GridsearchCV_test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "289aceb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c5bd72c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"C:\\\\Users\\\\shekh\\\\Downloads\\\\winequality-red.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "999131ed",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.098</td>\n",
       "      <td>25.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.9968</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.68</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.092</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.9970</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.2</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.075</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.4              0.70         0.00             1.9      0.076   \n",
       "1            7.8              0.88         0.00             2.6      0.098   \n",
       "2            7.8              0.76         0.04             2.3      0.092   \n",
       "3           11.2              0.28         0.56             1.9      0.075   \n",
       "4            7.4              0.70         0.00             1.9      0.076   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
       "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "\n",
       "   alcohol  quality  \n",
       "0      9.4        5  \n",
       "1      9.8        5  \n",
       "2      9.8        5  \n",
       "3      9.8        6  \n",
       "4      9.4        5  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "00d3afc6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1599 entries, 0 to 1598\n",
      "Data columns (total 12 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   fixed acidity         1599 non-null   float64\n",
      " 1   volatile acidity      1599 non-null   float64\n",
      " 2   citric acid           1599 non-null   float64\n",
      " 3   residual sugar        1599 non-null   float64\n",
      " 4   chlorides             1599 non-null   float64\n",
      " 5   free sulfur dioxide   1599 non-null   float64\n",
      " 6   total sulfur dioxide  1599 non-null   float64\n",
      " 7   density               1599 non-null   float64\n",
      " 8   pH                    1599 non-null   float64\n",
      " 9   sulphates             1599 non-null   float64\n",
      " 10  alcohol               1599 non-null   float64\n",
      " 11  quality               1599 non-null   int64  \n",
      "dtypes: float64(11), int64(1)\n",
      "memory usage: 150.0 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "150135f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fixed acidity</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>8.319637</td>\n",
       "      <td>1.741096</td>\n",
       "      <td>4.60000</td>\n",
       "      <td>7.1000</td>\n",
       "      <td>7.90000</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>15.90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volatile acidity</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.527821</td>\n",
       "      <td>0.179060</td>\n",
       "      <td>0.12000</td>\n",
       "      <td>0.3900</td>\n",
       "      <td>0.52000</td>\n",
       "      <td>0.640000</td>\n",
       "      <td>1.58000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>citric acid</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.270976</td>\n",
       "      <td>0.194801</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.26000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residual sugar</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>2.538806</td>\n",
       "      <td>1.409928</td>\n",
       "      <td>0.90000</td>\n",
       "      <td>1.9000</td>\n",
       "      <td>2.20000</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>15.50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chlorides</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.087467</td>\n",
       "      <td>0.047065</td>\n",
       "      <td>0.01200</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.07900</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.61100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>15.874922</td>\n",
       "      <td>10.460157</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>14.00000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>72.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>46.467792</td>\n",
       "      <td>32.895324</td>\n",
       "      <td>6.00000</td>\n",
       "      <td>22.0000</td>\n",
       "      <td>38.00000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>289.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>density</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.996747</td>\n",
       "      <td>0.001887</td>\n",
       "      <td>0.99007</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>0.99675</td>\n",
       "      <td>0.997835</td>\n",
       "      <td>1.00369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pH</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>3.311113</td>\n",
       "      <td>0.154386</td>\n",
       "      <td>2.74000</td>\n",
       "      <td>3.2100</td>\n",
       "      <td>3.31000</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>4.01000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sulphates</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.658149</td>\n",
       "      <td>0.169507</td>\n",
       "      <td>0.33000</td>\n",
       "      <td>0.5500</td>\n",
       "      <td>0.62000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>2.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alcohol</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>10.422983</td>\n",
       "      <td>1.065668</td>\n",
       "      <td>8.40000</td>\n",
       "      <td>9.5000</td>\n",
       "      <td>10.20000</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>14.90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>quality</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>5.636023</td>\n",
       "      <td>0.807569</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>6.00000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       count       mean        std      min      25%  \\\n",
       "fixed acidity         1599.0   8.319637   1.741096  4.60000   7.1000   \n",
       "volatile acidity      1599.0   0.527821   0.179060  0.12000   0.3900   \n",
