0.00564</td>\n",
       "      <td>0.431674</td>\n",
       "      <td>0.683244</td>\n",
       "      <td>0.129303</td>\n",
       "      <td>2.784312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>174.688</td>\n",
       "      <td>240.005</td>\n",
       "      <td>74.287</td>\n",
       "      <td>0.01360</td>\n",
       "      <td>0.407567</td>\n",
       "      <td>0.655683</td>\n",
       "      <td>0.158453</td>\n",
       "      <td>2.679772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>198.764</td>\n",
       "      <td>396.961</td>\n",
       "      <td>74.904</td>\n",
       "      <td>0.00740</td>\n",
       "      <td>0.451221</td>\n",
       "      <td>0.643956</td>\n",
       "      <td>0.207454</td>\n",
       "      <td>2.138608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>214.289</td>\n",
       "      <td>260.277</td>\n",
       "      <td>77.973</td>\n",
       "      <td>0.00567</td>\n",
       "      <td>0.462803</td>\n",
       "      <td>0.664357</td>\n",
       "      <td>0.190667</td>\n",
       "      <td>2.555477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>195 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      MDVPFO  MDVPFHI  MDVPFLO    MDVPJ      RPDE       DFA   spread2  \\\n",
       "0    119.992  157.302   74.997  0.00784  0.414783  0.815285  0.266482   \n",
       "1    122.400  148.650  113.819  0.00968  0.458359  0.819521  0.335590   \n",
       "2    116.682  131.111  111.555  0.01050  0.429895  0.825288  0.311173   \n",
       "3    116.676  137.871  111.366  0.00997  0.434969  0.819235  0.334147   \n",
       "4    116.014  141.781  110.655  0.01284  0.417356  0.823484  0.234513   \n",
       "..       ...      ...      ...      ...       ...       ...       ...   \n",
       "190  174.188  230.978   94.261  0.00459  0.448439  0.657899  0.121952   \n",
       "191  209.516  253.017   89.488  0.00564  0.431674  0.683244  0.129303   \n",
       "192  174.688  240.005   74.287  0.01360  0.407567  0.655683  0.158453   \n",
       "193  198.764  396.961   74.904  0.00740  0.451221  0.643956  0.207454   \n",
       "194  214.289  260.277   77.973  0.00567  0.462803  0.664357  0.190667   \n",
       "\n",
       "           D2  \n",
       "0    2.301442  \n",
       "1    2.486855  \n",
       "2    2.342259  \n",
       "3    2.405554  \n",
       "4    2.332180  \n",
       "..        ...  \n",
       "190  2.657476  \n",
       "191  2.784312  \n",
       "192  2.679772  \n",
       "193  2.138608  \n",
       "194  2.555477  \n",
       "\n",
       "[195 rows x 8 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "44c4a0e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f48d8922",
   "metadata": {},
   "source": [
    "# 5. Modelling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ffe3a9e",
   "metadata": {},
   "source": [
    "### 5.1 Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cd2b8f81",
   "metadata": {},
   "outputs": [],
   "source": [
    "models = {\n",
    "    'Logistic Regression': LogisticRegression(),\n",
    "    'Naive Bayes': GaussianNB(),\n",
    "    'XG Boost': XGBClassifier(),\n",
    "    'Random Forest': RandomForestClassifier(),\n",
    "    'Gradient Boosting': GradientBoostingClassifier(),\n",
    "    'Decision Tree': DecisionTreeClassifier(),\n",
    "    'K Nearest Neighbors': KNeighborsClassifier(),\n",
    "    'Extra Tree': ExtraTreesClassifier()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "75246afa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Logistic Regression\n",
      "Training Accuracy:  0.8525641025641025\n",
      "Testing Accuracy:  0.8974358974358975\n",
      "Precision:  0.8787878787878788\n",
      "Recall:  1.0\n",
      "F1 Score:  0.9354838709677419\n",
      "===================================\n",
      "Model: Naive Bayes\n",
      "Training Accuracy:  0.7948717948717948\n",
      "Testing Accuracy:  0.8461538461538461\n",
      "Precision:  0.896551724137931\n",
      "Recall:  0.896551724137931\n",
      "F1 Score:  0.896551724137931\n",
      "===================================\n",
      "Model: XG Boost\n",
      "Training Accuracy:  1.0\n",
      "Testing Accuracy:  0.9230769230769231\n",
      "Precision:  1.0\n",
      "Recall:  0.896551724137931\n",
      "F1 Score:  0.9454545454545454\n",
      "===================================\n",
