McKinsey ProHack Challange 2020 xgboost with optimization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains my approach to McKinsey ProHack Challange 2020. In this work i have investigate multiple approach to similar problems and try to create a hybrid solution. The thing that can make my solution special can be usage of knnimputer for handling missing values and usage of regressor's parameter tuning via hyperopt library.\n",
    "I train and test the model on the train data only since i can't measure losses on the test data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.metrics.regression module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.metrics. Anything that cannot be imported from sklearn.metrics is now part of the private API.\n",
      "  warnings.warn(message, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.impute import KNNImputer\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn import preprocessing\n",
    "from math import sqrt\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics.regression import mean_absolute_error as mae\n",
    "from sklearn.metrics import make_scorer\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from hyperopt import hp, fmin, tpe\n",
    "from hyperopt.pyll import scope\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>existence expectancy index</th>\n",
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       "      <th>Income Index</th>\n",
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       "      <th>Intergalactic Development Index (IDI)</th>\n",
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       "      <th>Population, total (millions)</th>\n",
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       "      <th>Mortality rate, under-five (per 1,000 live births)</th>\n",
       "      <th>Mortality rate, infant (per 1,000 live births)</th>\n",
       "      <th>Old age dependency ratio (old age (65 and older) per 100 creatures (ages 15-64))</th>\n",
       "      <th>Population, ages 15–64 (millions)</th>\n",
       "      <th>Population, ages 65 and older (millions)</th>\n",
       "      <th>Life expectancy at birth, male (galactic years)</th>\n",
       "      <th>Life expectancy at birth, female (galactic years)</th>\n",
       "      <th>Population, under age 5 (millions)</th>\n",
       "      <th>Young age (0-14) dependency ratio (per 100 creatures ages 15-64)</th>\n",
       "      <th>Adolescent birth rate (births per 1,000 female creatures ages 15-19)</th>\n",
       "      <th>Total unemployment rate (female to male ratio)</th>\n",
       "      <th>Vulnerable employment (% of total employment)</th>\n",
       "      <th>Unemployment, total (% of labour force)</th>\n",
       "      <th>Employment in agriculture (% of total employment)</th>\n",
       "      <th>Labour force participation rate (% ages 15 and older)</th>\n",
       "      <th>Labour force participation rate (% ages 15 and older), female</th>\n",
       "      <th>Employment in services (% of total employment)</th>\n",
       "      <th>Labour force participation rate (% ages 15 and older), male</th>\n",
       "      <th>Employment to population ratio (% ages 15 and older)</th>\n",
       "      <th>Jungle area (% of total land area)</th>\n",
       "      <th>Share of employment in nonagriculture, female (% of total employment in nonagriculture)</th>\n",
       "      <th>Youth unemployment rate (female to male ratio)</th>\n",
       "      <th>Unemployment, youth (% ages 15–24)</th>\n",
       "      <th>Mortality rate, female grown up (per 1,000 people)</th>\n",
       "      <th>Mortality rate, male grown up (per 1,000 people)</th>\n",
       "      <th>Infants lacking immunization, red hot disease (% of one-galactic year-olds)</th>\n",
       "      <th>Infants lacking immunization, Combination Vaccine (% of one-galactic year-olds)</th>\n",
       "      <th>Gross galactic product (GGP) per capita</th>\n",
       "      <th>Gross galactic product (GGP), total</th>\n",
       "      <th>Outer Galaxies direct investment, net inflows (% of GGP)</th>\n",
       "      <th>Exports and imports (% of GGP)</th>\n",
       "      <th>Share of seats in senate (% held by female)</th>\n",
       "      <th>Natural resource depletion</th>\n",
       "      <th>Mean years of education, female (galactic years)</th>\n",
       "      <th>Mean years of education, male (galactic years)</th>\n",
       "      <th>Expected years of education, female (galactic years)</th>\n",
       "      <th>Expected years of education, male (galactic years)</th>\n",
       "      <th>Maternal mortality ratio (deaths per 100,000 live births)</th>\n",
       "      <th>Renewable energy consumption (% of total final energy consumption)</th>\n",
       "      <th>Estimated gross galactic income per capita, male</th>\n",
       "      <th>Estimated gross galactic income per capita, female</th>\n",
       "      <th>Rural population with access to electricity (%)</th>\n",
       "      <th>Domestic credit provided by financial sector (% of GGP)</th>\n",
       "      <th>Population with at least some secondary education, female (% ages 25 and older)</th>\n",
       "      <th>Population with at least some secondary education, male (% ages 25 and older)</th>\n",
       "      <th>Gross fixed capital formation (% of GGP)</th>\n",
       "      <th>Remittances, inflows (% of GGP)</th>\n",
       "      <th>Population with at least some secondary education (% ages 25 and older)</th>\n",
       "      <th>Intergalactic inbound tourists (thousands)</th>\n",
       "      <th>Gross enrolment ratio, primary (% of primary under-age population)</th>\n",
       "      <th>Respiratory disease incidence (per 100,000 people)</th>\n",
       "      <th>Interstellar phone subscriptions (per 100 people)</th>\n",
