hotel_guest_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "22bbbb68",
   "metadata": {},
   "source": [
    "## Predicting Hotel Guest Cancellation\n",
    "### Sakher Alqa. - UGA.EDU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "273a7f3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn import preprocessing\n",
    "import numpy as np\n",
    "from sklearn.impute import KNNImputer\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn import svm\n",
    "from sklearn.pipeline import Pipeline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fb9627e8",
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_week_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "      <th>reservation_status_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>342</td>\n",
       "      <td>2015</td>\n",
       "      <td>July</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2015-07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>737</td>\n",
       "      <td>2015</td>\n",
       "      <td>July</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2015-07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2015</td>\n",
       "      <td>July</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>75.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2015-07-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2015</td>\n",
       "      <td>July</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>304.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>75.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2015-07-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2015</td>\n",
       "      <td>July</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>98.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2015-07-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119385</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>2017</td>\n",
       "      <td>August</td>\n",
       "      <td>35</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>394.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>96.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2017-09-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119386</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>102</td>\n",
       "      <td>2017</td>\n",
       "      <td>August</td>\n",
       "      <td>35</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>225.43</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2017-09-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119387</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>2017</td>\n",
       "      <td>August</td>\n",
       "      <td>35</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>157.71</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2017-09-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119388</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>109</td>\n",
       "      <td>2017</td>\n",
       "      <td>August</td>\n",
       "      <td>35</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>89.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>104.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2017-09-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119389</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>205</td>\n",
       "      <td>2017</td>\n",
       "      <td>August</td>\n",
       "      <td>35</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>151.20</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2017-09-07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119390 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
       "0       Resort Hotel            0        342               2015   \n",
       "1       Resort Hotel            0        737               2015   \n",
       "2       Resort Hotel            0          7               2015   \n",
       "3       Resort Hotel            0         13               2015   \n",
       "4       Resort Hotel            0         14               2015   \n",
       "...              ...          ...        ...                ...   \n",
       "119385    City Hotel            0         23               2017   \n",
       "119386    City Hotel            0        102               2017   \n",
       "119387    City Hotel            0         34               2017   \n",
       "119388    City Hotel            0        109               2017   \n",
       "119389    City Hotel            0        205               2017   \n",
       "\n",
       "       arrival_date_month  arrival_date_week_number  \\\n",
       "0                    July                        27   \n",
       "1                    July                        27   \n",
       "2                    July                        27   \n",
       "3                    July                        27   \n",
       "4                    July                        27   \n",
       "...                   ...                       ...   \n",
       "119385             August                        35   \n",
       "119386             August                        35   \n",
       "119387             August                        35   \n",
       "119388             August                        35   \n",
       "119389             August                        35   \n",
       "\n",
       "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
       "0                               1                        0   \n",
       "1                               1                        0   \n",