      "Model: Random Forest\n",
      "Training Accuracy:  1.0\n",
      "Testing Accuracy:  0.9743589743589743\n",
      "Precision:  0.9666666666666667\n",
      "Recall:  1.0\n",
      "F1 Score:  0.9830508474576272\n",
      "===================================\n",
      "Model: Gradient Boosting\n",
      "Training Accuracy:  1.0\n",
      "Testing Accuracy:  0.9487179487179487\n",
      "Precision:  0.9354838709677419\n",
      "Recall:  1.0\n",
      "F1 Score:  0.9666666666666667\n",
      "===================================\n",
      "Model: Decision Tree\n",
      "Training Accuracy:  1.0\n",
      "Testing Accuracy:  0.9230769230769231\n",
      "Precision:  0.9333333333333333\n",
      "Recall:  0.9655172413793104\n",
      "F1 Score:  0.9491525423728814\n",
      "===================================\n",
      "Model: K Nearest Neighbors\n",
      "Training Accuracy:  0.8846153846153846\n",
      "Testing Accuracy:  0.8717948717948718\n",
      "Precision:  0.875\n",
      "Recall:  0.9655172413793104\n",
      "F1 Score:  0.9180327868852459\n",
      "===================================\n",
      "Model: Extra Tree\n",
      "Training Accuracy:  1.0\n",
      "Testing Accuracy:  0.9487179487179487\n",
      "Precision:  0.9655172413793104\n",
      "Recall:  0.9655172413793104\n",
      "F1 Score:  0.9655172413793104\n",
      "===================================\n",
      "\n",
      "The best model based on accuracy is Random Forest with Testing Accuracy: 0.9743589743589743\n"
     ]
    }
   ],
   "source": [
    "model_list = []\n",
    "train_accuracy_list = []\n",
    "test_accuracy_list = []\n",
    "precision_list = []\n",
    "recall_list = []\n",
    "f1_list = []\n",
    "\n",
    "for model_name, model in models.items():\n",
    "\n",
    "    model.fit(x_train, y_train)\n",
    "    y_pred_train = model.predict(x_train)\n",
    "    y_pred = model.predict(x_test)\n",
    "    \n",
    "    train_accuracy = accuracy_score(y_train,y_pred_train)\n",
    "    test_accuracy = accuracy_score(y_test, y_pred)\n",
    "    precision = precision_score(y_test, y_pred)\n",
    "    recall = recall_score(y_test, y_pred)\n",
    "    f1 = f1_score(y_test, y_pred)\n",
    "\n",
    "    print(f\"Model: {model_name}\")\n",
    "    print(f\"Training Accuracy: \",train_accuracy)\n",
    "    print(\"Testing Accuracy: \", test_accuracy)\n",
    "    print(\"Precision: \",precision)\n",
    "    print(\"Recall: \",recall)\n",
    "    print(\"F1 Score: \",f1)\n",
    "\n",
    "\n",
    "    model_list.append(model_name)\n",
    "    train_accuracy_list.append(train_accuracy)\n",
    "    test_accuracy_list.append(test_accuracy)\n",
    "    precision_list.append(precision)\n",
    "    recall_list.append(recall)\n",
    "    f1_list.append(f1)\n",
    "\n",
    "    print(\"=\" * 35)\n",
    "\n",
    "max_accuracy_index = test_accuracy_list.index(max(test_accuracy_list))\n",
    "print(f\"\\nThe best model based on accuracy is {model_list[max_accuracy_index]} with Testing Accuracy: {test_accuracy_list[max_accuracy_index]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c69a89d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>Train Accuracy</th>\n",
       "      <th>Test Accuracy</th>\n",
       "      <th>Precision</th>\n",
       "      <th>Recall</th>\n",
       "      <th>F1 Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>0.852564</td>\n",
       "      <td>0.897436</td>\n",
       "      <td>0.878788</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.935484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Naive Bayes</td>\n",
       "      <td>0.794872</td>\n",
       "      <td>0.846154</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>XG Boost</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.923077</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.945455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Random Forest</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974359</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.983051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gradient Boosting</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.948718</td>\n",