       "citric acid           1599.0   0.270976   0.194801  0.00000   0.0900   \n",
       "residual sugar        1599.0   2.538806   1.409928  0.90000   1.9000   \n",
       "chlorides             1599.0   0.087467   0.047065  0.01200   0.0700   \n",
       "free sulfur dioxide   1599.0  15.874922  10.460157  1.00000   7.0000   \n",
       "total sulfur dioxide  1599.0  46.467792  32.895324  6.00000  22.0000   \n",
       "density               1599.0   0.996747   0.001887  0.99007   0.9956   \n",
       "pH                    1599.0   3.311113   0.154386  2.74000   3.2100   \n",
       "sulphates             1599.0   0.658149   0.169507  0.33000   0.5500   \n",
       "alcohol               1599.0  10.422983   1.065668  8.40000   9.5000   \n",
       "quality               1599.0   5.636023   0.807569  3.00000   5.0000   \n",
       "\n",
       "                           50%        75%        max  \n",
       "fixed acidity          7.90000   9.200000   15.90000  \n",
       "volatile acidity       0.52000   0.640000    1.58000  \n",
       "citric acid            0.26000   0.420000    1.00000  \n",
       "residual sugar         2.20000   2.600000   15.50000  \n",
       "chlorides              0.07900   0.090000    0.61100  \n",
       "free sulfur dioxide   14.00000  21.000000   72.00000  \n",
       "total sulfur dioxide  38.00000  62.000000  289.00000  \n",
       "density                0.99675   0.997835    1.00369  \n",
       "pH                     3.31000   3.400000    4.01000  \n",
       "sulphates              0.62000   0.730000    2.00000  \n",
       "alcohol               10.20000  11.100000   14.90000  \n",
       "quality                6.00000   6.000000    8.00000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2b1f544a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n",
       "       'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n",
       "       'pH', 'sulphates', 'alcohol', 'quality'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c45303fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1599, 12)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0efce61d",
   "metadata": {},
   "source": [
    "#### Exploring the data and data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ad08cc3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.700</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.99780</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.36</td>\n",
       "      <td>6.10</td>\n",
       "      <td>0.071</td>\n",
       "      <td>17.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0.99780</td>\n",
       "      <td>3.35</td>\n",
       "      <td>0.80</td>\n",
       "      <td>10.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7.9</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.21</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.106</td>\n",
       "      <td>10.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.99660</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0.91</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>7.3</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.36</td>\n",
       "      <td>5.90</td>\n",
       "      <td>0.074</td>\n",
       "      <td>12.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>0.99780</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.83</td>\n",
       "      <td>10.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.05</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.086</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.41</td>\n",
       "      <td>0.39</td>\n",
       "      <td>10.9</td>\n",
       "      <td>5</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1563</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1564</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1567</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1581</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.053</td>\n",
       "      <td>24.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.99402</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.60</td>\n",
       "      <td>11.3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1596</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.076</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.99574</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.75</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "4               7.4             0.700         0.00            1.90      0.076   \n",
       "11              7.5             0.500         0.36            6.10      0.071   \n",
       "27              7.9             0.430         0.21            1.60      0.106   \n",
       "40              7.3             0.450         0.36            5.90      0.074   \n",
       "65              7.2             0.725         0.05            4.65      0.086   \n",
       "...             ...               ...          ...             ...        ...   \n",
       "1563            7.2             0.695         0.13            2.00      0.076   \n",
       "1564            7.2             0.695         0.13            2.00      0.076   \n",
       "1567            7.2             0.695         0.13            2.00      0.076   \n",
       "1581            6.2             0.560         0.09            1.70      0.053   \n",
       "1596            6.3             0.510         0.13            2.30      0.076   \n",
       "\n",
       "      free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "4                    11.0                  34.0  0.99780  3.51       0.56   \n",
       "11                   17.0                 102.0  0.99780  3.35       0.80   \n",
       "27                   10.0                  37.0  0.99660  3.17       0.91   \n",
       "40                   12.0                  87.0  0.99780  3.33       0.83   \n",
       "65                    4.0                  11.0  0.99620  3.41       0.39   \n",
       "...                   ...                   ...      ...   ...        ...   \n",
       "1563                 12.0                  20.0  0.99546  3.29       0.54   \n",
       "1564                 12.0                  20.0  0.99546  3.29       0.54   \n",
       "1567                 12.0                  20.0  0.99546  3.29       0.54   \n",
       "1581                 24.0                  32.0  0.99402  3.54       0.60   \n",
