docs/sample-scripts/HR-Attrition-Model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Complete flow to generate a ML model for the HR Attrition dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Prepare the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import a custom transformer for preprocessing data based on feature definitions\n",
    "from preprocessor import Preprocessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample</th>\n",
       "      <th>variable_type</th>\n",
       "      <th>data_type</th>\n",
       "      <th>feature_strategy</th>\n",
       "      <th>hash_features</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</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>Age</th>\n",
       "      <td>41</td>\n",
       "      <td>feature</td>\n",
       "      <td>int</td>\n",
       "      <td>scaling</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Attrition</th>\n",
       "      <td>Yes</td>\n",
       "      <td>target</td>\n",
       "      <td>str</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BusinessTravel</th>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>feature</td>\n",
       "      <td>str</td>\n",
       "      <td>one hot encoding</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DailyRate</th>\n",
       "      <td>1102</td>\n",
       "      <td>feature</td>\n",
       "      <td>int</td>\n",
       "      <td>scaling</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department</th>\n",
       "      <td>Sales</td>\n",
       "      <td>feature</td>\n",
       "      <td>str</td>\n",
       "      <td>one hot encoding</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       sample variable_type data_type  feature_strategy  \\\n",
       "name                                                                      \n",
       "Age                        41       feature       int           scaling   \n",
       "Attrition                 Yes        target       str              none   \n",
       "BusinessTravel  Travel_Rarely       feature       str  one hot encoding   \n",
       "DailyRate                1102       feature       int           scaling   \n",
       "Department              Sales       feature       str  one hot encoding   \n",
       "\n",
       "                hash_features  \n",
       "name                           \n",
       "Age                       NaN  \n",
       "Attrition                 NaN  \n",
       "BusinessTravel            NaN  \n",
       "DailyRate                 NaN  \n",
       "Department                NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Import feature definitions and data\n",
    "sheets = pd.read_excel('Data/HR-Employee-Attrition.xlsx', sheet_name=[\"Feature Definitions\", \"Train-Test\"])\n",
    "\n",
    "# Create feature definitions data frame\n",
    "features = sheets[\"Feature Definitions\"]\n",
    "features.columns = [c.lower() for c in features.columns]\n",
    "features.set_index(\"name\", append=False, inplace=True)\n",
    "features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yes</td>\n",
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       "      <th>1</th>\n",
       "      <td>No</td>\n",
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       "      <th>2</th>\n",
       "      <td>No</td>\n",
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       "      <td>No</td>\n",
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       "      <th>4</th>\n",
       "      <td>No</td>\n",
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      ],
      "text/plain": [
       "  Attrition\n",
       "0       Yes\n",
       "1        No\n",
       "2        No\n",
       "3        No\n",
       "4        No"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setup the data dataframe\n",
    "data = sheets[\"Train-Test\"]\n",
    "\n",
    "# Get the target features\n",
    "target = features.loc[features[\"variable_type\"] == \"target\"]\n",
    "target_name = target.index[0]\n",
    "\n",
    "# Get the target data\n",
    "d_target = data.loc[:,[target_name]]\n",
    "\n",
    "d_target.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the features to be excluded from the model\n",
    "exclusions = features['variable_type'].isin([\"excluded\", \"target\", \"identifier\"])\n",
    "\n",
    "excluded = features.loc[exclusions]\n",
    "features = features.loc[~exclusions]\n",
    "\n",
    "# Remove excluded features from the data\n",
    "data = data[features.index.tolist()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the data into training and testing subsets\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(data, d_target, test_size=0.30, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>YearsAtCompany</th>\n",
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       "      <th>YearsWithCurrManager</th>\n",
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       "      <th>893</th>\n",
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       "      <td>Life Sciences</td>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>75</td>\n",
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       "      <td>3</td>\n",
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       "      <td>27</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>829</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>3</td>\n",
       "      <td>Male</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
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       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>35</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>138</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>2</td>\n",
       "      <td>Female</td>\n",
       "      <td>37</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
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       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
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       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>45</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>193</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>Other</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>52</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age     BusinessTravel  DailyRate              Department  \\\n",
       "893   41  Travel_Frequently       1200  Research & Development   \n",
       "115   50  Travel_Frequently        809                   Sales   \n",
       "526   27  Travel_Frequently        829                   Sales   \n",
       "175   35  Travel_Frequently        138  Research & Development   \n",