       "      <td>0.935484</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Decision Tree</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.923077</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.949153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>K Nearest Neighbors</td>\n",
       "      <td>0.884615</td>\n",
       "      <td>0.871795</td>\n",
       "      <td>0.875000</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.918033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Extra Tree</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.948718</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.965517</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Model  Train Accuracy  Test Accuracy  Precision    Recall  \\\n",
       "0  Logistic Regression        0.852564       0.897436   0.878788  1.000000   \n",
       "1          Naive Bayes        0.794872       0.846154   0.896552  0.896552   \n",
       "2             XG Boost        1.000000       0.923077   1.000000  0.896552   \n",
       "3        Random Forest        1.000000       0.974359   0.966667  1.000000   \n",
       "4    Gradient Boosting        1.000000       0.948718   0.935484  1.000000   \n",
       "5        Decision Tree        1.000000       0.923077   0.933333  0.965517   \n",
       "6  K Nearest Neighbors        0.884615       0.871795   0.875000  0.965517   \n",
       "7           Extra Tree        1.000000       0.948718   0.965517  0.965517   \n",
       "\n",
       "   F1 Score  \n",
       "0  0.935484  \n",
       "1  0.896552  \n",
       "2  0.945455  \n",
       "3  0.983051  \n",
       "4  0.966667  \n",
       "5  0.949153  \n",
       "6  0.918033  \n",
       "7  0.965517  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = {\n",
    "    'Model': model_list,\n",
    "    'Train Accuracy': train_accuracy_list,\n",
    "    'Test Accuracy': test_accuracy_list,\n",
    "    'Precision': precision_list,\n",
    "    'Recall': recall_list,\n",
    "    'F1 Score': f1_list\n",
    "}\n",
    "\n",
    "results = pd.DataFrame(results)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e38bfde0",
   "metadata": {},
   "source": [
    "### 5.2 HyperParamter Tuning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "76df7c6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    'Logistic Regression': {'C': [0.001, 0.01, 0.1, 1, 10, 100]},\n",
    "    'Naive Bayes': {},\n",
    "    'XG Boost': {'learning_rate': [0.01, 0.1, 0.5], 'n_estimators': [50, 100, 200], 'max_depth': [5, 10, 15]},\n",
    "    'Random Forest': {'n_estimators': [100, 200, 300], 'max_depth': [None, 10, 20]},\n",
    "    'Gradient Boosting': {'n_estimators': [50, 100, 200], 'learning_rate': [0.01, 0.1, 0.5], 'max_depth': [3, 5, 10]},\n",
    "    'Decision Tree': {'max_depth': [3, 5, 10, None], 'min_samples_split': [2, 5, 10]},\n",
    "    'K Nearest Neighbors': {'n_neighbors': [3, 5, 10]},\n",
    "    'Extra Tree': {'n_estimators': [50, 100, 200], 'max_depth': [3, 5, 10]}\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "11b74c37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Best parameters for Logistic Regression: {'C': 1}\n",
      "Train Accuracy for Logistic Regression: 0.8525641025641025\n",
      "Test Accuracy for Logistic Regression: 0.8974358974358975\n",
      "Precision for Logistic Regression: 0.8787878787878788\n",
      "Recall for Logistic Regression: 1.0\n",
      "F1 Score for Logistic Regression: 0.9354838709677419\n",
      "===================================\n",
      "\n",
      "Best parameters for Naive Bayes: {}\n",
      "Train Accuracy for Naive Bayes: 0.7948717948717948\n",
      "Test Accuracy for Naive Bayes: 0.8461538461538461\n",
      "Precision for Naive Bayes: 0.896551724137931\n",
      "Recall for Naive Bayes: 0.896551724137931\n",
      "F1 Score for Naive Bayes: 0.896551724137931\n",
      "===================================\n",
      "\n",
      "Best parameters for XG Boost: {'learning_rate': 0.1, 'max_depth': 10, 'n_estimators': 50}\n",
      "Train Accuracy for XG Boost: 1.0\n",
      "Test Accuracy for XG Boost: 0.8717948717948718\n",
      "Precision for XG Boost: 0.9285714285714286\n",
      "Recall for XG Boost: 0.896551724137931\n",
      "F1 Score for XG Boost: 0.9122807017543859\n",
      "===================================\n",
      "\n",
      "Best parameters for Random Forest: {'max_depth': 10, 'n_estimators': 300}\n",
      "Train Accuracy for Random Forest: 1.0\n",