       "2                               1                        0   \n",
       "3                               1                        0   \n",
       "4                               1                        0   \n",
       "...                           ...                      ...   \n",
       "119385                         30                        2   \n",
       "119386                         31                        2   \n",
       "119387                         31                        2   \n",
       "119388                         31                        2   \n",
       "119389                         29                        2   \n",
       "\n",
       "        stays_in_week_nights  adults  ...  deposit_type  agent company  \\\n",
       "0                          0       2  ...    No Deposit    NaN     NaN   \n",
       "1                          0       2  ...    No Deposit    NaN     NaN   \n",
       "2                          1       1  ...    No Deposit    NaN     NaN   \n",
       "3                          1       1  ...    No Deposit  304.0     NaN   \n",
       "4                          2       2  ...    No Deposit  240.0     NaN   \n",
       "...                      ...     ...  ...           ...    ...     ...   \n",
       "119385                     5       2  ...    No Deposit  394.0     NaN   \n",
       "119386                     5       3  ...    No Deposit    9.0     NaN   \n",
       "119387                     5       2  ...    No Deposit    9.0     NaN   \n",
       "119388                     5       2  ...    No Deposit   89.0     NaN   \n",
       "119389                     7       2  ...    No Deposit    9.0     NaN   \n",
       "\n",
       "       days_in_waiting_list customer_type     adr  \\\n",
       "0                         0     Transient    0.00   \n",
       "1                         0     Transient    0.00   \n",
       "2                         0     Transient   75.00   \n",
       "3                         0     Transient   75.00   \n",
       "4                         0     Transient   98.00   \n",
       "...                     ...           ...     ...   \n",
       "119385                    0     Transient   96.14   \n",
       "119386                    0     Transient  225.43   \n",
       "119387                    0     Transient  157.71   \n",
       "119388                    0     Transient  104.40   \n",
       "119389                    0     Transient  151.20   \n",
       "\n",
       "        required_car_parking_spaces  total_of_special_requests  \\\n",
       "0                                 0                          0   \n",
       "1                                 0                          0   \n",
       "2                                 0                          0   \n",
       "3                                 0                          0   \n",
       "4                                 0                          1   \n",
       "...                             ...                        ...   \n",
       "119385                            0                          0   \n",
       "119386                            0                          2   \n",
       "119387                            0                          4   \n",
       "119388                            0                          0   \n",
       "119389                            0                          2   \n",
       "\n",
       "        reservation_status reservation_status_date  \n",
       "0                Check-Out              2015-07-01  \n",
       "1                Check-Out              2015-07-01  \n",
       "2                Check-Out              2015-07-02  \n",
       "3                Check-Out              2015-07-02  \n",
       "4                Check-Out              2015-07-03  \n",
       "...                    ...                     ...  \n",
       "119385           Check-Out              2017-09-06  \n",
       "119386           Check-Out              2017-09-07  \n",
       "119387           Check-Out              2017-09-07  \n",
       "119388           Check-Out              2017-09-07  \n",
       "119389           Check-Out              2017-09-07  \n",
       "\n",
       "[119390 rows x 32 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('hotel_bookings.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "72615d5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "feature: hotel\n",
      "hotel\n",
      "City Hotel      2569\n",
      "Resort Hotel    1038\n",
      "dtype: int64\n",
      "---\n",
      "feature: is_canceled\n",
      "is_canceled\n",
      "0    1200\n",
      "1    2407\n",
      "dtype: int64\n",
      "---\n",
      "feature: stays_in_weekend_nights\n",
      "stays_in_weekend_nights\n",
      "0     1589\n",
      "1      892\n",
      "2      964\n",
      "---\n",
      "feature: stays_in_week_nights\n",
      "stays_in_week_nights\n",
      "0     247\n",
      "1     984\n",
      "2     993\n",
      "---\n",
      "feature: adults\n",
      "adults\n",
      "0       13\n",
      "1      883\n",
      "2     2545\n",
      "---\n",
      "feature: children\n",
      "children\n",
      "0.0     3322\n",
      "1.0      152\n",
      "2.0      130\n",
      "---\n",
      "feature: babies\n",
      "babies\n",
      "0    3590\n",
      "1      17\n",
      "dtype: int64\n",
      "---\n",
      "feature: meal\n",
      "meal\n",
