predict_reach_goal.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[<span style=\"color:#FF7B07\">**1. Import Libraries and Load Data**](#1)<br>\n",
    "[<span style=\"color:#FF7B07\">**2. Balance Data**](#2)<br>\n",
    "[<span style=\"color:#FF7B07\">**3. Create & Test Model**](#3)<br> \n",
    "[<span style=\"color:#FF7B07\">**4. Reduce Data Features & Test**](#4)<br>\n",
    "[<span style=\"color:#FF7B07\">**5. Summary**](#5)<br> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#FF7B07\"><div align=\"center\">**Import Libraries and Load Data** <a  name=\"1\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from imblearn.over_sampling import SMOTE\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from plotly.subplots import make_subplots\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split, KFold\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import f1_score,precision_score,recall_score,accuracy_score\n",
    "from sklearn.metrics import classification_report,confusion_matrix\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import decomposition\n",
    "import itertools\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The data is large and this command will help us to see the whole result \n",
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('../data/data_for_predit_reach_goal.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> We use the first 7 days in input and the last 5 days for output so we need applicants who have at least 12 days of log. <br> To be definitely sure I leave users who has 30 or more days of logs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data[data[\"logged_frequency\"]>30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    2196\n",
       "1.0     950\n",
       "Name: reach_goal, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"reach_goal\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> As you see data is imbalanced so we need to handle this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Data shape - (3146, 207) \n",
      " Unique users - 3146 \n",
      "\n"
     ]
    },
    {
     "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>user_id</th>\n",
       "      <th>total_calories</th>\n",
       "      <th>total_carbs</th>\n",
       "      <th>total_fat</th>\n",
       "      <th>total_protein</th>\n",
       "      <th>total_sodium</th>\n",
       "      <th>total_sugar</th>\n",
       "      <th>goal_calories</th>\n",
       "      <th>goal_carbs</th>\n",
       "      <th>goal_fat</th>\n",
       "      <th>goal_protein</th>\n",
       "      <th>goal_sodium</th>\n",
       "      <th>goal_sugar</th>\n",
       "      <th>foods_len</th>\n",
       "      <th>healtyDistrib</th>\n",
       "      <th>calories_diff</th>\n",
       "      <th>carbs_diff</th>\n",
       "      <th>fat_diff</th>\n",
       "      <th>protein_diff</th>\n",
       "      <th>sodium_diff</th>\n",
       "      <th>sugar_diff</th>\n",
       "      <th>total_calories_1</th>\n",
       "      <th>total_carbs_1</th>\n",
       "      <th>total_fat_1</th>\n",
       "      <th>total_protein_1</th>\n",
       "      <th>total_sodium_1</th>\n",
       "      <th>total_sugar_1</th>\n",
       "      <th>goal_calories_1</th>\n",
       "      <th>goal_carbs_1</th>\n",
       "      <th>goal_fat_1</th>\n",
       "      <th>goal_protein_1</th>\n",
       "      <th>goal_sodium_1</th>\n",
       "      <th>goal_sugar_1</th>\n",
       "      <th>foods_len_1</th>\n",
       "      <th>healtyDistrib_1</th>\n",
       "      <th>calories_diff_1</th>\n",
       "      <th>carbs_diff_1</th>\n",
       "      <th>fat_diff_1</th>\n",
       "      <th>protein_diff_1</th>\n",
       "      <th>sodium_diff_1</th>\n",
       "      <th>sugar_diff_1</th>\n",
       "      <th>total_calories_2</th>\n",
       "      <th>total_carbs_2</th>\n",
       "      <th>total_fat_2</th>\n",