      "Test Accuracy for Random Forest: 0.9743589743589743\n",
      "Precision for Random Forest: 0.9666666666666667\n",
      "Recall for Random Forest: 1.0\n",
      "F1 Score for Random Forest: 0.9830508474576272\n",
      "===================================\n",
      "\n",
      "Best parameters for Gradient Boosting: {'learning_rate': 0.5, 'max_depth': 5, 'n_estimators': 100}\n",
      "Train Accuracy for Gradient Boosting: 1.0\n",
      "Test Accuracy for Gradient Boosting: 0.9230769230769231\n",
      "Precision for Gradient Boosting: 0.9333333333333333\n",
      "Recall for Gradient Boosting: 0.9655172413793104\n",
      "F1 Score for Gradient Boosting: 0.9491525423728814\n",
      "===================================\n",
      "\n",
      "Best parameters for Decision Tree: {'max_depth': None, 'min_samples_split': 2}\n",
      "Train Accuracy for Decision Tree: 1.0\n",
      "Test Accuracy for Decision Tree: 0.9230769230769231\n",
      "Precision for Decision Tree: 0.9333333333333333\n",
      "Recall for Decision Tree: 0.9655172413793104\n",
      "F1 Score for Decision Tree: 0.9491525423728814\n",
      "===================================\n",
      "\n",
      "Best parameters for K Nearest Neighbors: {'n_neighbors': 10}\n",
      "Train Accuracy for K Nearest Neighbors: 0.8589743589743589\n",
      "Test Accuracy for K Nearest Neighbors: 0.8461538461538461\n",
      "Precision for K Nearest Neighbors: 0.896551724137931\n",
      "Recall for K Nearest Neighbors: 0.896551724137931\n",
      "F1 Score for K Nearest Neighbors: 0.896551724137931\n",
      "===================================\n",
      "\n",
      "Best parameters for Extra Tree: {'max_depth': 10, 'n_estimators': 200}\n",
      "Train Accuracy for Extra Tree: 1.0\n",
      "Test Accuracy for Extra Tree: 0.9743589743589743\n",
      "Precision for Extra Tree: 0.9666666666666667\n",
      "Recall for Extra Tree: 1.0\n",
      "F1 Score for Extra Tree: 0.9830508474576272\n",
      "===================================\n",
      "We got Random Forest as highest test acuracy of 0.9743589743589743\n"
     ]
    }
   ],
   "source": [
    "modelss =[]\n",
    "train_accuracies = []\n",
    "test_accuracies = []\n",
    "precisions = []\n",
    "recalls = []\n",
    "f1_scores = []\n",
    "\n",
    "for model_name, model in models.items():\n",
    "    if model_name in param_grid:\n",
    "        grid_search = GridSearchCV(model, param_grid[model_name], cv=5, n_jobs=-1)\n",
    "        \n",
    "        grid_search.fit(x_train, y_train)\n",
    "        best_model_cv = grid_search.best_estimator_\n",
    "        best_params = grid_search.best_params_\n",
    "        print(f\"\\nBest parameters for {model_name}: {best_params}\")\n",
    "        \n",
    "        y_train_pred = best_model_cv.predict(x_train)\n",
    "        y_pred = best_model_cv.predict(x_test)\n",
    "        \n",
    "        train_accuracy = accuracy_score(y_train, y_train_pred)\n",
    "        test_accuracy = accuracy_score(y_test, y_pred)\n",
    "        precision = precision_score(y_test, y_pred)\n",
    "        recall = recall_score(y_test, y_pred)\n",
    "        f1 = f1_score(y_test, y_pred)\n",
    "        \n",
    "        modelss.append(model_name)\n",
    "        train_accuracies.append(train_accuracy)\n",
    "        test_accuracies.append(test_accuracy)\n",
    "        precisions.append(precision)\n",
    "        recalls.append(recall)\n",
    "        f1_scores.append(f1)\n",
    "        \n",
    "        print(f\"Train Accuracy for {model_name}: {train_accuracy}\")\n",
    "        print(f\"Test Accuracy for {model_name}: {test_accuracy}\")\n",
    "        print(f\"Precision for {model_name}: {precision}\")\n",
    "        print(f\"Recall for {model_name}: {recall}\")\n",
    "        print(f\"F1 Score for {model_name}: {f1}\")\n",
    "        print(\"=\" * 35)\n",
    "\n",
    "best_test_accuracy_index = test_accuracies.index(max(test_accuracies))\n",
    "print(f\"We got {modelss[best_test_accuracy_index]} as highest test acuracy of {test_accuracies[best_test_accuracy_index]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ee8e47d3",
   "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>Model</th>\n",
       "      <th>Train Accuracy</th>\n",
       "      <th>Test Accuracy</th>\n",
       "      <th>Precision</th>\n",