      "BB           2864\n",
      "FB             28\n",
      "HB            320\n",
      "---\n",
      "feature: country\n",
      "country\n",
      "AGO    72\n",
      "ALB     1\n",
      "ARE     2\n",
      "---\n",
      "feature: market_segment\n",
      "market_segment\n",
      "Aviation           18\n",
      "Complementary      26\n",
      "Corporate         170\n",
      "---\n",
      "feature: distribution_channel\n",
      "distribution_channel\n",
      "Corporate     219\n",
      "Direct        483\n",
      "GDS             5\n",
      "---\n",
      "feature: is_repeated_guest\n",
      "is_repeated_guest\n",
      "0    3493\n",
      "1     114\n",
      "dtype: int64\n",
      "---\n",
      "feature: previous_cancellations\n",
      "previous_cancellations\n",
      "0     3428\n",
      "1      169\n",
      "2        2\n",
      "---\n",
      "feature: previous_bookings_not_canceled\n",
      "previous_bookings_not_canceled\n",
      "0     3509\n",
      "1       42\n",
      "2       22\n",
      "---\n",
      "feature: reserved_room_type\n",
      "reserved_room_type\n",
      "A    2625\n",
      "B      40\n",
      "C      28\n",
      "---\n",
      "feature: assigned_room_type\n",
      "assigned_room_type\n",
      "A    2258\n",
      "B      82\n",
      "C      68\n",
      "---\n",
      "feature: booking_changes\n",
      "booking_changes\n",
      "0     3115\n",
      "1      327\n",
      "2      125\n",
      "---\n",
      "feature: deposit_type\n",
      "deposit_type\n",
      "No Deposit    3146\n",
      "Non Refund     457\n",
      "Refundable       4\n",
      "---\n",
      "feature: agent\n",
      "agent\n",
      "1.0      195\n",
      "2.0        1\n",
      "3.0       32\n",
      "---\n",
      "feature: company\n",
      "company\n",
      "9.0      1\n",
      "12.0     1\n",
      "14.0     1\n",
      "---\n",
      "feature: days_in_waiting_list\n",
      "days_in_waiting_list\n",
      "0      3512\n",
      "2         1\n",
      "3         3\n",
      "---\n",
      "feature: customer_type\n",
      "customer_type\n",
      "Contract            114\n",
      "Group                15\n",
      "Transient          2778\n",
      "---\n",
      "feature: required_car_parking_spaces\n",
      "required_car_parking_spaces\n",
      "0    3485\n",
      "1     120\n",
      "2       2\n",
      "---\n",
      "feature: total_of_special_requests\n",
      "total_of_special_requests\n",
      "0    2222\n",
      "1     938\n",
      "2     361\n",
      "---\n"
     ]
    }
   ],
   "source": [
    "#more clarifications on values\n",
    "for col in df.columns:\n",
    "    print(f'feature: {col}')\n",
    "    df_g = df.groupby(col)\n",
    "    s = str(df_g.size()).split('\\n')\n",
    "    #printing first 5 lines\n",
    "    for x in range(0,4):\n",
    "        print(s[x])\n",
    "    print('---')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "68847c6b",
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_week_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>children</th>\n",
       "      <th>babies</th>\n",
       "      <th>meal</th>\n",
       "      <th>country</th>\n",
       "      <th>market_segment</th>\n",
       "      <th>...</th>\n",
       "      <th>assigned_room_type</th>\n",
       "      <th>booking_changes</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>PRT</td>\n",
       "      <td>Direct</td>\n",
       "      <td>...</td>\n",
       "      <td>C</td>\n",
       "      <td>3</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>PRT</td>\n",
       "      <td>Direct</td>\n",
       "      <td>...</td>\n",
       "      <td>C</td>\n",
       "      <td>4</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>GBR</td>\n",
       "      <td>Direct</td>\n",
       "      <td>...</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>GBR</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>...</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>304.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>GBR</td>\n",
       "      <td>Online TA</td>\n",
       "      <td>...</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119385</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>BEL</td>\n",
       "      <td>Offline TA/TO</td>\n",
       "      <td>...</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>394.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119386</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>FRA</td>\n",
       "      <td>Online TA</td>\n",
       "      <td>...</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119387</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>DEU</td>\n",
       "      <td>Online TA</td>\n",
       "      <td>...</td>\n",
       "      <td>D</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119388</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>BB</td>\n",
       "      <td>GBR</td>\n",
       "      <td>Online TA</td>\n",
       "      <td>...</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>89.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119389</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>HB</td>\n",
       "      <td>DEU</td>\n",
       "      <td>Online TA</td>\n",
       "      <td>...</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Transient</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119390 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               hotel  is_canceled  stays_in_weekend_nights  \\\n",