       "1596                 29.0                  40.0  0.99574  3.42       0.75   \n",
       "\n",
       "      alcohol  quality  \n",
       "4         9.4        5  \n",
       "11       10.5        5  \n",
       "27        9.5        5  \n",
       "40       10.5        5  \n",
       "65       10.9        5  \n",
       "...       ...      ...  \n",
       "1563     10.1        5  \n",
       "1564     10.1        5  \n",
       "1567     10.1        5  \n",
       "1581     11.3        5  \n",
       "1596     11.0        6  \n",
       "\n",
       "[240 rows x 12 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d1954e2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b4b7cfe2",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulphates, alcohol, quality]\n",
       "Index: []"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ff4d61e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1359, 12)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9259c293",
   "metadata": {},
   "source": [
    "* As above all features are numeric type we don't need them to change"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "637bd09e",
   "metadata": {},
   "source": [
    "## FEATURES\n",
    "* 1 - fixed acidity\n",
    "* 2 - volatile acidity\n",
    "* 3 - citric acid\n",
    "* 4 - residual sugar\n",
    "* 5 - chlorides\n",
    "* 6 - free sulfur dioxide\n",
    "* 7 - total sulfur dioxide\n",
    "* 8 - density\n",
    "* 9 - pH\n",
    "* 10 - sulphates\n",
    "* 11 - alcohol\n",
    "* Output variable (based on sensory data):\n",
    "* 12 - quality (score between 0 and 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "739cf915",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "C:\\Users\\shekh\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "plt.suptitle(\"Distribution of the data\")\n",
    "plotno=1\n",
    "\n",
    "for i in df:\n",
    "    if plotno<=12:\n",
    "        plt.subplot(5,3,plotno)\n",
    "        sns.distplot(df[i])\n",
    "        plt.xlabel(i)\n",
    "    plotno+=1\n",
    "plt.tight_layout()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92b0ce95",
   "metadata": {},
   "source": [
    "##### we can make following conclusion by observing above distribution plot of features of data:\n",
    "* we that fixed acidity, density, ph are almost symmetric but are little skewed and outliers are present in them\n",
    "* volatile acidity has also skewed and becasue of it has disturbed skeweness\n",
    "* citric acid is largly skewed so we have to handle it\n",
    "* residual sugar, chlorides free sulfur dioxide, sulphates, alcohol are right skewed and outliers present in the tail present in them\n",
    "* clear we can see that above feautres are somewhat symmertic and because of outliers there is a skeweness in it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6fbd7f0f",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fixed acidity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.255124</td>\n",
       "      <td>0.667437</td>\n",
       "      <td>0.111025</td>\n",
       "      <td>0.085886</td>\n",
       "      <td>-0.140580</td>\n",
       "      <td>-0.103777</td>\n",
       "      <td>0.670195</td>\n",
       "      <td>-0.686685</td>\n",
       "      <td>0.190269</td>\n",
       "      <td>-0.061596</td>\n",
       "      <td>0.119024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volatile acidity</th>\n",
       "      <td>-0.255124</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.551248</td>\n",
       "      <td>-0.002449</td>\n",
       "      <td>0.055154</td>\n",
       "      <td>-0.020945</td>\n",
       "      <td>0.071701</td>\n",
       "      <td>0.023943</td>\n",
       "      <td>0.247111</td>\n",
       "      <td>-0.256948</td>\n",
       "      <td>-0.197812</td>\n",
       "      <td>-0.395214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>citric acid</th>\n",
       "      <td>0.667437</td>\n",
       "      <td>-0.551248</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.143892</td>\n",
       "      <td>0.210195</td>\n",
       "      <td>-0.048004</td>\n",
       "      <td>0.047358</td>\n",
       "      <td>0.357962</td>\n",
       "      <td>-0.550310</td>\n",
       "      <td>0.326062</td>\n",
       "      <td>0.105108</td>\n",
       "      <td>0.228057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residual sugar</th>\n",
       "      <td>0.111025</td>\n",
       "      <td>-0.002449</td>\n",
       "      <td>0.143892</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.026656</td>\n",
       "      <td>0.160527</td>\n",
       "      <td>0.201038</td>\n",
       "      <td>0.324522</td>\n",
       "      <td>-0.083143</td>\n",
       "      <td>-0.011837</td>\n",
       "      <td>0.063281</td>\n",
       "      <td>0.013640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chlorides</th>\n",
       "      <td>0.085886</td>\n",
       "      <td>0.055154</td>\n",
       "      <td>0.210195</td>\n",
       "      <td>0.026656</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000749</td>\n",
       "      <td>0.045773</td>\n",
       "      <td>0.193592</td>\n",
       "      <td>-0.270893</td>\n",
       "      <td>0.394557</td>\n",
       "      <td>-0.223824</td>\n",
       "      <td>-0.130988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <td>-0.140580</td>\n",
       "      <td>-0.020945</td>\n",
       "      <td>-0.048004</td>\n",
       "      <td>0.160527</td>\n",
       "      <td>0.000749</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.667246</td>\n",
       "      <td>-0.018071</td>\n",
       "      <td>0.056631</td>\n",
       "      <td>0.054126</td>\n",
       "      <td>-0.080125</td>\n",
       "      <td>-0.050463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <td>-0.103777</td>\n",
       "      <td>0.071701</td>\n",
       "      <td>0.047358</td>\n",
       "      <td>0.201038</td>\n",
       "      <td>0.045773</td>\n",
       "      <td>0.667246</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.078141</td>\n",
       "      <td>-0.079257</td>\n",
       "      <td>0.035291</td>\n",
       "      <td>-0.217829</td>\n",
       "      <td>-0.177855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>density</th>\n",
       "      <td>0.670195</td>\n",
       "      <td>0.023943</td>\n",
       "      <td>0.357962</td>\n",