       "      <th>Interstellar Data Net users, total (% of population)</th>\n",
       "      <th>Current health expenditure (% of GGP)</th>\n",
       "      <th>Intergalactic Development Index (IDI), female</th>\n",
       "      <th>Intergalactic Development Index (IDI), male</th>\n",
       "      <th>Gender Development Index (GDI)</th>\n",
       "      <th>Intergalactic Development Index (IDI), female, Rank</th>\n",
       "      <th>Intergalactic Development Index (IDI), male, Rank</th>\n",
       "      <th>Adjusted net savings</th>\n",
       "      <th>Creature Immunodeficiency Disease prevalence, adult (% ages 15-49), total</th>\n",
       "      <th>Private galaxy capital flows (% of GGP)</th>\n",
       "      <th>Gender Inequality Index (GII)</th>\n",
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       "      <td>68.168081</td>\n",
       "      <td>24615.241111</td>\n",
       "      <td>0.691643</td>\n",
       "      <td>12.463787</td>\n",
       "      <td>6.907088</td>\n",
       "      <td>0.558809</td>\n",
       "      <td>0.367607</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102.488207</td>\n",
       "      <td>69.492450</td>\n",
       "      <td>26.14549</td>\n",
       "      <td>1270.75047</td>\n",
       "      <td>51.635952</td>\n",
       "      <td>141.410527</td>\n",
       "      <td>111.576541</td>\n",
       "      <td>16.085961</td>\n",
       "      <td>664.201756</td>\n",
       "      <td>60.031881</td>\n",
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       "      <td>24.009969</td>\n",
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       "      <td>Pictor II</td>\n",
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       "    <tr>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.096601</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      galactic year                       galaxy  existence expectancy index  \\\n",
       "1834        1000000     Carina Dwarf (E206-G220)                    0.683066   \n",
       "1217         996004                    Pictor II                    0.990119   \n",
       "542          993012                     Maffei 2                    0.866042   \n",
       "2053        1001000              NGC 147 (DDO 3)                    0.552732   \n",
       "2581        1004004  KKH 11 (ZOAG G135.74-04.53)                    0.980875   \n",
       "\n",
       "      existence expectancy at birth  Gross income per capita  Income Index  \\\n",
       "1834                      68.168081             24615.241111      0.691643   \n",
       "1217                      84.355560             58391.510809      0.938477   \n",
       "542                       75.328206             29664.424677      0.571391   \n",
       "2053                      64.088779             18988.184195      0.654838   \n",
       "2581                      83.927089             23933.694960      0.839285   \n",
       "\n",
       "      Expected years of education (galactic years)  \\\n",
       "1834                                     12.463787   \n",
       "1217                                     21.267333   \n",
       "542                                      10.311530   \n",
       "2053                                     10.560082   \n",
       "2581                                     18.207712   \n",
       "\n",
       "      Mean years of education (galactic years)  \\\n",
       "1834                                  6.907088   \n",
       "1217                                 13.735319   \n",
       "542                                        NaN   \n",
       "2053                                  7.992130   \n",
       "2581                                 11.833098   \n",
       "\n",
       "      Intergalactic Development Index (IDI)  Education Index  \\\n",
       "1834                               0.558809         0.367607   \n",
       "1217                               1.010111         1.076723   \n",
       "542                                     NaN              NaN   \n",
       "2053                               0.675970         0.523748   \n",
       "2581                               0.890669         0.919344   \n",
       "\n",
       "      Intergalactic Development Index (IDI), Rank  \\\n",
       "1834                                          NaN   \n",
       "1217                                    57.261884   \n",
       "542                                           NaN   \n",
       "2053                                   186.150538   \n",
       "2581                                   134.397117   \n",
       "\n",
       "      Population using at least basic drinking-water services (%)  \\\n",
       "1834                                         102.488207             \n",
       "1217                                                NaN             \n",
       "542                                                 NaN             \n",
       "2053                                          55.584494             \n",
       "2581                                         109.235865             \n",
       "\n",
       "      Population using at least basic sanitation services (%)  \\\n",
       "1834                                          69.492450         \n",
       "1217                                                NaN         \n",
       "542                                                 NaN         \n",
       "2053                                          76.325372         \n",
       "2581                                         136.623705         \n",
       "\n",
       "      Gross capital formation (% of GGP)  Population, total (millions)  \\\n",
       "1834                            26.14549                    1270.75047   \n",
