Random_Forest.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wine Quality\n",
    "\n",
    "In this notebook, we would like to build a model that assigns a score to a wine according to its physicochemical attributes. The dataset can be downloaded from [kaggle](https://www.kaggle.com/yasserh/wine-quality-dataset) or from the [UCI machine learning repository](https://archive.ics.uci.edu/ml/datasets/wine+quality)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Libraries\n",
    "\n",
    "import os, types\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, precision_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from imblearn.over_sampling import SMOTE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0. Dataset\n",
    "\n",
    "First we will load the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>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",
       "Id                                                                            \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",
       "Id                                                                        \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",
       "Id                    \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": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df = pd.read_csv(\"WineQT.csv\", index_col=\"Id\")\n",
    "wine_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we will do an exploratory data analysis (EDA), to gather first insights and determine the model steps. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1143 entries, 0 to 1597\n",
      "Data columns (total 12 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   fixed acidity         1143 non-null   float64\n",
      " 1   volatile acidity      1143 non-null   float64\n",
      " 2   citric acid           1143 non-null   float64\n",
      " 3   residual sugar        1143 non-null   float64\n",
      " 4   chlorides             1143 non-null   float64\n",
      " 5   free sulfur dioxide   1143 non-null   float64\n",
      " 6   total sulfur dioxide  1143 non-null   float64\n",
      " 7   density               1143 non-null   float64\n",
      " 8   pH                    1143 non-null   float64\n",
      " 9   sulphates             1143 non-null   float64\n",
      " 10  alcohol               1143 non-null   float64\n",
      " 11  quality               1143 non-null   int64  \n",
      "dtypes: float64(11), int64(1)\n",
      "memory usage: 116.1 KB\n"
     ]
    }
   ],
   "source": [
    "wine_df.info() #there are no missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5    483\n",
       "6    462\n",
       "7    143\n",
       "4     33\n",
       "8     16\n",
       "3      6\n",
       "Name: quality, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Let us see the distribution of our data\n",
    "#Classes are very unbalanced\n",
    "wine_df[\"quality\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>count</th>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "      <td>1143.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.311111</td>\n",
       "      <td>0.531339</td>\n",
       "      <td>0.268364</td>\n",
       "      <td>2.532152</td>\n",
       "      <td>0.086933</td>\n",
       "      <td>15.615486</td>\n",
       "      <td>45.914698</td>\n",
       "      <td>0.996730</td>\n",
       "      <td>3.311015</td>\n",
       "      <td>0.657708</td>\n",
       "      <td>10.442111</td>\n",
       "      <td>5.657043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.747595</td>\n",
       "      <td>0.179633</td>\n",
       "      <td>0.196686</td>\n",
       "      <td>1.355917</td>\n",
       "      <td>0.047267</td>\n",
       "      <td>10.250486</td>\n",
       "      <td>32.782130</td>\n",
       "      <td>0.001925</td>\n",
       "      <td>0.156664</td>\n",
       "      <td>0.170399</td>\n",
       "      <td>1.082196</td>\n",
       "      <td>0.805824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.600000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.012000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.990070</td>\n",
       "      <td>2.740000</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.100000</td>\n",
       "      <td>0.392500</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>0.070000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.995570</td>\n",
       "      <td>3.205000</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>0.079000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>0.996680</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>0.620000</td>\n",
       "      <td>10.200000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.100000</td>\n",
       "      <td>0.640000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>0.997845</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>15.900000</td>\n",
       "      <td>1.580000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>0.611000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>1.003690</td>\n",
       "      <td>4.010000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>14.900000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
       "count    1143.000000       1143.000000  1143.000000     1143.000000   \n",
       "mean        8.311111          0.531339     0.268364        2.532152   \n",
       "std         1.747595          0.179633     0.196686        1.355917   \n",
       "min         4.600000          0.120000     0.000000        0.900000   \n",