       "      <td>0.324522</td>\n",
       "      <td>0.193592</td>\n",
       "      <td>-0.018071</td>\n",
       "      <td>0.078141</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.355617</td>\n",
       "      <td>0.146036</td>\n",
       "      <td>-0.504995</td>\n",
       "      <td>-0.184252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pH</th>\n",
       "      <td>-0.686685</td>\n",
       "      <td>0.247111</td>\n",
       "      <td>-0.550310</td>\n",
       "      <td>-0.083143</td>\n",
       "      <td>-0.270893</td>\n",
       "      <td>0.056631</td>\n",
       "      <td>-0.079257</td>\n",
       "      <td>-0.355617</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.214134</td>\n",
       "      <td>0.213418</td>\n",
       "      <td>-0.055245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sulphates</th>\n",
       "      <td>0.190269</td>\n",
       "      <td>-0.256948</td>\n",
       "      <td>0.326062</td>\n",
       "      <td>-0.011837</td>\n",
       "      <td>0.394557</td>\n",
       "      <td>0.054126</td>\n",
       "      <td>0.035291</td>\n",
       "      <td>0.146036</td>\n",
       "      <td>-0.214134</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.091621</td>\n",
       "      <td>0.248835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alcohol</th>\n",
       "      <td>-0.061596</td>\n",
       "      <td>-0.197812</td>\n",
       "      <td>0.105108</td>\n",
       "      <td>0.063281</td>\n",
       "      <td>-0.223824</td>\n",
       "      <td>-0.080125</td>\n",
       "      <td>-0.217829</td>\n",
       "      <td>-0.504995</td>\n",
       "      <td>0.213418</td>\n",
       "      <td>0.091621</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.480343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>quality</th>\n",
       "      <td>0.119024</td>\n",
       "      <td>-0.395214</td>\n",
       "      <td>0.228057</td>\n",
       "      <td>0.013640</td>\n",
       "      <td>-0.130988</td>\n",
       "      <td>-0.050463</td>\n",
       "      <td>-0.177855</td>\n",
       "      <td>-0.184252</td>\n",
       "      <td>-0.055245</td>\n",
       "      <td>0.248835</td>\n",
       "      <td>0.480343</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      fixed acidity  volatile acidity  citric acid  \\\n",
       "fixed acidity              1.000000         -0.255124     0.667437   \n",
       "volatile acidity          -0.255124          1.000000    -0.551248   \n",
       "citric acid                0.667437         -0.551248     1.000000   \n",
       "residual sugar             0.111025         -0.002449     0.143892   \n",
       "chlorides                  0.085886          0.055154     0.210195   \n",
       "free sulfur dioxide       -0.140580         -0.020945    -0.048004   \n",
       "total sulfur dioxide      -0.103777          0.071701     0.047358   \n",
       "density                    0.670195          0.023943     0.357962   \n",
       "pH                        -0.686685          0.247111    -0.550310   \n",
       "sulphates                  0.190269         -0.256948     0.326062   \n",
       "alcohol                   -0.061596         -0.197812     0.105108   \n",
       "quality                    0.119024         -0.395214     0.228057   \n",
       "\n",
       "                      residual sugar  chlorides  free sulfur dioxide  \\\n",
       "fixed acidity               0.111025   0.085886            -0.140580   \n",
       "volatile acidity           -0.002449   0.055154            -0.020945   \n",
       "citric acid                 0.143892   0.210195            -0.048004   \n",
       "residual sugar              1.000000   0.026656             0.160527   \n",
       "chlorides                   0.026656   1.000000             0.000749   \n",
       "free sulfur dioxide         0.160527   0.000749             1.000000   \n",
       "total sulfur dioxide        0.201038   0.045773             0.667246   \n",
       "density                     0.324522   0.193592            -0.018071   \n",
       "pH                         -0.083143  -0.270893             0.056631   \n",
       "sulphates                  -0.011837   0.394557             0.054126   \n",
       "alcohol                     0.063281  -0.223824            -0.080125   \n",
       "quality                     0.013640  -0.130988            -0.050463   \n",
       "\n",
       "                      total sulfur dioxide   density        pH  sulphates  \\\n",
       "fixed acidity                    -0.103777  0.670195 -0.686685   0.190269   \n",
       "volatile acidity                  0.071701  0.023943  0.247111  -0.256948   \n",
       "citric acid                       0.047358  0.357962 -0.550310   0.326062   \n",
       "residual sugar                    0.201038  0.324522 -0.083143  -0.011837   \n",
       "chlorides                         0.045773  0.193592 -0.270893   0.394557   \n",
       "free sulfur dioxide               0.667246 -0.018071  0.056631   0.054126   \n",
       "total sulfur dioxide              1.000000  0.078141 -0.079257   0.035291   \n",
       "density                           0.078141  1.000000 -0.355617   0.146036   \n",
       "pH                               -0.079257 -0.355617  1.000000  -0.214134   \n",
       "sulphates                         0.035291  0.146036 -0.214134   1.000000   \n",
       "alcohol                          -0.217829 -0.504995  0.213418   0.091621   \n",
       "quality                          -0.177855 -0.184252 -0.055245   0.248835   \n",
       "\n",
       "                       alcohol   quality  \n",
       "fixed acidity        -0.061596  0.119024  \n",
       "volatile acidity     -0.197812 -0.395214  \n",
       "citric acid           0.105108  0.228057  \n",
       "residual sugar        0.063281  0.013640  \n",
       "chlorides            -0.223824 -0.130988  \n",
       "free sulfur dioxide  -0.080125 -0.050463  \n",
       "total sulfur dioxide -0.217829 -0.177855  \n",
       "density              -0.504995 -0.184252  \n",
       "pH                    0.213418 -0.055245  \n",
       "sulphates             0.091621  0.248835  \n",
       "alcohol               1.000000  0.480343  \n",