       "63    45      Travel_Rarely        193  Research & Development   \n",
       "\n",
       "     DistanceFromHome  Education EducationField  EnvironmentSatisfaction  \\\n",
       "893                22          3  Life Sciences                        4   \n",
       "115                12          3      Marketing                        3   \n",
       "526                 8          1      Marketing                        3   \n",
       "175                 2          3        Medical                        2   \n",
       "63                  6          4          Other                        4   \n",
       "\n",
       "     Gender  HourlyRate  ...  PerformanceRating  RelationshipSatisfaction  \\\n",
       "893  Female          75  ...                  3                         1   \n",
       "115  Female          77  ...                  3                         4   \n",
       "526    Male          84  ...                  3                         2   \n",
       "175  Female          37  ...                  3                         4   \n",
       "63     Male          52  ...                  3                         2   \n",
       "\n",
       "    StockOptionLevel  TotalWorkingYears TrainingTimesLastYear  \\\n",
       "893                2                 12                     4   \n",
       "115                0                 16                     3   \n",
       "526                1                  5                     3   \n",
       "175                0                 10                     5   \n",
       "63                 0                 17                     3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "893                2               6                   2   \n",
       "115                3               2                   2   \n",
       "526                3               4                   2   \n",
       "175                3               6                   2   \n",
       "63                 4               0                   0   \n",
       "\n",
       "    YearsSinceLastPromotion YearsWithCurrManager  \n",
       "893                       3                    3  \n",
       "115                       2                    1  \n",
       "526                       1                    1  \n",
       "175                       1                    2  \n",
       "63                        0                    0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.head()"
   ]
  },
  {
   "cell_type": "code",
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       "      <th>63</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.717995</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-1.131942</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>0.512184</td>\n",
       "      <td>0.799463</td>\n",
       "      <td>0.058274</td>\n",
       "      <td>0.899445</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>381</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.311464</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.969763</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>2.018796</td>\n",
       "      <td>1.633413</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>0.030790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.210630</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>0.003310</td>\n",
       "      <td>0.790241</td>\n",
       "      <td>-0.375111</td>\n",
       "      <td>0.780896</td>\n",
       "      <td>1.265490</td>\n",
       "      <td>-0.034487</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>0.899445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.184623</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.807584</td>\n",
       "      <td>-0.613794</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-0.605477</td>\n",
       "      <td>-0.241123</td>\n",
       "      <td>1.216438</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-0.837864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.311464</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.969763</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>-0.994429</td>\n",
       "      <td>-0.451462</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-1.706519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.677258</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.483227</td>\n",
       "      <td>-0.332987</td>\n",
       "      <td>-0.375111</td>\n",
       "      <td>-0.605477</td>\n",
       "      <td>-0.241123</td>\n",
       "      <td>1.216438</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-0.837864</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>399 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      BusinessTravel_Non-Travel  BusinessTravel_Travel_Frequently  \\\n",
       "893                           0                                 1   \n",
       "115                           0                                 1   \n",
       "526                           0                                 1   \n",
       "175                           0                                 1   \n",
       "63                            0                                 0   \n",
       "...                         ...                               ...   \n",
       "381                           0                                 0   \n",
       "292                           0                                 0   \n",
       "1083                          0                                 0   \n",
       "551                           0                                 0   \n",
       "141                           0                                 1   \n",
       "\n",
       "      BusinessTravel_Travel_Rarely  Department_Human Resources  \\\n",
       "893                              0                           0   \n",
       "115                              0                           0   \n",
       "526                              0                           0   \n",
       "175                              0                           0   \n",
       "63                               1                           0   \n",
       "...                            ...                         ...   \n",
       "381                              1                           1   \n",
       "292                              1                           0   \n",
       "1083                             1                           0   \n",
       "551                              1                           0   \n",
       "141                              0                           0   \n",
       "\n",
       "      Department_Research & Development  Department_Sales  Education_1  \\\n",