       "1217                                 NaN                           NaN   \n",
       "542                                  NaN                           NaN   \n",
       "2053                                 NaN                           NaN   \n",
       "2581                                 NaN                           NaN   \n",
       "\n",
       "      Population, urban (%)  \\\n",
       "1834              51.635952   \n",
       "1217                    NaN   \n",
       "542                     NaN   \n",
       "2053                    NaN   \n",
       "2581                    NaN   \n",
       "\n",
       "      Mortality rate, under-five (per 1,000 live births)  \\\n",
       "1834                                         141.410527    \n",
       "1217                                                NaN    \n",
       "542                                                 NaN    \n",
       "2053                                                NaN    \n",
       "2581                                                NaN    \n",
       "\n",
       "      Mortality rate, infant (per 1,000 live births)  \\\n",
       "1834                                      111.576541   \n",
       "1217                                             NaN   \n",
       "542                                              NaN   \n",
       "2053                                             NaN   \n",
       "2581                                             NaN   \n",
       "\n",
       "      Old age dependency ratio (old age (65 and older) per 100 creatures (ages 15-64))  \\\n",
       "1834                                          16.085961                                  \n",
       "1217                                                NaN                                  \n",
       "542                                                 NaN                                  \n",
       "2053                                                NaN                                  \n",
       "2581                                                NaN                                  \n",
       "\n",
       "      Population, ages 15–64 (millions)  \\\n",
       "1834                         664.201756   \n",
       "1217                                NaN   \n",
       "542                                 NaN   \n",
       "2053                                NaN   \n",
       "2581                                NaN   \n",
       "\n",
       "      Population, ages 65 and older (millions)  \\\n",
       "1834                                 60.031881   \n",
       "1217                                       NaN   \n",
       "542                                        NaN   \n",
       "2053                                       NaN   \n",
       "2581                                       NaN   \n",
       "\n",
       "      Life expectancy at birth, male (galactic years)  \\\n",
       "1834                                        67.014791   \n",
       "1217                                              NaN   \n",
       "542                                               NaN   \n",
       "2053                                              NaN   \n",
       "2581                                              NaN   \n",
       "\n",
       "      Life expectancy at birth, female (galactic years)  \\\n",
       "1834                                          68.629045   \n",
       "1217                                                NaN   \n",
       "542                                                 NaN   \n",
       "2053                                                NaN   \n",
       "2581                                                NaN   \n",
       "\n",
       "      Population, under age 5 (millions)  \\\n",
       "1834                           58.325057   \n",
       "1217                                 NaN   \n",
       "542                                  NaN   \n",
       "2053                                 NaN   \n",
       "2581                                 NaN   \n",
       "\n",
       "      Young age (0-14) dependency ratio (per 100 creatures ages 15-64)  \\\n",
       "1834                                         104.629852                  \n",
       "1217                                                NaN                  \n",
       "542                                                 NaN                  \n",
       "2053                                                NaN                  \n",
       "2581                                                NaN                  \n",
       "\n",
       "      Adolescent birth rate (births per 1,000 female creatures ages 15-19)  \\\n",
       "1834                                         155.826773                      \n",
       "1217                                                NaN                      \n",
       "542                                                 NaN                      \n",
       "2053                                                NaN                      \n",
       "2581                                                NaN                      \n",
       "\n",
       "      Total unemployment rate (female to male ratio)  \\\n",
       "1834                                        2.493515   \n",
       "1217                                             NaN   \n",
       "542                                              NaN   \n",
       "2053                                             NaN   \n",
       "2581                                             NaN   \n",
       "\n",
       "      Vulnerable employment (% of total employment)  \\\n",
       "1834                                      89.180005   \n",
       "1217                                            NaN   \n",
       "542                                             NaN   \n",