       "quality               0.480343  1.000000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8095e68a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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X8jfXXxVr19/vBxR09vqzxsXbQ0U5eTKV2G8PEYOzo3ya1dbpTfvKNppMOv3bPvm1sf5Z6de6vk7/ts9iW+qGPeXGuwT5KqhzS51YVn4bTCrtnVqUbh9fygzOjvJvVltJmyzfo0mb9qtKOddZlTb1lLzJ8j2auHGvqlzkGnP2cZfJaFRR5hnzNtdAH7V+ebi2jXnH7hLkFpyc5Nq4vs78satsm8mkvD92y61540s6hMHNVXJykjEz22K7W9tmCv/fCtX44QMFzhgjB1/vK1nyCkcb98oIqBEsn2B/RW8uu5/lZ+cpPiJG4f/gPLqfPY9nMuzj/vVvhdUMVZWQKtq1qey9m5t9RlERB9W4daOL7vvknDH6Y/027fp9t62LCVygX79+euWVVzRz5ky1aNFCERERWrt2rTmPEh8fb5HrmD59usaNG6fp06ercePGGjZsmLp27ar33nvPZmWstHPC+fv766677tKyZct0xx13SJJWrlypwMBAderUSZL0yiuvaPDgwRo9unS43NixY/XHH3/olVdeMcecb/r06eZ/h4eHa/z48Vq+fLkmTpwod3d3eXl5ycnJqdwxw9a8+eabatmypebOnWvetnjxYtWoUUPR0dFq0ODCG3y1atU0fvx48/MxY8bop59+0hdffKEbbrhB2dnZWrBggd5880098kjp0LW6deuqY8eOVsvwV4/AV199VZLUsGFD7du3Ty+++KLV+PLq2qFDB3OPwokTJ0qSlixZogceeEBeXhd+iZNKlw0+f5ngElOJHA22yRyfyzeodJ6+rJQMi+1ZKZnyDfK7pGMYDAb1mzlEh7dH6VT0cUlSUM3SN+ndT/XVl3M/VnxknDrce6vGfTZLs7o+fdG5OHBtCg4unX8xNeW0xfbUlNMKOm+IzLkidu7TuCem62hMnIJDgvTUxFH6ctVSdel4r3JzSr9wfffVap08nqCkxBQ1alJfk2c9rbr1wvXoI2NtV6F/yS3YT5KUn5JlsT0/JUtuwdaHGLkGeMvByVH5KZmW+6RmyrdemCTJPdhXJQVFKso6YxmTkin3co4b2Ka+at3dThsefsW8zbt2iFpO7aef73mu0iZPXAJ85ODkqILzzkdBSqa86lW1uo9rsJ/V+L/+P6TS+d8SVm3XmfhkeYaH6Lqp/dRu2ST93mOmZCztVh/7wVpl7otVYXquAto20HVT+8k12E+Rsz+9spW0Efez9c077/rLS80q9zr56/rLS7U8f3kpmfKtG2Z9H38vNX+qjw59dvHEUmX317VWaOXa8axfzeo+rsF+VuNdyzm/1freouKcfPNQVGs8wkNUc1g3HXrGPq6zcu9ZKVnyLuc96hbkd0H8+e/Rczm4OqvZ9AGK/3arinPK5h1su2CUjn6yXul7YuVR/dLn/61sHP19ZHByVMnpDIvtxafT5V67xiUdo8rYYSpJOa28rWXJgLzNO5T7y2YVn0yUU40wVXlyiMLenaOTg576x8OXKivauFeGz9lzlX3e+zI7JVPe/+A89p75iI5uP6jE6BNXuISVk39QgCQpPTXDYnt6Srr8g8qfJ73T3bepXtN6Gt3jCVsWD7ioJ554Qk88Yf0a3Lhxo8VzJycnzZo1S7NmzboKJTv7mlftlS7DoEGDNGLECL399ttydXXVZ599pv79+5vH7EZFRWnkyJEW+9x0001asGBBucdcsWKF3njjDR05ckQ5OTkqLi6Wj4/1eT0u1Z49e7RhwwarSaojR45YTcKVlJRo7ty5+uKLL3Ty5EkVFhaqoKBAHh4e5roVFBSYE5B/JyoqSu3atbPYVt64578zfPhwLVq0SBMnTlRSUpLWrFmjX3/9tdz4efPm6ZlnnrHY1tK3kVr5XdovnP9Eu94366G5Zf/nbwz99/N/DHpuuKo1rKEX7y9L0BoMpdfY/5at0+YvS798rTgQq0Ydmqpj39v19Uv2PTQEf6/P/d0199WZ5udDBjx+WcfZuP53878PRh5WxM592rxnrXr27qoVn30jSfr846/MMYeiDis5KVWff/uBaoZXV3xc5Wjshd/TQe1eKpsKYMNDr1wk+urxbVhdty15Wnvnf6OE/5X2PjE4GNTxrce195WvlH302voycSlOfbfV/O/sg8eVFRmvO7YtUGCHxko9Ozfe0fdWl8VExctYVKxmLw3TwbnLZayEw5Hq3NNB7V8su/5+edj215+zl7s6fzxeGdEnFfFq5exNWZlUG3CbEr7+XcaCIqt/dw31V+vlU5T4wx868Wn5bYr/EoOTo9q/N0YySLsmLTFvrzesq5y93BT1xncVWLrKwW9YX3nddZtODZkgU2HZtZWz5n/mfxcejlNhdKxqrf1I7m2bKe/PiAoo6b9HG/fKaNX7Jj0wt2wezw+GWu+Q8E/c+9xQhTWsoYX3X70v6VfbHffcrqdfeNL8fOoj0y8SbV1QWJAef+YxTRw4WUXlfBbgCrpG53D8L6jUSbhevXrJZDJp1apVatu2rTZt2mQeOno5tm7dqkGDBumZZ55R165d5evrq+XLl5t7j12unJwc9erVy2qvs7Aw67+uv/zyy1qwYIFef/11NW3aVJ6ennrqqadUWFi6IpG7u/u/KtO/8fDDD2vy5MnaunWrtmzZotq1a+vmm28uN37KlCkaO9ayx86TTS+ceP5KiPhlu2IjDpufO7mUXsI+QX7KPOeXQp8gXx2PjPvb4w18Zpia3d5aL/WdqfTENPP2zOTSSZATDh+3iE84ckIBVS1XFMS1ad3ajdq9s2zogotL6eILgUFVlJxUNt9jYFAVRZazwps1WVnZij1yTLXqlN8D4K/XDa9ds9Ik4U78vEup56yi6Hj2vecW5KO85AzzdrcgH6UfsL5abEFatozFJXILsuxJ4xboq7yzv1DnJWfK0dW5dMjaOb3h3IJ8lZds+Su2b/2q6vzFFB3+dIP2Lyj7surk5a4qLerI//paajun9F5kcDDI4OCggfEfaf2AF5W0OfIyzsKVVZiWJWNxiVzPOx+uQb4qOOecnqsgOcNqfH458ZJ0Jj5ZBaez5Fk71JyEO1/6rhg5ODuVrrh6pPKt/Bb/8y6lWLn+3M+7/twDfZT2N9efe6Dl+XMPKrv+/uLk6aY7P5ugotx8bRj+ukzF9rOSpzV/XWsu//Basx6feUGsf7vr5FW/mvaMtP4jqGuIv274eqYytkfrwLj3L68SFaDce1aQj/KtnAdJyk/JuCDe2nvU4OSo9ovGyKN6oP73wFyLXnDBHRurSuv6uu/YRxb7dF77nOK/3qztT9puiMyVVpKeJVNxiRyr+Flsd6rir5LUiy844Tv4fvkN66eEEZNVGB170djiE4kqScuQc82qdpuEo417ZRz4ZafiI8rmgXV0KV1EwDvIV9nnnEfvIF+djPz71YbvfWaIGt/eSm/1na3Mc87jtWbLz1sVtfug+bnz2fPmH+intOSyevsH+evIAeuLLTRoVl/+Qf56d83b5m2OTo5q1q6p+gzurW51elww3zvwX1Spk3Bubm6699579dlnnykmJkYNGzZUq1atzH9v1KiRNm/ebB6uKUmbN29W48bWe2Bt2bJFtWrV0rRpZcuXHztmefN1cXFRSck/a2y3atVKX331lcLDwy95tdLNmzerd+/eevDBByWVLsIQHR1tLnv9+vXl7u6u9evXm5fLvZhGjRrp+++/t9j2xx8XX7WtvLpWqVJFffr00ZIlS7R161bzJIblsbZssK2Gohbk5is517JnS0Zyuhp1aGpukLh5uatOi/ra+OnPFz3WwGeGqWXXG/Ry/1lKPZFs8bfUE8lKTzytkDqWw3RCalfVvo3Mb/BfkJtzxjxc9C/JiSm66ZZ25qSbl7enWrRuqk+XfHHJx/XwdFet8Br6+osfy41pcn3D0tdLqjyTvhfn5isnN99iW15ShkI7NjEn3Zy93BXYsq6iP15v7RAyFpUobW+sQjs20Ym1O0s3GgwK7dhE0UvXSZLS9saqpLBYoR2b6Pjq7ZIkn7ph8qoeqNSdZV9OfBtUU+cvp+rol5u058UvLV6nKDtPP3SynBOzwSOdFdqxsX4b8YZy4ivHeTUVlShzb6wCb75eiWt3lG40GBTYsYniFlu/f6XtPKzAm5so9v015m1BtzRV+o7DVuMlyS0sQC7+XspPyig3xrdJLZlKjCpMzSo3piIV5+Yr+7zr70xShsI6NjEn3Zy93BXUsq4OXeT6O703VmEdmyj+p7LrL6xjEx1css4c5+zlrjuXTZSxoFjrB89XyTXwa76pqERZe2NV5ebrlbym7FqrcvP1OlbOqrgZOw+X/n1R2bVW5dZmytgRfUFs9YGdlBlxRNmRFyZAXUNLE3BZe49q35PvSDZaacwWTEUlSt8bq+COTXTqnHtWcMfrFbPE+nv09I4YBXdsosPvrzVvC7nlep0+Z3GYvxJwXrVDtfH+OSo8b4683dM/1v4Xyu5r7qH+umX5ZP0xaqHSdtnZSoPFxSqIPCyPdi115tezvXQNBrm3a6HMz78vdze/IQ/Ib+QAJTw6VQUHyr+//cUxJFAOfj4qTrHfJAlt3CujIDdfBed9XmQlp6t+h+t16mzSzdXLXTVb1NPmT9dZO4TZvc8MUdOubfVW/2eVdqJytB1sJS83T3m5eRbbTiedVquOLXUk8qgkycPLQ41aXKcfPrbeht31+24Nu8NylNqEV8fp+JHjWv72FyTggLMqdRJOKh2S2rNnTx04cMCcsPrLhAkT1LdvX7Vs2VKdO3fWDz/8oK+//lq//PKL1WPVr19f8fHxWr58udq2batVq1bpm2++sYgJDw9XbGysIiIiVL16dXl7e1+QYDrf448/rvfff18DBgzQxIkTFRAQoJiYGC1fvlwffPCB1VU16tevr5UrV2rLli3y9/fX/PnzlZSUZE7Cubm5adKkSZo4caJcXFx00003KSUlRQcOHNCwYcMuON6oUaP06quvasKECRo+fLh27txpXtm1PBer6/Dhw9WzZ0+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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.heatmap(df.corr(), annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d7e1346",
   "metadata": {},
   "source": [
    "##### We can make make following conclusion after making observation from above heatmap\n",
    "* we can see negative correlation btw volatile and citric acid, ph and citric acid that is -0.55\n",
    "* we can see negative correlation btw pH and fixed acidity that is -0.69\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb94df20",
   "metadata": {},
   "outputs": [],
   "source": [
    "##### AS we know that our target column is quality so we compare it with every other feature in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b6283ec1",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=df.drop('quality', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a15cc256",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "plotno=1\n",
    "\n",
    "for i in a:\n",
    "    if plotno<=10:\n",
    "        plt.subplot(5,3,plotno)\n",
    "        sns.barplot(data=df, x=df['quality'], y=df[i])\n",
    "        plt.title(f'{i} vs Quality')\n",
    "    plotno+=1\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16aea255",
   "metadata": {},
   "source": [
    "### we can make following conclusion by observing above barplots\n",