       "25%         7.100000          0.392500     0.090000        1.900000   \n",
       "50%         7.900000          0.520000     0.250000        2.200000   \n",
       "75%         9.100000          0.640000     0.420000        2.600000   \n",
       "max        15.900000          1.580000     1.000000       15.500000   \n",
       "\n",
       "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
       "count  1143.000000          1143.000000           1143.000000  1143.000000   \n",
       "mean      0.086933            15.615486             45.914698     0.996730   \n",
       "std       0.047267            10.250486             32.782130     0.001925   \n",
       "min       0.012000             1.000000              6.000000     0.990070   \n",
       "25%       0.070000             7.000000             21.000000     0.995570   \n",
       "50%       0.079000            13.000000             37.000000     0.996680   \n",
       "75%       0.090000            21.000000             61.000000     0.997845   \n",
       "max       0.611000            68.000000            289.000000     1.003690   \n",
       "\n",
       "                pH    sulphates      alcohol      quality  \n",
       "count  1143.000000  1143.000000  1143.000000  1143.000000  \n",
       "mean      3.311015     0.657708    10.442111     5.657043  \n",
       "std       0.156664     0.170399     1.082196     0.805824  \n",
       "min       2.740000     0.330000     8.400000     3.000000  \n",
       "25%       3.205000     0.550000     9.500000     5.000000  \n",
       "50%       3.310000     0.620000    10.200000     6.000000  \n",
       "75%       3.400000     0.730000    11.100000     6.000000  \n",
       "max       4.010000     2.000000    14.900000     8.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=wine_df, orient=\"h\")\n",
    "wine_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "boxplot_colors = [\"firebrick\", \"coral\", \"orange\", \"forestgreen\", \"limegreen\", \"mediumaquamarine\",\n",
    "                  \"blue\", \"royalblue\", \"deepskyblue\",\"darkviolet\", \"mediumslateblue\", \"orchid\"]\n",
    "\n",
    "fig, axs = plt.subplots(4, 3, figsize=(12,9))\n",
    "\n",
    "v=0\n",
    "for i in np.arange(4):\n",
    "    for j in np.arange(3):\n",
    "        sns.boxplot(x=wine_df[wine_df.columns[j+v]], ax=axs[i,j], color=boxplot_colors[j+v])\n",
    "        axs[i,j].set_title(wine_df.columns[j+v])\n",
    "    v=v+3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Analyze correlation between numerical variables\n",
    "fig, ax = plt.subplots(figsize=(10,10)) \n",
    "sns.heatmap(wine_df.corr().abs(), annot=True, linewidths=0.5, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\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",
       "    <tr>\n",
       "      <th>quality</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.45</td>\n",
       "      <td>0.8175</td>\n",
       "      <td>0.050</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>5.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.997565</td>\n",
       "      <td>3.355</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.60</td>\n",
       "      <td>0.6750</td>\n",
       "      <td>0.070</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.0780</td>\n",
       "      <td>12.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.996640</td>\n",
       "      <td>3.380</td>\n",
       "      <td>0.56</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7.80</td>\n",
       "      <td>0.5900</td>\n",
       "      <td>0.230</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0810</td>\n",
       "      <td>14.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.996920</td>\n",
       "      <td>3.300</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.90</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>0.245</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0785</td>\n",
       "      <td>14.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.996520</td>\n",
       "      <td>3.320</td>\n",
       "      <td>0.64</td>\n",
       "      <td>10.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.70</td>\n",
       "      <td>0.3600</td>\n",
       "      <td>0.400</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.0730</td>\n",
       "      <td>12.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.995680</td>\n",
       "      <td>3.270</td>\n",
       "      <td>0.74</td>\n",
       "      <td>11.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.85</td>\n",
       "      <td>0.3550</td>\n",
       "      <td>0.455</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.0715</td>\n",
       "      <td>6.5</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.995580</td>\n",
       "      <td>3.225</td>\n",
       "      <td>0.73</td>\n",
       "      <td>11.750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
       "quality                                                                 \n",
       "3                 7.45            0.8175        0.050             2.1   \n",
       "4                 7.60            0.6750        0.070             2.1   \n",
       "5                 7.80            0.5900        0.230             2.2   \n",
       "6                 7.90            0.5000        0.245             2.2   \n",
       "7                 8.70            0.3600        0.400             2.3   \n",
       "8                 8.85            0.3550        0.455             2.1   \n",
       "\n",