       "2053                                            NaN   \n",
       "2581                                            NaN   \n",
       "\n",
       "      Unemployment, total (% of labour force)  \\\n",
       "1834                                10.352628   \n",
       "1217                                      NaN   \n",
       "542                                       NaN   \n",
       "2053                                      NaN   \n",
       "2581                                      NaN   \n",
       "\n",
       "      Employment in agriculture (% of total employment)  \\\n",
       "1834                                          70.873016   \n",
       "1217                                                NaN   \n",
       "542                                                 NaN   \n",
       "2053                                                NaN   \n",
       "2581                                                NaN   \n",
       "\n",
       "      Labour force participation rate (% ages 15 and older)  \\\n",
       "1834                                          57.338404       \n",
       "1217                                                NaN       \n",
       "542                                                 NaN       \n",
       "2053                                                NaN       \n",
       "2581                                                NaN       \n",
       "\n",
       "      Labour force participation rate (% ages 15 and older), female  \\\n",
       "1834                                          34.716354               \n",
       "1217                                                NaN               \n",
       "542                                                 NaN               \n",
       "2053                                                NaN               \n",
       "2581                                                NaN               \n",
       "\n",
       "      Employment in services (% of total employment)  \\\n",
       "1834                                       59.715565   \n",
       "1217                                             NaN   \n",
       "542                                              NaN   \n",
       "2053                                             NaN   \n",
       "2581                                             NaN   \n",
       "\n",
       "      Labour force participation rate (% ages 15 and older), male  \\\n",
       "1834                                          58.733537             \n",
       "1217                                                NaN             \n",
       "542                                                 NaN             \n",
       "2053                                                NaN             \n",
       "2581                                                NaN             \n",
       "\n",
       "      Employment to population ratio (% ages 15 and older)  \\\n",
       "1834                                          58.187145      \n",
       "1217                                                NaN      \n",
       "542                                                 NaN      \n",
       "2053                                                NaN      \n",
       "2581                                                NaN      \n",
       "\n",
       "      Jungle area (% of total land area)  \\\n",
       "1834                           36.503294   \n",
       "1217                                 NaN   \n",
       "542                                  NaN   \n",
       "2053                                 NaN   \n",
       "2581                                 NaN   \n",
       "\n",
       "      Share of employment in nonagriculture, female (% of total employment in nonagriculture)  \\\n",
       "1834                                          38.790446                                         \n",
       "1217                                                NaN                                         \n",
       "542                                                 NaN                                         \n",
       "2053                                                NaN                                         \n",
       "2581                                                NaN                                         \n",
       "\n",
       "      Youth unemployment rate (female to male ratio)  \\\n",
       "1834                                         1.81998   \n",
       "1217                                             NaN   \n",
       "542                                              NaN   \n",
       "2053                                             NaN   \n",
       "2581                                             NaN   \n",
       "\n",
       "      Unemployment, youth (% ages 15–24)  \\\n",
       "1834                           25.781253   \n",
       "1217                                 NaN   \n",
       "542                                  NaN   \n",
       "2053                                 NaN   \n",
       "2581                                 NaN   \n",
       "\n",
       "      Mortality rate, female grown up (per 1,000 people)  \\\n",
       "1834                                          363.25365    \n",
       "1217                                                NaN    \n",
       "542                                                 NaN    \n",
       "2053                                                NaN    \n",
       "2581                                                NaN    \n",
       "\n",
       "      Mortality rate, male grown up (per 1,000 people)  \\\n",
       "1834                                        395.012893   \n",
       "1217                                               NaN   \n",
       "542                                                NaN   \n",