       "893                                   1                 0            0   \n",
       "115                                   0                 1            0   \n",
       "526                                   0                 1            1   \n",
       "175                                   1                 0            0   \n",
       "63                                    1                 0            0   \n",
       "...                                 ...               ...          ...   \n",
       "381                                   0                 0            0   \n",
       "292                                   0                 1            0   \n",
       "1083                                  0                 1            1   \n",
       "551                                   1                 0            0   \n",
       "141                                   0                 1            0   \n",
       "\n",
       "      Education_2  Education_3  Education_4  ...  TotalWorkingYears  \\\n",
       "893             0            1            0  ...           0.083789   \n",
       "115             0            1            0  ...           0.591154   \n",
       "526             0            0            0  ...          -0.804100   \n",
       "175             0            1            0  ...          -0.169894   \n",
       "63              0            0            1  ...           0.717995   \n",
       "...           ...          ...          ...  ...                ...   \n",
       "381             1            0            0  ...          -1.311464   \n",
       "292             0            1            0  ...           0.210630   \n",
       "1083            0            0            0  ...          -1.184623   \n",
       "551             0            1            0  ...          -1.311464   \n",
       "141             0            0            1  ...          -0.677258   \n",
       "\n",
       "      TrainingTimesLastYear  YearsAtCompany  YearsInCurrentRole  \\\n",
       "893                0.927695       -0.158869           -0.613794   \n",
       "115                0.153090       -0.807584           -0.613794   \n",
       "526                0.153090       -0.483227           -0.613794   \n",
       "175                1.702300       -0.158869           -0.613794   \n",
       "63                 0.153090       -1.131942           -1.175408   \n",
       "...                     ...             ...                 ...   \n",
       "381                0.153090       -0.969763           -1.175408   \n",
       "292                0.153090        0.003310            0.790241   \n",
       "1083               0.153090       -0.807584           -0.613794   \n",
       "551                0.153090       -0.969763           -1.175408   \n",
       "141                0.153090       -0.483227           -0.332987   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  JobRole0  JobRole1  \\\n",
       "893                  0.232242             -0.328203 -0.994429 -0.451462   \n",
       "115                 -0.071434             -0.882752  1.265490 -0.034487   \n",
       "526                 -0.375111             -0.882752  1.265490 -0.034487   \n",
       "175                 -0.375111             -0.605477 -0.994429 -1.702387   \n",
       "63                  -0.678787             -1.160026  0.512184  0.799463   \n",
       "...                       ...                   ...       ...       ...   \n",
       "381                 -0.678787             -1.160026  2.018796  1.633413   \n",
       "292                 -0.375111              0.780896  1.265490 -0.034487   \n",
       "1083                -0.678787             -0.605477 -0.241123  1.216438   \n",
       "551                 -0.678787             -1.160026 -0.994429 -0.451462   \n",
       "141                 -0.375111             -0.605477 -0.241123  1.216438   \n",
       "\n",
       "      JobRole2  JobRole3  \n",
       "893  -0.816773 -1.706519  \n",
       "115  -0.816773  0.899445  \n",
       "526  -0.816773  0.899445  \n",
       "175   1.808367  0.899445  \n",
       "63    0.058274  0.899445  \n",
       "...        ...       ...  \n",
       "381  -0.816773  0.030790  \n",
       "292  -0.816773  0.899445  \n",
       "1083 -0.816773 -0.837864  \n",
       "551  -0.816773 -1.706519  \n",
       "141  -0.816773 -0.837864  \n",
       "\n",
       "[399 rows x 74 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test the preprocessor\n",
    "prep = Preprocessor(features, return_type='df').fit(X_train)\n",
    "prep.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set up machine learning pipelines, fit and score the models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic Regression pipeline test accuracy: 0.905\n",
      "Random Forest pipeline test accuracy: 0.862\n",
      "Classifier with best accuracy: Logistic Regression\n",
      "Saved Logistic Regression pipeline to file\n"
     ]
    }
   ],
   "source": [
    "# Set up a pipeline to run the ML flow\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import pickle\n",
    "\n",
    "# Construct the pipelines\n",
    "pipe_lr = Pipeline([('prep', Preprocessor(features, return_type='df')), ('clf', LogisticRegression(solver='lbfgs', random_state=42))])\n",
    "pipe_rf = Pipeline([('prep', Preprocessor(features, return_type='df')), ('clf', RandomForestClassifier(n_estimators=10, random_state=42))])\n",
    "\n",
    "# List of pipelines for ease of iteration\n",
    "pipelines = [pipe_lr, pipe_rf]\n",
    "\n",
    "# Dictionary of pipelines and classifier types for ease of reference\n",
    "pipe_dict = {0: 'Logistic Regression', 1: 'Random Forest'}\n",
    "\n",
    "# Fit the pipelines\n",
    "for pipe in pipelines:\n",
    "    pipe.fit(X_train, y_train.values.ravel())\n",
    "\n",
    "# Compare accuracies\n",
    "for idx, val in enumerate(pipelines):\n",
    "    print('%s pipeline test accuracy: %.3f' % (pipe_dict[idx], val.score(X_test, y_test)))\n",
    "\n",
    "# Identify the most accurate model on test data\n",
    "best_acc = 0.0\n",
    "best_clf = 0\n",
    "best_pipe = ''\n",
    "for idx, val in enumerate(pipelines):\n",
    "    if val.score(X_test, y_test) > best_acc:\n",
    "        best_acc = val.score(X_test, y_test.values.ravel())\n",
    "        best_pipe = val\n",
    "        best_clf = idx\n",
    "print('Classifier with best accuracy: %s' % pipe_dict[best_clf])\n",
    "\n",
    "# Save pipeline to file\n",
    "with open('HR-Attrition-v1.pkl', 'wb') as file:\n",
    "    pickle.dump(best_pipe, file)\n",
    "    print('Saved %s pipeline to file' % pipe_dict[best_clf])\n",
    "\n",