    "* as the fixed acidity is increased quality of wine increases but it is not so obvious here\n",
    "* as volatile acidity increases quality og wine decreases\n",
    "* as levels of citric acid increases quality of wine increases\n",
    "* as the chlorides increases quality decreases, less chlorides good quality\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e50c2593",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.boxplot(data=df)\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c1447f8",
   "metadata": {},
   "source": [
    "* as we can see that there is minimum number of outliers present in the most of the features\n",
    "* we will handle all the outliers present but removing all the outliers can cause damage to the data so we will remove whats necessary\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "11dd22cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Making binary classificaion for the response variable.\n",
    "#Dividing wine as good and bad by giving the limit for the quality\n",
    "bins = (2, 6.5, 8)\n",
    "group_names = ['bad', 'good']\n",
    "df['quality'] = pd.cut(df['quality'], bins = bins, labels = group_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "66c110ad",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.098</td>\n",
       "      <td>25.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.9968</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.68</td>\n",
       "      <td>9.8</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.092</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.9970</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>9.8</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.2</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.075</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.8</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.075</td>\n",
       "      <td>13.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>bad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.4              0.70         0.00             1.9      0.076   \n",
       "1            7.8              0.88         0.00             2.6      0.098   \n",
       "2            7.8              0.76         0.04             2.3      0.092   \n",
       "3           11.2              0.28         0.56             1.9      0.075   \n",
       "5            7.4              0.66         0.00             1.8      0.075   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
       "5                 13.0                  40.0   0.9978  3.51       0.56   \n",
       "\n",
       "   alcohol quality  \n",
       "0      9.4     bad  \n",
       "1      9.8     bad  \n",
       "2      9.8     bad  \n",
       "3      9.8     bad  \n",
       "5      9.4     bad  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fe4fa51d",
   "metadata": {},
   "outputs": [],
   "source": [
    "quality_label=LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e9b4af18",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Bad becomes 0 and good becomes 1 \n",
    "df['quality'] = quality_label.fit_transform(df['quality'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6feb50e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1175\n",
       "1     184\n",
       "Name: quality, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['quality'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2905657b",
   "metadata": {},
   "source": [
    "# increasing the SVC accuracy using the hyperparameter gridsearch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "09e924ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=df.drop('quality', axis=1)\n",
    "y=df['quality']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d87a946e",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.098</td>\n",
       "      <td>25.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.9968</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.68</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.092</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.9970</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.2</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.075</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.075</td>\n",
       "      <td>13.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.4              0.70         0.00             1.9      0.076   \n",
       "1            7.8              0.88         0.00             2.6      0.098   \n",
       "2            7.8              0.76         0.04             2.3      0.092   \n",
       "3           11.2              0.28         0.56             1.9      0.075   \n",
       "5            7.4              0.66         0.00             1.8      0.075   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
       "5                 13.0                  40.0   0.9978  3.51       0.56   \n",
       "\n",
       "   alcohol  \n",
       "0      9.4  \n",
       "1      9.8  \n",
       "2      9.8  \n",
       "3      9.8  \n",
       "5      9.4  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c802bdf8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    0\n",
       "2    0\n",
       "3    0\n",
       "5    0\n",
       "Name: quality, dtype: int32"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4572623f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Train and Test splitting of data \n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.2, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b106b636",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler=StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9e65eaa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = scaler.fit_transform(x_train)\n",
    "X_test = scaler.fit_transform(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b3ad456",
   "metadata": {},
   "source": [
    "## peforming Support vector classifier without increasing the accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9ca4bd65",
   "metadata": {},
   "outputs": [],
   "source": [
    "svc = SVC() #CREATING THE SVC OBJECT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "56eebc17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#train the model\n",