       "2053                                               NaN   \n",
       "2581                                               NaN   \n",
       "\n",
       "      Infants lacking immunization, red hot disease (% of one-galactic year-olds)  \\\n",
       "1834                                          40.668232                             \n",
       "1217                                                NaN                             \n",
       "542                                                 NaN                             \n",
       "2053                                                NaN                             \n",
       "2581                                                NaN                             \n",
       "\n",
       "      Infants lacking immunization, Combination Vaccine (% of one-galactic year-olds)  \\\n",
       "1834                                          24.195895                                 \n",
       "1217                                                NaN                                 \n",
       "542                                                 NaN                                 \n",
       "2053                                                NaN                                 \n",
       "2581                                                NaN                                 \n",
       "\n",
       "      Gross galactic product (GGP) per capita  \\\n",
       "1834                              5168.707297   \n",
       "1217                                      NaN   \n",
       "542                                       NaN   \n",
       "2053                                      NaN   \n",
       "2581                                      NaN   \n",
       "\n",
       "      Gross galactic product (GGP), total  \\\n",
       "1834                         10374.713116   \n",
       "1217                                  NaN   \n",
       "542                                   NaN   \n",
       "2053                                  NaN   \n",
       "2581                                  NaN   \n",
       "\n",
       "      Outer Galaxies direct investment, net inflows (% of GGP)  \\\n",
       "1834                                          12.037633          \n",
       "1217                                                NaN          \n",
       "542                                                 NaN          \n",
       "2053                                                NaN          \n",
       "2581                                                NaN          \n",
       "\n",
       "      Exports and imports (% of GGP)  \\\n",
       "1834                      100.684153   \n",
       "1217                             NaN   \n",
       "542                              NaN   \n",
       "2053                             NaN   \n",
       "2581                             NaN   \n",
       "\n",
       "      Share of seats in senate (% held by female)  Natural resource depletion  \\\n",
       "1834                                          NaN                    7.297492   \n",
       "1217                                          NaN                         NaN   \n",
       "542                                           NaN                         NaN   \n",
       "2053                                          NaN                         NaN   \n",
       "2581                                          NaN                         NaN   \n",
       "\n",
       "      Mean years of education, female (galactic years)  \\\n",
       "1834                                          5.847486   \n",
       "1217                                               NaN   \n",
       "542                                                NaN   \n",
       "2053                                               NaN   \n",
       "2581                                               NaN   \n",
       "\n",
       "      Mean years of education, male (galactic years)  \\\n",
       "1834                                        7.524211   \n",
       "1217                                             NaN   \n",
       "542                                              NaN   \n",
       "2053                                             NaN   \n",
       "2581                                             NaN   \n",
       "\n",
       "      Expected years of education, female (galactic years)  \\\n",
       "1834                                          11.999416      \n",
       "1217                                                NaN      \n",
       "542                                                 NaN      \n",
       "2053                                                NaN      \n",
       "2581                                                NaN      \n",
       "\n",
       "      Expected years of education, male (galactic years)  \\\n",
       "1834                                          11.517468    \n",
       "1217                                                NaN    \n",
       "542                                                 NaN    \n",
       "2053                                                NaN    \n",
       "2581                                                NaN    \n",
       "\n",
       "      Maternal mortality ratio (deaths per 100,000 live births)  \\\n",
       "1834                                         865.567725           \n",
       "1217                                                NaN           \n",
       "542                                                 NaN           \n",
       "2053                                                NaN           \n",
       "2581                                                NaN           \n",
       "\n",
       "      Renewable energy consumption (% of total final energy consumption)  \\\n",