    "# Also save the preprocessor and model as separate files\n",
    "with open('HR-Attrition-v1-prep.pkl', 'wb') as file:\n",
    "    pickle.dump(best_pipe.named_steps['prep'], file)\n",
    "with open('HR-Attrition-v1-clf.pkl', 'wb') as file:\n",
    "    pickle.dump(best_pipe.named_steps['clf'], file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Validate the saved model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(memory=None,\n",
       "         steps=[('prep',\n",
       "                 <preprocessor.Preprocessor object at 0x0000024689421940>),\n",
       "                ('clf',\n",
       "                 LogisticRegression(C=1.0, class_weight=None, dual=False,\n",
       "                                    fit_intercept=True, intercept_scaling=1,\n",
       "                                    l1_ratio=None, max_iter=100,\n",
       "                                    multi_class='warn', n_jobs=None,\n",
       "                                    penalty='l2', random_state=42,\n",
       "                                    solver='lbfgs', tol=0.0001, verbose=0,\n",
       "                                    warm_start=False))],\n",
       "         verbose=False)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the saved pipeline from disk\n",
    "with open('HR-Attrition-v1.pkl', 'rb') as file:\n",
    "    model = pickle.load(file)\n",
    "\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "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>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1373</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Other</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>27</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>591</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>1005</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1282</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>Other</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>43</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1273</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</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>135</th>\n",
       "      <td>34</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>704</td>\n",
       "      <td>Sales</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>2035</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>36</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1120</td>\n",
       "      <td>Sales</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>2045</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>29</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>468</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2054</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>39</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>722</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>2056</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>36</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>884</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2061</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "0     37       Yes      Travel_Rarely       1373  Research & Development   \n",
       "1     27        No      Travel_Rarely        591  Research & Development   \n",
       "2     32        No  Travel_Frequently       1005  Research & Development   \n",
       "3     53        No      Travel_Rarely       1282  Research & Development   \n",
       "4     43        No      Travel_Rarely       1273  Research & Development   \n",
       "..   ...       ...                ...        ...                     ...   \n",
       "135   34        No      Travel_Rarely        704                   Sales   \n",
       "136   36        No      Travel_Rarely       1120                   Sales   \n",
       "137   29        No      Travel_Rarely        468  Research & Development   \n",
       "138   39        No      Travel_Rarely        722                   Sales   \n",
       "139   36        No  Travel_Frequently        884  Research & Development   \n",
       "\n",
       "     DistanceFromHome  Education EducationField  EmployeeCount  \\\n",
       "0                   2          2          Other              1   \n",
       "1                   2          1        Medical              1   \n",
       "2                   2          2  Life Sciences              1   \n",
       "3                   5          3          Other              1   \n",
       "4                   2          2        Medical              1   \n",
       "..                ...        ...            ...            ...   \n",
       "135                28          3      Marketing              1   \n",
       "136                11          4      Marketing              1   \n",
       "137                28          4        Medical              1   \n",
       "138                24          1      Marketing              1   \n",
       "139                23          2        Medical              1   \n",
       "\n",
       "     EmployeeNumber  ...  RelationshipSatisfaction StandardHours  \\\n",
       "0                 4  ...                         2            80   \n",
       "1                 7  ...                         4            80   \n",
       "2                 8  ...                         3            80   \n",
       "3                32  ...                         4            80   \n",
       "4                46  ...                         4            80   \n",
       "..              ...  ...                       ...           ...   \n",
       "135            2035  ...                         4            80   \n",
       "136            2045  ...                         1            80   \n",
       "137            2054  ...                         2            80   \n",
       "138            2056  ...                         1            80   \n",
       "139            2061  ...                         3            80   \n",
       "\n",
       "     StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                   0                  7                      3   \n",
       "1                   1                  6                      3   \n",
       "2                   0                  8                      2   \n",
       "3                   1                 26                      3   \n",
       "4                   2                  6                      3   \n",
       "..                ...                ...                    ...   \n",
       "135                 2                  8                      2   \n",
       "136                 1                  8                      2   \n",