       "0       Resort Hotel            0                        0   \n",
       "1       Resort Hotel            0                        0   \n",
       "2       Resort Hotel            0                        0   \n",
       "3       Resort Hotel            0                        0   \n",
       "4       Resort Hotel            0                        0   \n",
       "...              ...          ...                      ...   \n",
       "119385    City Hotel            0                        2   \n",
       "119386    City Hotel            0                        2   \n",
       "119387    City Hotel            0                        2   \n",
       "119388    City Hotel            0                        2   \n",
       "119389    City Hotel            0                        2   \n",
       "\n",
       "        stays_in_week_nights  adults  children  babies meal country  \\\n",
       "0                          0       2       0.0       0   BB     PRT   \n",
       "1                          0       2       0.0       0   BB     PRT   \n",
       "2                          1       1       0.0       0   BB     GBR   \n",
       "3                          1       1       0.0       0   BB     GBR   \n",
       "4                          2       2       0.0       0   BB     GBR   \n",
       "...                      ...     ...       ...     ...  ...     ...   \n",
       "119385                     5       2       0.0       0   BB     BEL   \n",
       "119386                     5       3       0.0       0   BB     FRA   \n",
       "119387                     5       2       0.0       0   BB     DEU   \n",
       "119388                     5       2       0.0       0   BB     GBR   \n",
       "119389                     7       2       0.0       0   HB     DEU   \n",
       "\n",
       "       market_segment  ... assigned_room_type  booking_changes  deposit_type  \\\n",
       "0              Direct  ...                  C                3    No Deposit   \n",
       "1              Direct  ...                  C                4    No Deposit   \n",
       "2              Direct  ...                  C                0    No Deposit   \n",
       "3           Corporate  ...                  A                0    No Deposit   \n",
       "4           Online TA  ...                  A                0    No Deposit   \n",
       "...               ...  ...                ...              ...           ...   \n",
       "119385  Offline TA/TO  ...                  A                0    No Deposit   \n",
       "119386      Online TA  ...                  E                0    No Deposit   \n",
       "119387      Online TA  ...                  D                0    No Deposit   \n",
       "119388      Online TA  ...                  A                0    No Deposit   \n",
       "119389      Online TA  ...                  A                0    No Deposit   \n",
       "\n",
       "        agent company days_in_waiting_list  customer_type  \\\n",
       "0         NaN     NaN                    0      Transient   \n",
       "1         NaN     NaN                    0      Transient   \n",
       "2         NaN     NaN                    0      Transient   \n",
       "3       304.0     NaN                    0      Transient   \n",
       "4       240.0     NaN                    0      Transient   \n",
       "...       ...     ...                  ...            ...   \n",
       "119385  394.0     NaN                    0      Transient   \n",
       "119386    9.0     NaN                    0      Transient   \n",
       "119387    9.0     NaN                    0      Transient   \n",
       "119388   89.0     NaN                    0      Transient   \n",
       "119389    9.0     NaN                    0      Transient   \n",
       "\n",
       "       required_car_parking_spaces  total_of_special_requests  \\\n",
       "0                                0                          0   \n",
       "1                                0                          0   \n",
       "2                                0                          0   \n",
       "3                                0                          0   \n",
       "4                                0                          1   \n",
       "...                            ...                        ...   \n",
       "119385                           0                          0   \n",
       "119386                           0                          2   \n",
       "119387                           0                          4   \n",
       "119388                           0                          0   \n",
       "119389                           0                          2   \n",
       "\n",
       "        reservation_status  \n",
       "0                Check-Out  \n",
       "1                Check-Out  \n",
       "2                Check-Out  \n",
       "3                Check-Out  \n",
       "4                Check-Out  \n",
       "...                    ...  \n",
       "119385           Check-Out  \n",
       "119386           Check-Out  \n",
       "119387           Check-Out  \n",
       "119388           Check-Out  \n",
       "119389           Check-Out  \n",
       "\n",
       "[119390 rows x 25 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping unnecessary features\n",
    "df = df.drop(columns=[\n",
    "'lead_time',\n",
    "'arrival_date_year',\n",