       "1834                                          94.323357                    \n",
       "1217                                                NaN                    \n",
       "542                                                 NaN                    \n",
       "2053                                                NaN                    \n",
       "2581                                                NaN                    \n",
       "\n",
       "      Estimated gross galactic income per capita, male  \\\n",
       "1834                                      39207.235708   \n",
       "1217                                               NaN   \n",
       "542                                                NaN   \n",
       "2053                                               NaN   \n",
       "2581                                               NaN   \n",
       "\n",
       "      Estimated gross galactic income per capita, female  \\\n",
       "1834                                       13239.993252    \n",
       "1217                                                NaN    \n",
       "542                                                 NaN    \n",
       "2053                                                NaN    \n",
       "2581                                                NaN    \n",
       "\n",
       "      Rural population with access to electricity (%)  \\\n",
       "1834                                        67.497801   \n",
       "1217                                              NaN   \n",
       "542                                               NaN   \n",
       "2053                                              NaN   \n",
       "2581                                              NaN   \n",
       "\n",
       "      Domestic credit provided by financial sector (% of GGP)  \\\n",
       "1834                                          46.610052         \n",
       "1217                                                NaN         \n",
       "542                                                 NaN         \n",
       "2053                                                NaN         \n",
       "2581                                                NaN         \n",
       "\n",
       "      Population with at least some secondary education, female (% ages 25 and older)  \\\n",
       "1834                                                NaN                                 \n",
       "1217                                                NaN                                 \n",
       "542                                                 NaN                                 \n",
       "2053                                                NaN                                 \n",
       "2581                                                NaN                                 \n",
       "\n",
       "      Population with at least some secondary education, male (% ages 25 and older)  \\\n",
       "1834                                                NaN                               \n",
       "1217                                                NaN                               \n",
       "542                                                 NaN                               \n",
       "2053                                                NaN                               \n",
       "2581                                                NaN                               \n",
       "\n",
       "      Gross fixed capital formation (% of GGP)  \\\n",
       "1834                                 22.796321   \n",
       "1217                                       NaN   \n",
       "542                                        NaN   \n",
       "2053                                       NaN   \n",
       "2581                                       NaN   \n",
       "\n",
       "      Remittances, inflows (% of GGP)  \\\n",
       "1834                              NaN   \n",
       "1217                              NaN   \n",
       "542                               NaN   \n",
       "2053                              NaN   \n",
       "2581                              NaN   \n",
       "\n",
       "      Population with at least some secondary education (% ages 25 and older)  \\\n",
       "1834                                                NaN                         \n",
       "1217                                                NaN                         \n",
       "542                                                 NaN                         \n",
       "2053                                                NaN                         \n",
       "2581                                                NaN                         \n",
       "\n",
       "      Intergalactic inbound tourists (thousands)  \\\n",
       "1834                                63647.608851   \n",
       "1217                                         NaN   \n",
       "542                                          NaN   \n",
       "2053                                         NaN   \n",
       "2581                                         NaN   \n",
       "\n",
       "      Gross enrolment ratio, primary (% of primary under-age population)  \\\n",
       "1834                                         113.268931                    \n",
       "1217                                                NaN                    \n",
       "542                                                 NaN                    \n",
       "2053                                                NaN                    \n",
       "2581                                                NaN                    \n",
       "\n",
       "      Respiratory disease incidence (per 100,000 people)  \\\n",