       "137                 0                  5                      3   \n",
       "138                 1                 21                      2   \n",
       "139                 1                 17                      3   \n",
       "\n",
       "    WorkLifeBalance  YearsAtCompany YearsInCurrentRole  \\\n",
       "0                 3               0                  0   \n",
       "1                 3               2                  2   \n",
       "2                 2               7                  7   \n",
       "3                 2              14                 13   \n",
       "4                 2               5                  3   \n",
       "..              ...             ...                ...   \n",
       "135               3               8                  7   \n",
       "136               2               6                  3   \n",
       "137               1               5                  4   \n",
       "138               2              20                  9   \n",
       "139               3               5                  2   \n",
       "\n",
       "     YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                          0                     0  \n",
       "1                          2                     2  \n",
       "2                          3                     6  \n",
       "3                          4                     8  \n",
       "4                          1                     4  \n",
       "..                       ...                   ...  \n",
       "135                        1                     7  \n",
       "136                        0                     0  \n",
       "137                        0                     4  \n",
       "138                        9                     6  \n",
       "139                        0                     3  \n",
       "\n",
       "[140 rows x 35 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load additional data to test the saved model\n",
    "validation = pd.read_excel('Data/HR-Employee-Attrition.xlsx', sheet_name=\"Validate\")\n",
    "validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yes</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>No</td>\n",
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       "      <th>2</th>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
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       "      <td>No</td>\n",
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       "      <th>4</th>\n",
       "      <td>No</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "  Attrition\n",
       "0       Yes\n",
       "1        No\n",
       "2        No\n",
       "3        No\n",
       "4        No"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the targets\n",
    "v_target = validation.loc[:,[target_name]]\n",
    "v_target.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>BusinessTravel</th>\n",
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       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>...</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37</td>\n",
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       "      <td>1373</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
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       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>27</td>\n",
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       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>40</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "      <td>3</td>\n",
       "      <td>3</td>\n",
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       "      <td>32</td>\n",
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       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
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       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1282</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>Other</td>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>43</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1273</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Medical</td>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
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       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
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       "      <td>4</td>\n",
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       "      <td>34</td>\n",
       "      <td>Travel_Rarely</td>\n",
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       "      <td>Sales</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>95</td>\n",
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       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
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       "      <td>36</td>\n",
       "      <td>Travel_Rarely</td>\n",
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       "      <td>Sales</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>2</td>\n",
       "      <td>Female</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>29</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>468</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>Medical</td>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
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       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
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       "      <td>39</td>\n",
       "      <td>Travel_Rarely</td>\n",
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       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>2</td>\n",
       "      <td>Female</td>\n",
       "      <td>60</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>36</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>884</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>Medical</td>\n",
       "      <td>3</td>\n",
       "      <td>Male</td>\n",
       "      <td>41</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age     BusinessTravel  DailyRate              Department  \\\n",
       "0     37      Travel_Rarely       1373  Research & Development   \n",
       "1     27      Travel_Rarely        591  Research & Development   \n",
       "2     32  Travel_Frequently       1005  Research & Development   \n",
       "3     53      Travel_Rarely       1282  Research & Development   \n",
       "4     43      Travel_Rarely       1273  Research & Development   \n",
       "..   ...                ...        ...                     ...   \n",
       "135   34      Travel_Rarely        704                   Sales   \n",
       "136   36      Travel_Rarely       1120                   Sales   \n",