       "      <th>total_protein_2</th>\n",
       "      <th>total_sodium_2</th>\n",
       "      <th>total_sugar_2</th>\n",
       "      <th>goal_calories_2</th>\n",
       "      <th>goal_carbs_2</th>\n",
       "      <th>goal_fat_2</th>\n",
       "      <th>goal_protein_2</th>\n",
       "      <th>goal_sodium_2</th>\n",
       "      <th>goal_sugar_2</th>\n",
       "      <th>foods_len_2</th>\n",
       "      <th>healtyDistrib_2</th>\n",
       "      <th>calories_diff_2</th>\n",
       "      <th>carbs_diff_2</th>\n",
       "      <th>fat_diff_2</th>\n",
       "      <th>protein_diff_2</th>\n",
       "      <th>sodium_diff_2</th>\n",
       "      <th>sugar_diff_2</th>\n",
       "      <th>total_calories_3</th>\n",
       "      <th>total_carbs_3</th>\n",
       "      <th>total_fat_3</th>\n",
       "      <th>total_protein_3</th>\n",
       "      <th>total_sodium_3</th>\n",
       "      <th>total_sugar_3</th>\n",
       "      <th>goal_calories_3</th>\n",
       "      <th>goal_carbs_3</th>\n",
       "      <th>goal_fat_3</th>\n",
       "      <th>goal_protein_3</th>\n",
       "      <th>goal_sodium_3</th>\n",
       "      <th>goal_sugar_3</th>\n",
       "      <th>foods_len_3</th>\n",
       "      <th>healtyDistrib_3</th>\n",
       "      <th>calories_diff_3</th>\n",
       "      <th>carbs_diff_3</th>\n",
       "      <th>fat_diff_3</th>\n",
       "      <th>protein_diff_3</th>\n",
       "      <th>sodium_diff_3</th>\n",
       "      <th>sugar_diff_3</th>\n",
       "      <th>total_calories_4</th>\n",
       "      <th>total_carbs_4</th>\n",
       "      <th>total_fat_4</th>\n",
       "      <th>total_protein_4</th>\n",
       "      <th>total_sodium_4</th>\n",
       "      <th>total_sugar_4</th>\n",
       "      <th>goal_calories_4</th>\n",
       "      <th>goal_carbs_4</th>\n",
       "      <th>goal_fat_4</th>\n",
       "      <th>goal_protein_4</th>\n",
       "      <th>goal_sodium_4</th>\n",
       "      <th>goal_sugar_4</th>\n",
       "      <th>foods_len_4</th>\n",
       "      <th>healtyDistrib_4</th>\n",
       "      <th>calories_diff_4</th>\n",
       "      <th>carbs_diff_4</th>\n",
       "      <th>fat_diff_4</th>\n",
       "      <th>protein_diff_4</th>\n",
       "      <th>sodium_diff_4</th>\n",
       "      <th>sugar_diff_4</th>\n",
       "      <th>total_calories_5</th>\n",
       "      <th>total_carbs_5</th>\n",
       "      <th>total_fat_5</th>\n",
       "      <th>total_protein_5</th>\n",
       "      <th>total_sodium_5</th>\n",
       "      <th>total_sugar_5</th>\n",
       "      <th>goal_calories_5</th>\n",
       "      <th>goal_carbs_5</th>\n",
       "      <th>goal_fat_5</th>\n",
       "      <th>goal_protein_5</th>\n",
       "      <th>goal_sodium_5</th>\n",
       "      <th>goal_sugar_5</th>\n",
       "      <th>foods_len_5</th>\n",
       "      <th>healtyDistrib_5</th>\n",
       "      <th>calories_diff_5</th>\n",
       "      <th>carbs_diff_5</th>\n",
       "      <th>fat_diff_5</th>\n",
       "      <th>protein_diff_5</th>\n",
       "      <th>sodium_diff_5</th>\n",
       "      <th>sugar_diff_5</th>\n",
       "      <th>total_calories_6</th>\n",
       "      <th>total_carbs_6</th>\n",
       "      <th>total_fat_6</th>\n",
       "      <th>total_protein_6</th>\n",
       "      <th>total_sodium_6</th>\n",
       "      <th>total_sugar_6</th>\n",
       "      <th>goal_calories_6</th>\n",
       "      <th>goal_carbs_6</th>\n",
       "      <th>goal_fat_6</th>\n",
       "      <th>goal_protein_6</th>\n",
       "      <th>goal_sodium_6</th>\n",
       "      <th>goal_sugar_6</th>\n",
       "      <th>foods_len_6</th>\n",
       "      <th>healtyDistrib_6</th>\n",
       "      <th>calories_diff_6</th>\n",
       "      <th>carbs_diff_6</th>\n",
       "      <th>fat_diff_6</th>\n",
       "      <th>protein_diff_6</th>\n",