       "1834                                          280.69331    \n",
       "1217                                                NaN    \n",
       "542                                                 NaN    \n",
       "2053                                                NaN    \n",
       "2581                                                NaN    \n",
       "\n",
       "      Interstellar phone subscriptions (per 100 people)  \\\n",
       "1834                                          74.143183   \n",
       "1217                                                NaN   \n",
       "542                                                 NaN   \n",
       "2053                                                NaN   \n",
       "2581                                                NaN   \n",
       "\n",
       "      Interstellar Data Net users, total (% of population)  \\\n",
       "1834                                          24.009969      \n",
       "1217                                                NaN      \n",
       "542                                                 NaN      \n",
       "2053                                                NaN      \n",
       "2581                                                NaN      \n",
       "\n",
       "      Current health expenditure (% of GGP)  \\\n",
       "1834                              13.457071   \n",
       "1217                                    NaN   \n",
       "542                                     NaN   \n",
       "2053                                    NaN   \n",
       "2581                                    NaN   \n",
       "\n",
       "      Intergalactic Development Index (IDI), female  \\\n",
       "1834                                       0.537767   \n",
       "1217                                            NaN   \n",
       "542                                             NaN   \n",
       "2053                                            NaN   \n",
       "2581                                            NaN   \n",
       "\n",
       "      Intergalactic Development Index (IDI), male  \\\n",
       "1834                                     0.710307   \n",
       "1217                                          NaN   \n",
       "542                                           NaN   \n",
       "2053                                          NaN   \n",
       "2581                                          NaN   \n",
       "\n",
       "      Gender Development Index (GDI)  \\\n",
       "1834                        0.899854   \n",
       "1217                             NaN   \n",
       "542                              NaN   \n",
       "2053                             NaN   \n",
       "2581                             NaN   \n",
       "\n",
       "      Intergalactic Development Index (IDI), female, Rank  \\\n",
       "1834                                                NaN     \n",
       "1217                                                NaN     \n",
       "542                                                 NaN     \n",
       "2053                                                NaN     \n",
       "2581                                                NaN     \n",
       "\n",
       "      Intergalactic Development Index (IDI), male, Rank  \\\n",
       "1834                                                NaN   \n",
       "1217                                                NaN   \n",
       "542                                                 NaN   \n",
       "2053                                                NaN   \n",
       "2581                                                NaN   \n",
       "\n",
       "      Adjusted net savings   \\\n",
       "1834                    NaN   \n",
       "1217                    NaN   \n",
       "542                     NaN   \n",
       "2053                    NaN   \n",
       "2581                    NaN   \n",
       "\n",
       "      Creature Immunodeficiency Disease prevalence, adult (% ages 15-49), total  \\\n",
       "1834                                           5.137678                           \n",
       "1217                                                NaN                           \n",
       "542                                                 NaN                           \n",
       "2053                                                NaN                           \n",
       "2581                                                NaN                           \n",
       "\n",
       "      Private galaxy capital flows (% of GGP)  Gender Inequality Index (GII)  \\\n",
       "1834                                      NaN                            NaN   \n",
       "1217                                      NaN                            NaN   \n",
       "542                                       NaN                            NaN   \n",
       "2053                                      NaN                            NaN   \n",
       "2581                                      NaN                            NaN   \n",
       "\n",
       "             y  \n",
       "1834  0.047766  \n",
       "1217  0.182895  \n",
       "542   0.051707  \n",
       "2053  0.044860  \n",
       "2581  0.096601  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train=pd.read_csv('train.csv')\n",
    "train.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#encoding categorical columns\n",
    "le = preprocessing.LabelEncoder()\n",
    "train['galaxy']=le.fit_transform(train['galaxy'])\n",
    "train['galactic year']=le.fit_transform(train['galactic year'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#missing values handled with knnimputer\n",
    "imp = KNNImputer(weights='distance')\n",