    "svc.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9999eca1",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_svc = svc.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ea45ece1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_svc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7622b7a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7b336689",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9191176470588235"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,pred_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5176c4ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "#lets increase the accuracy using gridsearchcv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f10b5775",
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8b17b80b",
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_svc = GridSearchCV(svc, param_grid=parameters, scoring='accuracy', cv=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8be06cf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=10, estimator=SVC(),\n",
       "             param_grid={'C': [1, 10], 'kernel': ('linear', 'rbf')},\n",
       "             scoring='accuracy')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_svc.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "c931c24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_predict=grid_svc.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "dcd75a18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "000fa3a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9191176470588235"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, grid_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0419ed99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=1.2, gamma=0.9)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# doing grid search again\n",
    "svc2 = SVC(C = 1.2, gamma =  0.9, kernel= 'rbf')\n",
    "svc2.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "95eb1a92",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_svc2 = svc2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "38ebcd8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,\n",
       "       1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_svc2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "56ee5ee7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9044117647058824"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, pred_svc2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d4e52b33",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Performing SVR(SUPORT VECTOR REGRESSION) on Admission dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c7ca9771",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2=pd.read_csv(\"C:\\\\Users\\\\shekh\\\\Downloads\\\\Admission_Predict_Ver1.1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "847ab23b",
   "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",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Serial No.</th>\n",
       "      <th>GRE Score</th>\n",
       "      <th>TOEFL Score</th>\n",
       "      <th>University Rating</th>\n",
       "      <th>SOP</th>\n",
       "      <th>LOR</th>\n",
       "      <th>CGPA</th>\n",
       "      <th>Research</th>\n",
       "      <th>Chance of Admit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>337</td>\n",
       "      <td>118</td>\n",
       "      <td>4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>9.65</td>\n",
       "      <td>1</td>\n",
       "      <td>0.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>324</td>\n",
       "      <td>107</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>8.87</td>\n",
       "      <td>1</td>\n",
       "      <td>0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>316</td>\n",
       "      <td>104</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>8.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>322</td>\n",
       "      <td>110</td>\n",
       "      <td>3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>8.67</td>\n",
       "      <td>1</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>314</td>\n",
       "      <td>103</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.21</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>496</td>\n",
       "      <td>332</td>\n",
       "      <td>108</td>\n",
       "      <td>5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.02</td>\n",
       "      <td>1</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>497</td>\n",
       "      <td>337</td>\n",
       "      <td>117</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.87</td>\n",
       "      <td>1</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>498</td>\n",
       "      <td>330</td>\n",
       "      <td>120</td>\n",
       "      <td>5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.56</td>\n",
       "      <td>1</td>\n",
       "      <td>0.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>499</td>\n",
       "      <td>312</td>\n",
       "      <td>103</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.43</td>\n",
       "      <td>0</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>500</td>\n",
       "      <td>327</td>\n",
       "      <td>113</td>\n",
       "      <td>4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>9.04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Serial No.  GRE Score  TOEFL Score  University Rating  SOP  LOR   CGPA  \\\n",
       "0             1        337          118                  4  4.5   4.5  9.65   \n",
       "1             2        324          107                  4  4.0   4.5  8.87   \n",
       "2             3        316          104                  3  3.0   3.5  8.00   \n",
       "3             4        322          110                  3  3.5   2.5  8.67   \n",
       "4             5        314          103                  2  2.0   3.0  8.21   \n",
       "..          ...        ...          ...                ...  ...   ...   ...   \n",
       "495         496        332          108                  5  4.5   4.0  9.02   \n",
       "496         497        337          117                  5  5.0   5.0  9.87   \n",
       "497         498        330          120                  5  4.5   5.0  9.56   \n",
       "498         499        312          103                  4  4.0   5.0  8.43   \n",
       "499         500        327          113                  4  4.5   4.5  9.04   \n",
       "\n",
       "     Research  Chance of Admit   \n",
       "0           1              0.92  \n",