       "137   29      Travel_Rarely        468  Research & Development   \n",
       "138   39      Travel_Rarely        722                   Sales   \n",
       "139   36  Travel_Frequently        884  Research & Development   \n",
       "\n",
       "     DistanceFromHome  Education EducationField  EnvironmentSatisfaction  \\\n",
       "0                   2          2          Other                        4   \n",
       "1                   2          1        Medical                        1   \n",
       "2                   2          2  Life Sciences                        4   \n",
       "3                   5          3          Other                        3   \n",
       "4                   2          2        Medical                        4   \n",
       "..                ...        ...            ...                      ...   \n",
       "135                28          3      Marketing                        4   \n",
       "136                11          4      Marketing                        2   \n",
       "137                28          4        Medical                        4   \n",
       "138                24          1      Marketing                        2   \n",
       "139                23          2        Medical                        3   \n",
       "\n",
       "     Gender  HourlyRate  ...  PerformanceRating  RelationshipSatisfaction  \\\n",
       "0      Male          92  ...                  3                         2   \n",
       "1      Male          40  ...                  3                         4   \n",
       "2      Male          79  ...                  3                         3   \n",
       "3    Female          58  ...                  3                         4   \n",
       "4    Female          72  ...                  3                         4   \n",
       "..      ...         ...  ...                ...                       ...   \n",
       "135  Female          95  ...                  4                         4   \n",
       "136  Female         100  ...                  3                         1   \n",
       "137  Female          73  ...                  3                         2   \n",
       "138  Female          60  ...                  3                         1   \n",
       "139    Male          41  ...                  3                         3   \n",
       "\n",
       "    StockOptionLevel  TotalWorkingYears TrainingTimesLastYear  \\\n",
       "0                  0                  7                     3   \n",
       "1                  1                  6                     3   \n",
       "2                  0                  8                     2   \n",
       "3                  1                 26                     3   \n",
       "4                  2                  6                     3   \n",
       "..               ...                ...                   ...   \n",
       "135                2                  8                     2   \n",
       "136                1                  8                     2   \n",
       "137                0                  5                     3   \n",
       "138                1                 21                     2   \n",
       "139                1                 17                     3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                  3               0                   0   \n",
       "1                  3               2                   2   \n",
       "2                  2               7                   7   \n",
       "3                  2              14                  13   \n",
       "4                  2               5                   3   \n",
       "..               ...             ...                 ...   \n",
       "135                3               8                   7   \n",
       "136                2               6                   3   \n",
       "137                1               5                   4   \n",
       "138                2              20                   9   \n",
       "139                3               5                   2   \n",
       "\n",
       "    YearsSinceLastPromotion YearsWithCurrManager  \n",
       "0                         0                    0  \n",
       "1                         2                    2  \n",
       "2                         3                    6  \n",
       "3                         4                    8  \n",
       "4                         1                    4  \n",
       "..                      ...                  ...  \n",
       "135                       1                    7  \n",
       "136                       0                    0  \n",
       "137                       0                    4  \n",
       "138                       9                    6  \n",
       "139                       0                    3  \n",
       "\n",
       "[140 rows x 31 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove excluded features from the validation dataset\n",
    "validation = validation[features.index.tolist()]\n",
    "validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8785714285714286"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get a score for the validation dataset from the saved pipeline\n",
    "model.score(validation, v_target.values.ravel())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Train a Keras model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>BusinessTravel_Non-Travel</th>\n",
       "      <th>BusinessTravel_Travel_Frequently</th>\n",
       "      <th>BusinessTravel_Travel_Rarely</th>\n",
       "      <th>Department_Human Resources</th>\n",
       "      <th>Department_Research &amp; Development</th>\n",
       "      <th>Department_Sales</th>\n",
       "      <th>Education_1</th>\n",
       "      <th>Education_2</th>\n",
       "      <th>Education_3</th>\n",
       "      <th>Education_4</th>\n",
       "      <th>...</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "      <th>JobRole0</th>\n",
       "      <th>JobRole1</th>\n",
       "      <th>JobRole2</th>\n",
       "      <th>JobRole3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.591154</td>\n",
       "      <td>-0.621514</td>\n",
       "      <td>1.462919</td>\n",
       "      <td>1.913468</td>\n",
       "      <td>1.143272</td>\n",
       "      <td>1.058170</td>\n",
       "      <td>0.512184</td>\n",
       "      <td>0.799463</td>\n",
       "      <td>0.058274</td>\n",
       "      <td>0.899445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.210630</td>\n",
       "      <td>-0.621514</td>\n",
