Untitled.ipynb

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     "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",
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       "    }\n",
       "\n",
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       "        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>Unnamed: 0</th>\n",
       "      <th>id</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Customer Type</th>\n",
       "      <th>Age</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Class</th>\n",
       "      <th>Flight Distance</th>\n",
       "      <th>Inflight wifi service</th>\n",
       "      <th>Departure/Arrival time convenient</th>\n",
       "      <th>...</th>\n",
       "      <th>Inflight entertainment</th>\n",
       "      <th>On-board service</th>\n",
       "      <th>Leg room service</th>\n",
       "      <th>Baggage handling</th>\n",
       "      <th>Checkin service</th>\n",
       "      <th>Inflight service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>Departure Delay in Minutes</th>\n",
       "      <th>Arrival Delay in Minutes</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>70172</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>13</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Eco Plus</td>\n",
       "      <td>460</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>18.0</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>5047</td>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>235</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>110028</td>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>26</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1142</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>24026</td>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>562</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>9.0</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>119299</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>61</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>214</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0      id  Gender      Customer Type  Age   Type of Travel  \\\n",
       "0           0   70172    Male     Loyal Customer   13  Personal Travel   \n",
       "1           1    5047    Male  disloyal Customer   25  Business travel   \n",
       "2           2  110028  Female     Loyal Customer   26  Business travel   \n",
       "3           3   24026  Female     Loyal Customer   25  Business travel   \n",
       "4           4  119299    Male     Loyal Customer   61  Business travel   \n",
       "\n",
       "      Class  Flight Distance  Inflight wifi service  \\\n",
       "0  Eco Plus              460                      3   \n",
       "1  Business              235                      3   \n",
       "2  Business             1142                      2   \n",
       "3  Business              562                      2   \n",
       "4  Business              214                      3   \n",
       "\n",
       "   Departure/Arrival time convenient  ...  Inflight entertainment  \\\n",
       "0                                  4  ...                       5   \n",
       "1                                  2  ...                       1   \n",
       "2                                  2  ...                       5   \n",
       "3                                  5  ...                       2   \n",
       "4                                  3  ...                       3   \n",
       "\n",
       "   On-board service  Leg room service  Baggage handling  Checkin service  \\\n",
       "0                 4                 3                 4                4   \n",
       "1                 1                 5                 3                1   \n",
       "2                 4                 3                 4                4   \n",
       "3                 2                 5                 3                1   \n",
       "4                 3                 4                 4                3   \n",
       "\n",
       "   Inflight service  Cleanliness  Departure Delay in Minutes  \\\n",
       "0                 5            5                          25   \n",
       "1                 4            1                           1   \n",
       "2                 4            5                           0   \n",
       "3                 4            2                          11   \n",
       "4                 3            3                           0   \n",
       "\n",
       "   Arrival Delay in Minutes             satisfaction  \n",
       "0                      18.0  neutral or dissatisfied  \n",
       "1                       6.0  neutral or dissatisfied  \n",
       "2                       0.0                satisfied  \n",
       "3                       9.0  neutral or dissatisfied  \n",
       "4                       0.0                satisfied  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data = pd.read_csv('train.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "b4ac4255",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Customer Type</th>\n",
       "      <th>Age</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Class</th>\n",
       "      <th>Flight Distance</th>\n",
       "      <th>Inflight wifi service</th>\n",
       "      <th>Departure/Arrival time convenient</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Gate location</th>\n",
       "      <th>...</th>\n",
       "      <th>Inflight entertainment</th>\n",
       "      <th>On-board service</th>\n",
       "      <th>Leg room service</th>\n",
       "      <th>Baggage handling</th>\n",
       "      <th>Checkin service</th>\n",
       "      <th>Inflight service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>Departure Delay in Minutes</th>\n",
       "      <th>Arrival Delay in Minutes</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
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       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>214</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Customer Type  Age  Type of Travel  Class  Flight Distance  \\\n",
       "0       1              0   13               1      2              460   \n",
       "1       1              1   25               0      0              235   \n",
       "2       0              0   26               0      0             1142   \n",
       "3       0              0   25               0      0              562   \n",
       "4       1              0   61               0      0              214   \n",
       "\n",
       "   Inflight wifi service  Departure/Arrival time convenient  \\\n",
       "0                      3                                  4   \n",
       "1                      3                                  2   \n",
       "2                      2                                  2   \n",
       "3                      2                                  5   \n",
       "4                      3                                  3   \n",
       "\n",
       "   Ease of Online booking  Gate location  ...  Inflight entertainment  \\\n",
       "0                       3              1  ...                       5   \n",
       "1                       3              3  ...                       1   \n",
       "2                       2              2  ...                       5   \n",
       "3                       5              5  ...                       2   \n",
       "4                       3              3  ...                       3   \n",
       "\n",
       "   On-board service  Leg room service  Baggage handling  Checkin service  \\\n",
       "0                 4                 3                 4                4   \n",
       "1                 1                 5                 3                1   \n",
       "2                 4                 3                 4                4   \n",
       "3                 2                 5                 3                1   \n",
       "4                 3                 4                 4                3   \n",
       "\n",
       "   Inflight service  Cleanliness  Departure Delay in Minutes  \\\n",
       "0                 5            5                          25   \n",
       "1                 4            1                           1   \n",
       "2                 4            5                           0   \n",
       "3                 4            2                          11   \n",
       "4                 3            3                           0   \n",
       "\n",
       "   Arrival Delay in Minutes  satisfaction  \n",
       "0                      18.0             0  \n",
       "1                       6.0             0  \n",
       "2                       0.0             1  \n",
       "3                       9.0             0  \n",
       "4                       0.0             1  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = data.drop(['Unnamed: 0', 'id'], axis=1).dropna()\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "for column in ['Gender', 'Customer Type', 'Type of Travel', 'Class', 'satisfaction']:\n",
    "    encoder = LabelEncoder()\n",
    "    data[column] = encoder.fit_transform(data[column])\n",
    "\n",
    "x = data.drop('satisfaction', axis=1)\n",
    "y = data['satisfaction']    \n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "797b589d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Perceptron()"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import Perceptron\n",
    "trainPer = Perceptron(random_state=0)\n",
    "trainPer.fit(x.values, y.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "a6f1c412",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataTest = pd.read_csv('test.csv')\n",
    "dataTest.head()\n",
    "\n",
    "dataTest = dataTest.drop(['Unnamed: 0', 'id'], axis=1).dropna()\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "for column in ['Gender', 'Customer Type', 'Type of Travel', 'Class', 'satisfaction']:\n",
    "    encoder = LabelEncoder()\n",
    "    dataTest[column] = encoder.fit_transform(dataTest[column])\n",
    "\n",
    "x2 = dataTest.drop('satisfaction', axis=1)\n",
    "y2 = dataTest['satisfaction']    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "8ef4b1ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8280616382806164"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from sklearn.metrics import accuracy_score\n",
    "accuracy_score(y2.values, trainPer.predict(x2.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "9bfdde57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6602942880315144"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.kernel_approximation import RBFSampler\n",
    "from sklearn.linear_model import SGDClassifier\n",
    "\n",
    "rbf_feature = RBFSampler(gamma=0.0001, random_state=0)\n",
    "X_features = rbf_feature.fit_transform(dataTest)\n",
    "\n",
    "clf = SGDClassifier(max_iter=2000)\n",
    "clf.fit(X_features,  y2.values)\n",
    "clf.score(X_features, y2.values)\n"
   ]
  }
 ],
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