       "1           1              0.76  \n",
       "2           1              0.72  \n",
       "3           1              0.80  \n",
       "4           0              0.65  \n",
       "..        ...               ...  \n",
       "495         1              0.87  \n",
       "496         1              0.96  \n",
       "497         1              0.93  \n",
       "498         0              0.73  \n",
       "499         0              0.84  \n",
       "\n",
       "[500 rows x 9 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7e79c4ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Serial No.', 'GRE Score', 'TOEFL Score', 'University Rating', 'SOP',\n",
       "       'LOR ', 'CGPA', 'Research', 'Chance of Admit '],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "747314ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.columns=df2.columns.str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "65d86b6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Serial No.', 'GRE Score', 'TOEFL Score', 'University Rating', 'SOP',\n",
       "       'LOR', 'CGPA', 'Research', 'Chance of Admit'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "db9b90d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=df2.drop('Chance of Admit', axis=1)\n",
    "b=df2['Chance of Admit']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "24df1d18",
   "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>Serial No.</th>\n",
       "      <th>GRE Score</th>\n",
       "      <th>TOEFL Score</th>\n",
       "      <th>University Rating</th>\n",
       "      <th>SOP</th>\n",
       "      <th>LOR</th>\n",
       "      <th>CGPA</th>\n",
       "      <th>Research</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>337</td>\n",
       "      <td>118</td>\n",
       "      <td>4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>9.65</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>324</td>\n",
       "      <td>107</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>8.87</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>316</td>\n",
       "      <td>104</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>8.00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>322</td>\n",
       "      <td>110</td>\n",
       "      <td>3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>8.67</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>314</td>\n",
       "      <td>103</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Serial No.  GRE Score  TOEFL Score  University Rating  SOP  LOR  CGPA  \\\n",
       "0           1        337          118                  4  4.5  4.5  9.65   \n",
       "1           2        324          107                  4  4.0  4.5  8.87   \n",
       "2           3        316          104                  3  3.0  3.5  8.00   \n",
       "3           4        322          110                  3  3.5  2.5  8.67   \n",
       "4           5        314          103                  2  2.0  3.0  8.21   \n",
       "\n",
       "   Research  \n",
       "0         1  \n",
       "1         1  \n",
       "2         1  \n",
       "3         1  \n",
       "4         0  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a5e20f96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.92\n",
       "1    0.76\n",
       "2    0.72\n",
       "3    0.80\n",
       "4    0.65\n",
       "Name: Chance of Admit, dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "7f979c7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "svr=SVR()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "8ca0e1e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVR()"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "b9018ec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Train and Test splitting of data \n",
    "a_train, a_test, b_train, b_test = train_test_split(a, b, test_size = 0.2, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "86113a8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaled=StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "ab50b389",
   "metadata": {},
   "outputs": [],
   "source": [
    "A_train = scaler.fit_transform(a_train)\n",
    "A_test = scaler.fit_transform(a_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "2630ac75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVR()"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svr.fit(A_train, b_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9e3194b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "svr_predict=svr.predict(A_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "bb7e2ec5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.85836204, 0.74285984, 0.59313567, 0.68769681, 0.79012905,\n",
       "       0.85237763, 0.50621352, 0.64618803, 0.73835474, 0.76391515,\n",
       "       0.60242062, 0.71633606, 0.64322537, 0.89372726, 0.80955004,\n",
       "       0.45964503, 0.79629897, 0.5216186 , 0.52747205, 0.59542898,\n",
       "       0.67713195, 0.55031366, 0.74348241, 0.78552294, 0.74614562,\n",
       "       0.60890196, 0.85029883, 0.848458  , 0.61035801, 0.76079577,\n",
       "       0.58458253, 0.75402981, 0.60723793, 0.84534291, 0.60308779,\n",
       "       0.76729333, 0.52010027, 0.88760194, 0.67816604, 0.68585995,\n",
       "       0.8796056 , 0.53329685, 0.65686509, 0.86188072, 0.86873954,\n",
       "       0.49786761, 0.88326648, 0.77864555, 0.77622701, 0.86633699,\n",
       "       0.82782111, 0.57161906, 0.67777614, 0.54418799, 0.90559769,\n",
       "       0.57921764, 0.8771188 , 0.63036637, 0.68770512, 0.44920983,\n",
       "       0.61228566, 0.72786084, 0.6126474 , 0.63357822, 0.46934858,\n",
       "       0.5640784 , 0.84543931, 0.84885506, 0.68495279, 0.70725196,\n",
       "       0.67121471, 0.7946378 , 0.70285112, 0.60642004, 0.52131664,\n",
       "       0.71919945, 0.80022504, 0.85598958, 0.47221817, 0.62399534,\n",
       "       0.68096067, 0.80802995, 0.66219761, 0.81461567, 0.75476309,\n",
       "       0.67052933, 0.6213321 , 0.74200035, 0.77997502, 0.70801854,\n",
       "       0.75574611, 0.84577237, 0.88275618, 0.70721259, 0.77967803,\n",
       "       0.47544668, 0.64680698, 0.69904447, 0.73310456, 0.56379101])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svr_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2e15aa5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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