    "train=pd.DataFrame(imp.fit_transform(train.copy()), columns=train.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Choosing high correlation  columsn for training\n",
    "corr = train.corrwith(train['y'])\n",
    "dictt = corr.to_dict()\n",
    "Corrlist = []\n",
    "for key,value in dictt.items():\n",
    "    if value >= 0.3:\n",
    "        Corrlist.append(key)\n",
    "    elif value <= - 0.3:\n",
    "        Corrlist.append(key)\n",
    "train_final = train[Corrlist]\n",
    "train_final=train_final.drop('y', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#a great script for parameter tuning, i can't remember the source\n",
    "scope.define(GradientBoostingRegressor)    \n",
    "\n",
    "def train_GradientBoostingRegressor(Xdata, Ydata, loss='ls' ,alpha = 0.50, cv = 2, n_steps = 10):\n",
    "    #split data\n",
    "    X_train, X_test, y_train, y_test = train_test_split(Xdata, Ydata, test_size=.33, random_state = 42)\n",
    "    \n",
    "    # create and objective function\n",
    "    def objective_function_regression(estimator):\n",
    "        mae_array = cross_val_score( estimator, X_train, y_train, cv= cv, n_jobs=-1, \n",
    "                                    scoring = make_scorer(mae) )\n",
    "        return mae_array.mean()\n",
    "\n",
    "\n",
    "    # search space\n",
    "    n_estimators     = hp.randint('n_estimators',1000) \n",
    "    learning_rate    = hp.loguniform('learning_rate',-3,1)\n",
    "    max_depth        = hp.randint('max_depth', 10)\n",
    "    max_features     = hp.randint('max_features',X_train.shape[1])\n",
    "    min_samples_leaf = hp.randint('min_samples_leaf', 10)\n",
    "    #criterion        = hp.choice('criterion', ['friedman_mse'])\n",
    "                                       \n",
    "    # model / estimator to be optimized\n",
    "    est0 = (0.1, scope.GradientBoostingRegressor( n_estimators  = n_estimators + 1,\n",
    "                                            learning_rate = learning_rate,\n",
    "                                            max_depth = max_depth + 1,\n",
    "                                            max_features = max_features + 1,\n",
    "                                            min_samples_leaf = min_samples_leaf + 1,\n",
    "                                            random_state= 101) \n",
    "        )\n",
    "\n",
    "    search_space_regression = hp.pchoice('estimator', [est0])\n",
    "    \n",
    "    best = fmin(\n",
    "    fn= objective_function_regression,\n",
    "    space= search_space_regression,\n",
    "    algo = tpe.suggest, # This is the optimization algorithm hyperopt uses, a tree of parzen estimators\n",
    "    max_evals = n_steps,\n",
    "    verbose = 0  # The number of iterations\n",
    "         )\n",
    "    \n",
    "    # Allocate optimized parameters and apply to test data set\n",
    "    Regressor = GradientBoostingRegressor( learning_rate = best['learning_rate'],\n",
    "                          max_depth = best['max_depth'],\n",
    "                          max_features = best['max_features'],\n",
    "                          min_samples_leaf = best['min_samples_leaf'],\n",
    "                          n_estimators = best['n_estimators'],\n",
    "                          random_state = 101\n",
    "                                       )\n",
    "    # fit\n",
    "    Regressor.fit(X_train,y_train)\n",
    "    \n",
    "    #evaluate\n",
    "    yhat = Regressor.predict(X_test) ;\n",
    "    error_pct = np.round( np.median(np.abs(yhat - y_test)), 2)\n",
    "    #print('--'*20)\n",
    "    \n",
    "    print(\"{} {}\".format('The Median Abs. Error (%) for the test set is :', error_pct))\n",
    "    \n",
    "    return Regressor, y_test, yhat "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Median Abs. Error (%) for the test set is : 0.01\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(GradientBoostingRegressor(learning_rate=0.07906541393315811, max_features=42,\n",
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       " 3583    0.029127\n",
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       " 462     0.089346\n",
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       " 328     0.068582\n",
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       " 367     0.059493\n",
       " 3335    0.049538\n",
       " 2917    0.039898\n",
       " 2111    0.056985\n",
       " 2763    0.068138\n",
       " 772     0.066039\n",
       " 2453    0.379398\n",
       " 3608    0.049725\n",
       " 3037    0.319765\n",
       " 498     0.048741\n",
       " 1234    0.101893\n",
       " 1420    0.183552\n",
       " 435     0.053141\n",
       " 365     0.050312\n",
       " 1862    0.047613\n",
       " 276     0.082301\n",
       " 2552    0.058177\n",
       " 3602    0.182444\n",
       " 1584    0.047187\n",
       " 407     0.050288\n",
       " 2249    0.291572\n",
       " 1263    0.059203\n",
       " 3374    0.040166\n",
       " 844     0.080353\n",
       " 1788    0.217605\n",
       " 1670    0.050005\n",
       " 2003    0.042593\n",
       " 2164    0.063025\n",
       " 1910    0.067396\n",
       " 3240    0.217826\n",
       " 1783    0.115425\n",
       " 3384    0.038319\n",
       " 855     0.159479\n",
       " 3121    0.125961\n",
       " 78      0.052425\n",
       " 944     0.066515\n",
       " 199     0.059080\n",
       " 1600    0.058162\n",
       " 1514    0.048994\n",
       " Name: y, dtype: float64, array([0.06672628, 0.06930328, 0.04256048, ..., 0.05548033, 0.06712246,\n",
       "        0.04535004]))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_GradientBoostingRegressor(train_final, train['y'], loss='ls' ,alpha = 0.50, cv = 2, n_steps = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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