    "'arrival_date_month',\n",
    "'arrival_date_week_number',\n",
    "'arrival_date_day_of_month',\n",
    "'adr',\n",
    "'reservation_status_date',\n",
    "])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c5b5b6c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5546/3569085873.py:10: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append(Canceled_df)\n",
      "/tmp/ipykernel_5546/3569085873.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append(Check_Out_df)\n"
     ]
    }
   ],
   "source": [
    "#y is imbalanced, class is reservation_status\n",
    "#Canceled     43017, Check-Out    75166, No-Show       1207\n",
    "#undersampling\n",
    "Canceled_df = df[ df['reservation_status'] == 'Canceled' ]\n",
    "Canceled_df = Canceled_df.sample(n = 1200)\n",
    "Check_Out_df = df[ df['reservation_status'] == 'Check-Out' ]\n",
    "Check_Out_df = Check_Out_df.sample(n = 1200)\n",
    "df = df.drop( df[ df['reservation_status'] == 'Canceled' ].index )\n",
    "df = df.drop( df[ df['reservation_status'] == 'Check-Out'].index )\n",
    "df = df.append(Canceled_df)\n",
    "df = df.append(Check_Out_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "46325c4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reservation_status\n",
      "Canceled     1200\n",
      "Check-Out    1200\n",
      "No-Show      1207\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#y is imbalanced, class is reservation_status\n",
    "#Canceled     43017, Check-Out    75166, No-Show       1207\n",
    "#copy No-Show 3 times , Oversampling\n",
    "#df = df.append([ df[ df['reservation_status'] == 'No-Show' ] ] * 40 )\n",
    "df_g = df.groupby('reservation_status')\n",
    "print(df_g.size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "392402cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='reservation_status'>"
      ]
     },
     "execution_count": 11,
     "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": [
    "df_g.size().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eabda5a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#extract y\n",
    "y = df['reservation_status']\n",
    "df = df.drop(columns=['reservation_status'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3c02cc74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 2, 2, ..., 1, 1, 1])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#encoding categorical features\n",
    "enc = preprocessing.OrdinalEncoder()\n",
    "X = enc.fit_transform(df,y)\n",
    "enc = preprocessing.LabelEncoder()\n",
    "y = enc.fit_transform(y)\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0a856867",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Impute\n",
    "imputer = KNNImputer()\n",
    "#imputer = SimpleImputer()\n",
    "X = imputer.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0bc9fdea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00742291, 0.00742291, 0.        , ..., 0.01484582, 0.        ,\n",
       "        0.        ],\n",
       "       [0.01212664, 0.01212664, 0.04850655, ..., 0.        , 0.        ,\n",
       "        0.01212664],\n",
       "       [0.00724854, 0.00724854, 0.01449708, ..., 0.01449708, 0.        ,\n",
       "        0.        ],\n",
       "       ...,\n",
       "       [0.        , 0.        , 0.05739076, ..., 0.05739076, 0.02869538,\n",
       "        0.05739076],\n",
       "       [0.        , 0.        , 0.        , ..., 0.05127643, 0.        ,\n",
       "        0.        ],\n",
       "       [0.02020305, 0.        , 0.02020305, ..., 0.06060915, 0.        ,\n",
       "        0.        ]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#normalize\n",
    "X = preprocessing.normalize(X)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3988ae95",
   "metadata": {},
   "outputs": [],
   "source": [
    "#extracting testing dataset\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0b1a2414",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 10 folds for each of 1 candidates, totalling 10 fits\n",
      "[CV 1/10] END .......................svm__C=1.0;, score=0.550 total time=   0.2s\n",
      "[CV 2/10] END .......................svm__C=1.0;, score=0.554 total time=   0.2s\n",
      "[CV 3/10] END .......................svm__C=1.0;, score=0.506 total time=   0.2s\n",
      "[CV 4/10] END .......................svm__C=1.0;, score=0.524 total time=   0.2s\n",
      "[CV 5/10] END .......................svm__C=1.0;, score=0.579 total time=   0.2s\n",
      "[CV 6/10] END .......................svm__C=1.0;, score=0.515 total time=   0.2s\n",
      "[CV 7/10] END .......................svm__C=1.0;, score=0.500 total time=   0.2s\n",
      "[CV 8/10] END .......................svm__C=1.0;, score=0.507 total time=   0.2s\n",
      "[CV 9/10] END .......................svm__C=1.0;, score=0.507 total time=   0.2s\n",
      "[CV 10/10] END ......................svm__C=1.0;, score=0.515 total time=   0.2s\n"
     ]
    }
   ],
   "source": [
    "#training\n",
    "pipe = Pipeline(\n",
    "    steps=[(\"svm\", svm.SVC())]\n",
    ")\n",
    "param_grid = {\n",
    "    \"svm__C\": [1.0],\n",
    "}\n",
    "search = GridSearchCV(pipe, param_grid, cv=10, verbose=3)\n",
    "fit = search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "18b13c95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5011086474501109"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit.score(X_test,y_test)"
   ]
  }
 ],
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