       "         chlorides  free sulfur dioxide  total sulfur dioxide   density  \\\n",
       "quality                                                                   \n",
       "3           0.0800                  5.5                  15.0  0.997565   \n",
       "4           0.0780                 12.0                  32.0  0.996640   \n",
       "5           0.0810                 14.0                  46.0  0.996920   \n",
       "6           0.0785                 14.0                  35.0  0.996520   \n",
       "7           0.0730                 12.0                  28.0  0.995680   \n",
       "8           0.0715                  6.5                  18.0  0.995580   \n",
       "\n",
       "            pH  sulphates  alcohol  \n",
       "quality                             \n",
       "3        3.355       0.56    9.825  \n",
       "4        3.380       0.56   10.000  \n",
       "5        3.300       0.58    9.700  \n",
       "6        3.320       0.64   10.500  \n",
       "7        3.270       0.74   11.600  \n",
       "8        3.225       0.73   11.750  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#grouping data to see if we observe significant differences between classes\n",
    "wine_df.groupby([\"quality\"]).median()\n",
    "\n",
    "#volatile acidity, sulphates, citric acid and fixed acidity are ordered. This may suggest that these variables have an influence on the ranking. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Build a Model\n",
    "\n",
    "We will build a Random Forest Classifier. We will compare two metrics: accuracy and precision. \n",
    "\n",
    "* precision = tp / (tp + fp)\n",
    "* accuracy = (tp + tn) / (tp + tn + fp + fn) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test data: (array([3, 4, 5, 6, 7, 8]), array([  2,   9, 151, 137,  41,   3]))\n",
      "train data: (array([3, 4, 5, 6, 7, 8]), array([  4,  24, 332, 325, 102,  13]))\n"
     ]
    }
   ],
   "source": [
    "#define X and y\n",
    "X = wine_df.iloc[:,:-1].to_numpy()\n",
    "y = wine_df[\"quality\"].to_numpy()\n",
    "\n",
    "#test-train split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)\n",
    "print(\"test data:\", np.unique(y_test.flatten(), return_counts=True))\n",
    "print(\"train data:\" ,np.unique(y_train.flatten(), return_counts=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy for train data: 1.0\n",
      "accuracy for test data: 0.6530612244897959\n",
      "accuracy for original data: 0.8958880139982502\n",
      " \n",
      "precision for train data: 1.0\n",
      "precision for test data: 0.3329330168039845\n",
      "precision for original data: 0.9384341961104666\n"
     ]
    }
   ],
   "source": [
    "#define the model\n",
    "forest = RandomForestClassifier(random_state=0)\n",
    "\n",
    "#fit the model\n",
    "forest.fit(X_train,y_train)\n",
    "\n",
    "#compute predictions\n",
    "predictions_test = forest.predict(X_test)\n",
    "predictions_train = forest.predict(X_train)\n",
    "predictions_original = forest.predict(X)\n",
    "\n",
    "#compute accuracy\n",
    "accuracy_test = accuracy_score(y_test, predictions_test)\n",
    "accuracy_train = accuracy_score(y_train, predictions_train)\n",
    "accuracy_original = accuracy_score(y, predictions_original)\n",
    "\n",
    "#compute precision\n",
    "precision_test = precision_score(y_test, predictions_test, average='macro', zero_division=0)\n",
    "precision_train = precision_score(y_train, predictions_train, average='macro', zero_division=0)\n",
    "precision_original = precision_score(y, predictions_original, average='macro', zero_division=0)\n",
    "\n",
    "print(\"accuracy for train data:\", accuracy_train)\n",
    "print(\"accuracy for test data:\", accuracy_test)\n",
    "print(\"accuracy for original data:\", accuracy_original)\n",
    "print(\" \")\n",
    "print(\"precision for train data:\", precision_train)\n",
    "print(\"precision for test data:\", precision_test)\n",
    "print(\"precision for original data:\", precision_original)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(ncols=3, figsize=(15, 4))\n",
    "ax1, ax2, ax3 = axes\n",
    "\n",
    "conf_matrix_test = confusion_matrix(y_test, predictions_test)\n",
    "conf_matrix_train = confusion_matrix(y_train, predictions_train)\n",
    "conf_matrix_original = confusion_matrix(y, predictions_original)\n",
    "\n",
    "s1 = sns.heatmap(conf_matrix_train, annot=True, cmap=\"YlGnBu\", fmt=\"d\", xticklabels=np.arange(6) + 3, yticklabels=np.arange(6) + 3, ax=ax1)\n",
    "s2 = sns.heatmap(conf_matrix_test, annot=True, cmap=\"YlGnBu\", fmt=\"d\", xticklabels=np.arange(6) + 3, yticklabels=np.arange(6) + 3, ax=ax2)\n",
    "s3 = sns.heatmap(conf_matrix_original, annot=True, cmap=\"YlGnBu\", fmt=\"d\", xticklabels=np.arange(6) + 3, yticklabels=np.arange(6) + 3, ax=ax3)\n",
    "\n",
    "s1.set(xlabel='Predicted', ylabel='True', title=\"Train data\")\n",
    "s2.set(xlabel='Predicted', ylabel='True', title=\"Test data\")\n",
    "s3.set(xlabel='Predicted', ylabel='True', title=\"Original data\")\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='importance', ylabel='feature'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "importance_df = pd.DataFrame({\"feature\": wine_df.iloc[:,:-1].columns, \"importance\": forest.feature_importances_}).sort_values(by=\"importance\", ascending=False)\n",
    "sns.barplot(data=importance_df, y=\"feature\", x=\"importance\")"
   ]
  }
 ],
 "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}