       "      <td>-1.131942</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>-0.994429</td>\n",
       "      <td>-0.451462</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-1.706519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1193</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.464312</td>\n",
       "      <td>-0.621514</td>\n",
       "      <td>-0.969763</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>-0.994429</td>\n",
       "      <td>-0.451462</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-1.706519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.296735</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.969763</td>\n",
       "      <td>-1.175408</td>\n",
       "      <td>-0.678787</td>\n",
       "      <td>-1.160026</td>\n",
       "      <td>-0.994429</td>\n",
       "      <td>-0.451462</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>-1.706519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1165</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.296735</td>\n",
       "      <td>0.153090</td>\n",
       "      <td>-0.483227</td>\n",
       "      <td>-0.332987</td>\n",
       "      <td>-0.071434</td>\n",
       "      <td>-0.605477</td>\n",
       "      <td>0.512184</td>\n",
       "      <td>0.799463</td>\n",
       "      <td>0.058274</td>\n",
       "      <td>0.899445</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      BusinessTravel_Non-Travel  BusinessTravel_Travel_Frequently  \\\n",
       "1298                          0                                 0   \n",
       "620                           0                                 0   \n",
       "1193                          0                                 0   \n",
       "139                           0                                 0   \n",
       "1165                          0                                 0   \n",
       "\n",
       "      BusinessTravel_Travel_Rarely  Department_Human Resources  \\\n",
       "1298                             1                           0   \n",
       "620                              1                           0   \n",
       "1193                             1                           0   \n",
       "139                              1                           0   \n",
       "1165                             1                           0   \n",
       "\n",
       "      Department_Research & Development  Department_Sales  Education_1  \\\n",
       "1298                                  1                 0            0   \n",
       "620                                   1                 0            0   \n",
       "1193                                  1                 0            0   \n",
       "139                                   1                 0            0   \n",
       "1165                                  1                 0            1   \n",
       "\n",
       "      Education_2  Education_3  Education_4  ...  TotalWorkingYears  \\\n",
       "1298            0            1            0  ...           0.591154   \n",
       "620             0            0            1  ...           0.210630   \n",
       "1193            0            0            1  ...           0.464312   \n",
       "139             0            1            0  ...          -0.296735   \n",
       "1165            0            0            0  ...          -0.296735   \n",
       "\n",
       "      TrainingTimesLastYear  YearsAtCompany  YearsInCurrentRole  \\\n",
       "1298              -0.621514        1.462919            1.913468   \n",
       "620               -0.621514       -1.131942           -1.175408   \n",
       "1193              -0.621514       -0.969763           -1.175408   \n",
       "139                0.153090       -0.969763           -1.175408   \n",
       "1165               0.153090       -0.483227           -0.332987   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  JobRole0  JobRole1  \\\n",
       "1298                 1.143272              1.058170  0.512184  0.799463   \n",
       "620                 -0.678787             -1.160026 -0.994429 -0.451462   \n",
       "1193                -0.678787             -1.160026 -0.994429 -0.451462   \n",
       "139                 -0.678787             -1.160026 -0.994429 -0.451462   \n",
       "1165                -0.071434             -0.605477  0.512184  0.799463   \n",
       "\n",
       "      JobRole2  JobRole3  \n",
       "1298  0.058274  0.899445  \n",
       "620  -0.816773 -1.706519  \n",
       "1193 -0.816773 -1.706519  \n",
       "139  -0.816773 -1.706519  \n",
       "1165  0.058274  0.899445  \n",
       "\n",
       "[5 rows x 74 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run the training data through the preprocessor\n",
    "X_train_transformed = best_pipe.named_steps['prep'].transform(X_train)\n",
    "X_train_transformed.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# Encode target values\n",
    "le = LabelEncoder().fit(y_train.values.ravel())\n",
    "y_train_encoded = le.transform(y_train.values.ravel())\n",
    "y_train_encoded[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "931/931 [==============================] - 0s 498us/step - loss: 0.2025 - accuracy: 0.2266\n",
      "Epoch 2/50\n",
      "931/931 [==============================] - 0s 165us/step - loss: 0.1567 - accuracy: 0.3373\n",
      "Epoch 3/50\n",
      "931/931 [==============================] - 0s 178us/step - loss: 0.1286 - accuracy: 0.5800\n",
      "Epoch 4/50\n",
      "931/931 [==============================] - 0s 165us/step - loss: 0.1126 - accuracy: 0.6273\n",
      "Epoch 5/50\n",
      "931/931 [==============================] - 0s 167us/step - loss: 0.0951 - accuracy: 0.7132\n",
      "Epoch 6/50\n",
      "931/931 [==============================] - 0s 164us/step - loss: 0.0796 - accuracy: 0.7444\n",
      "Epoch 7/50\n",
      "931/931 [==============================] - 0s 155us/step - loss: 0.0626 - accuracy: 0.8163\n",
      "Epoch 8/50\n",
      "931/931 [==============================] - 0s 187us/step - loss: 0.0501 - accuracy: 0.8528\n",
      "Epoch 9/50\n",
      "931/931 [==============================] - 0s 202us/step - loss: 0.0432 - accuracy: 0.8937\n",
      "Epoch 10/50\n",
      "931/931 [==============================] - 0s 216us/step - loss: 0.0341 - accuracy: 0.9151\n",
      "Epoch 11/50\n",
      "931/931 [==============================] - 0s 209us/step - loss: 0.0302 - accuracy: 0.9323\n",
      "Epoch 12/50\n",
      "931/931 [==============================] - 0s 201us/step - loss: 0.0207 - accuracy: 0.9538\n",
      "Epoch 13/50\n",
      "931/931 [==============================] - 0s 194us/step - loss: 0.0166 - accuracy: 0.9646\n",