       "      <th>Recall</th>\n",
       "      <th>F1 Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>0.852564</td>\n",
       "      <td>0.897436</td>\n",
       "      <td>0.878788</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.935484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Naive Bayes</td>\n",
       "      <td>0.794872</td>\n",
       "      <td>0.846154</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>XG Boost</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.871795</td>\n",
       "      <td>0.928571</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.912281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Random Forest</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974359</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.983051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gradient Boosting</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.923077</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.949153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Decision Tree</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.923077</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.965517</td>\n",
       "      <td>0.949153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>K Nearest Neighbors</td>\n",
       "      <td>0.858974</td>\n",
       "      <td>0.846154</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Extra Tree</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974359</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.983051</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Model  Train Accuracy  Test Accuracy  Precision    Recall  \\\n",
       "0  Logistic Regression        0.852564       0.897436   0.878788  1.000000   \n",
       "1          Naive Bayes        0.794872       0.846154   0.896552  0.896552   \n",
       "2             XG Boost        1.000000       0.871795   0.928571  0.896552   \n",
       "3        Random Forest        1.000000       0.974359   0.966667  1.000000   \n",
       "4    Gradient Boosting        1.000000       0.923077   0.933333  0.965517   \n",
       "5        Decision Tree        1.000000       0.923077   0.933333  0.965517   \n",
       "6  K Nearest Neighbors        0.858974       0.846154   0.896552  0.896552   \n",
       "7           Extra Tree        1.000000       0.974359   0.966667  1.000000   \n",
       "\n",
       "   F1 Score  \n",
       "0  0.935484  \n",
       "1  0.896552  \n",
       "2  0.912281  \n",
       "3  0.983051  \n",
       "4  0.949153  \n",
       "5  0.949153  \n",
       "6  0.896552  \n",
       "7  0.983051  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results1 = {\n",
    "    'Model': modelss,\n",
    "    'Train Accuracy': train_accuracies,\n",
    "    'Test Accuracy': test_accuracies,\n",
    "    'Precision': precisions,\n",
    "    'Recall': recalls,\n",
    "    'F1 Score': f1_scores\n",
    "}\n",
    "\n",
    "results1 = pd.DataFrame(results1)\n",
    "results1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c4fe6f4",
   "metadata": {},
   "source": [
    "### ROC AUC Curve Representation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d5154604",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_roc_curve(ax, y_true, y_score, model_name):\n",
    "    fpr, tpr, thresholds = roc_curve(y_true, y_score)\n",
    "    roc_auc = roc_auc_score(y_true, y_score)\n",
    "    ax.plot(fpr, tpr, lw=2, label='%s (area = %0.2f)' % (model_name, roc_auc))\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "for model_name, model in models.items():\n",
    "    model.fit(x_train, y_train)\n",
    "    y_score = model.predict_proba(x_test)[:, 1]\n",
    "    plot_roc_curve(ax, y_test, y_score, model_name)\n",
    "\n",
    "\n",
    "ax.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "ax.set_xlim([0.0, 1.0])\n",
    "ax.set_ylim([0.0, 1.05])\n",
    "ax.set_xlabel('False Positive Rate')\n",
    "ax.set_ylabel('True Positive Rate')\n",
    "ax.set_title('Receiver Operating Characteristic')\n",
    "ax.legend(loc=\"lower right\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e6050c31",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_model = models['Extra Tree']\n",
    "pickle.dump(best_model,open('Parkinsons_Model.pkl','wb'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}