      "Epoch 14/50\n",
      "931/931 [==============================] - 0s 215us/step - loss: 0.0134 - accuracy: 0.9678\n",
      "Epoch 15/50\n",
      "931/931 [==============================] - 0s 178us/step - loss: 0.0094 - accuracy: 0.9817\n",
      "Epoch 16/50\n",
      "931/931 [==============================] - 0s 159us/step - loss: 0.0072 - accuracy: 0.9903\n",
      "Epoch 17/50\n",
      "931/931 [==============================] - 0s 162us/step - loss: 0.0052 - accuracy: 0.9936\n",
      "Epoch 18/50\n",
      "931/931 [==============================] - 0s 162us/step - loss: 0.0041 - accuracy: 0.9946\n",
      "Epoch 19/50\n",
      "931/931 [==============================] - 0s 160us/step - loss: 0.0132 - accuracy: 0.9774\n",
      "Epoch 20/50\n",
      "931/931 [==============================] - 0s 179us/step - loss: 0.0167 - accuracy: 0.9656\n",
      "Epoch 21/50\n",
      "931/931 [==============================] - 0s 185us/step - loss: 0.0070 - accuracy: 0.9850\n",
      "Epoch 22/50\n",
      "931/931 [==============================] - 0s 159us/step - loss: 0.0041 - accuracy: 0.9936\n",
      "Epoch 23/50\n",
      "931/931 [==============================] - 0s 162us/step - loss: 0.0019 - accuracy: 0.9989\n",
      "Epoch 24/50\n",
      "931/931 [==============================] - 0s 165us/step - loss: 0.0014 - accuracy: 0.9989\n",
      "Epoch 25/50\n",
      "931/931 [==============================] - 0s 207us/step - loss: 0.0010 - accuracy: 1.0000\n",
      "Epoch 26/50\n",
      "931/931 [==============================] - 0s 161us/step - loss: 8.1854e-04 - accuracy: 1.0000\n",
      "Epoch 27/50\n",
      "931/931 [==============================] - 0s 163us/step - loss: 6.7515e-04 - accuracy: 1.0000\n",
      "Epoch 28/50\n",
      "931/931 [==============================] - 0s 172us/step - loss: 5.9500e-04 - accuracy: 1.0000\n",
      "Epoch 29/50\n",
      "931/931 [==============================] - 0s 180us/step - loss: 5.1935e-04 - accuracy: 1.0000\n",
      "Epoch 30/50\n",
      "931/931 [==============================] - 0s 197us/step - loss: 4.4537e-04 - accuracy: 1.0000\n",
      "Epoch 31/50\n",
      "931/931 [==============================] - 0s 194us/step - loss: 3.9470e-04 - accuracy: 1.0000\n",
      "Epoch 32/50\n",
      "931/931 [==============================] - 0s 191us/step - loss: 3.5023e-04 - accuracy: 1.0000\n",
      "Epoch 33/50\n",
      "931/931 [==============================] - 0s 196us/step - loss: 3.1019e-04 - accuracy: 1.0000\n",
      "Epoch 34/50\n",
      "931/931 [==============================] - 0s 175us/step - loss: 2.7797e-04 - accuracy: 1.0000\n",
      "Epoch 35/50\n",
      "931/931 [==============================] - 0s 172us/step - loss: 2.5035e-04 - accuracy: 1.0000\n",
      "Epoch 36/50\n",
      "931/931 [==============================] - 0s 163us/step - loss: 2.2762e-04 - accuracy: 1.0000\n",
      "Epoch 37/50\n",
      "931/931 [==============================] - 0s 161us/step - loss: 2.0539e-04 - accuracy: 1.0000\n",
      "Epoch 38/50\n",
      "931/931 [==============================] - 0s 172us/step - loss: 1.8716e-04 - accuracy: 1.0000\n",
      "Epoch 39/50\n",
      "931/931 [==============================] - 0s 164us/step - loss: 1.6805e-04 - accuracy: 1.0000\n",
      "Epoch 40/50\n",
      "931/931 [==============================] - 0s 181us/step - loss: 1.5399e-04 - accuracy: 1.0000\n",
      "Epoch 41/50\n",
      "931/931 [==============================] - 0s 170us/step - loss: 1.3869e-04 - accuracy: 1.0000\n",
      "Epoch 42/50\n",
      "931/931 [==============================] - 0s 175us/step - loss: 1.2607e-04 - accuracy: 1.0000\n",
      "Epoch 43/50\n",
      "931/931 [==============================] - 0s 176us/step - loss: 1.1507e-04 - accuracy: 1.0000\n",
      "Epoch 44/50\n",
      "931/931 [==============================] - 0s 175us/step - loss: 1.0526e-04 - accuracy: 1.0000\n",
      "Epoch 45/50\n",
      "931/931 [==============================] - 0s 165us/step - loss: 9.6587e-05 - accuracy: 1.0000\n",
      "Epoch 46/50\n",
      "931/931 [==============================] - 0s 180us/step - loss: 8.8015e-05 - accuracy: 1.0000\n",
      "Epoch 47/50\n",
      "931/931 [==============================] - 0s 175us/step - loss: 8.1163e-05 - accuracy: 1.0000\n",
      "Epoch 48/50\n",
      "931/931 [==============================] - 0s 185us/step - loss: 7.3699e-05 - accuracy: 1.0000\n",
      "Epoch 49/50\n",
      "931/931 [==============================] - 0s 174us/step - loss: 6.7770e-05 - accuracy: 1.0000\n",
      "Epoch 50/50\n",
      "931/931 [==============================] - 0s 170us/step - loss: 6.2085e-05 - accuracy: 1.0000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.callbacks.History at 0x2469e051cc0>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "\n",
    "# Define the Keras model\n",
    "model = Sequential()\n",
    "model.add(Dense(100, input_dim=74, activation='relu'))\n",
    "model.add(Dense(50, activation='relu'))\n",
    "model.add(Dense(1, activation='sigmoid'))\n",
    "\n",
    "# Compile the Keras model\n",
    "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
    "\n",
    "# Fit the Keras model on the dataset\n",
    "model.fit(X_train_transformed, y_train_encoded, epochs=50, batch_size=8, class_weight={0:0.1, 1:2.0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "399/399 [==============================] - 0s 35us/step\n",
      "Keras test accuracy: 0.877\n"
     ]
    }
   ],
   "source": [
    "# Run the test data through the preprocessor\n",
    "X_test_transformed = best_pipe.named_steps['prep'].transform(X_test)\n",
    "# Encode the test labels\n",
    "y_test_encoded = le.transform(y_test.values.ravel())\n",
    "\n",
    "# Check model accuracy on test data\n",
    "print('Keras test accuracy: %.3f' % (model.evaluate(X_test_transformed, y_test_encoded)[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the keras model architecture and weights to disk\n",
    "model.save('HR-Attrition-Keras-v1.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keras prediction: 0\n"
     ]
    }
   ],
   "source": [
    "import keras\n",
    "from keras import backend as kerasbackend\n",
    "\n",
    "kerasbackend.clear_session()\n",
    "            \n",
    "# Load the keras model architecture and weights from disk\n",
    "keras_model = keras.models.load_model('HR-Attrition-Keras-v1.h5')\n",
    "keras_model._make_predict_function()\n",
    "\n",
    "print('Keras prediction: %.0f' % (keras_model.predict(X_test_transformed.iloc[[0]])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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