       "      <th>sodium_diff_6</th>\n",
       "      <th>sugar_diff_6</th>\n",
       "      <th>total_calories_7</th>\n",
       "      <th>total_carbs_7</th>\n",
       "      <th>total_fat_7</th>\n",
       "      <th>total_protein_7</th>\n",
       "      <th>total_sodium_7</th>\n",
       "      <th>total_sugar_7</th>\n",
       "      <th>goal_calories_7</th>\n",
       "      <th>goal_carbs_7</th>\n",
       "      <th>goal_fat_7</th>\n",
       "      <th>goal_protein_7</th>\n",
       "      <th>goal_sodium_7</th>\n",
       "      <th>goal_sugar_7</th>\n",
       "      <th>foods_len_7</th>\n",
       "      <th>healtyDistrib_7</th>\n",
       "      <th>calories_diff_7</th>\n",
       "      <th>carbs_diff_7</th>\n",
       "      <th>fat_diff_7</th>\n",
       "      <th>protein_diff_7</th>\n",
       "      <th>sodium_diff_7</th>\n",
       "      <th>sugar_diff_7</th>\n",
       "      <th>total_calories_8</th>\n",
       "      <th>total_carbs_8</th>\n",
       "      <th>total_fat_8</th>\n",
       "      <th>total_protein_8</th>\n",
       "      <th>total_sodium_8</th>\n",
       "      <th>total_sugar_8</th>\n",
       "      <th>goal_calories_8</th>\n",
       "      <th>goal_carbs_8</th>\n",
       "      <th>goal_fat_8</th>\n",
       "      <th>goal_protein_8</th>\n",
       "      <th>goal_sodium_8</th>\n",
       "      <th>goal_sugar_8</th>\n",
       "      <th>foods_len_8</th>\n",
       "      <th>healtyDistrib_8</th>\n",
       "      <th>calories_diff_8</th>\n",
       "      <th>carbs_diff_8</th>\n",
       "      <th>fat_diff_8</th>\n",
       "      <th>protein_diff_8</th>\n",
       "      <th>sodium_diff_8</th>\n",
       "      <th>sugar_diff_8</th>\n",
       "      <th>total_calories_9</th>\n",
       "      <th>total_carbs_9</th>\n",
       "      <th>total_fat_9</th>\n",
       "      <th>total_protein_9</th>\n",
       "      <th>total_sodium_9</th>\n",
       "      <th>total_sugar_9</th>\n",
       "      <th>goal_calories_9</th>\n",
       "      <th>goal_carbs_9</th>\n",
       "      <th>goal_fat_9</th>\n",
       "      <th>goal_protein_9</th>\n",
       "      <th>goal_sodium_9</th>\n",
       "      <th>goal_sugar_9</th>\n",
       "      <th>foods_len_9</th>\n",
       "      <th>healtyDistrib_9</th>\n",
       "      <th>calories_diff_9</th>\n",
       "      <th>carbs_diff_9</th>\n",
       "      <th>fat_diff_9</th>\n",
       "      <th>protein_diff_9</th>\n",
       "      <th>sodium_diff_9</th>\n",
       "      <th>sugar_diff_9</th>\n",
       "      <th>logged_frequency</th>\n",
       "      <th>start_date</th>\n",
       "      <th>days_missed</th>\n",
       "      <th>is_180_diet</th>\n",
       "      <th>reach_goal</th>\n",
       "      <th>FoodGroup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.524046</td>\n",
       "      <td>0.168717</td>\n",
       "      <td>0.15812</td>\n",
       "      <td>0.159744</td>\n",
       "      <td>0.113894</td>\n",
       "      <td>0.01426</td>\n",
       "      <td>0.372187</td>\n",
       "      <td>0.317666</td>\n",
       "      <td>0.24186</td>\n",
       "      <td>0.21123</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.011132</td>\n",
       "      <td>0.067797</td>\n",
       "      <td>0.034141</td>\n",
       "      <td>0.363905</td>\n",
       "      <td>0.572824</td>\n",
       "      <td>0.531616</td>\n",
       "      <td>0.483384</td>\n",
       "      <td>0.680708</td>\n",
       "      <td>0.400831</td>\n",
       "      <td>0.401553</td>\n",
       "      <td>0.27768</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>0.364217</td>\n",
       "      <td>0.295058</td>\n",
       "      <td>0.022635</td>\n",
       "      <td>0.433783</td>\n",
       "      <td>0.371151</td>\n",
       "      <td>0.283721</td>\n",
       "      <td>0.245989</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.013019</td>\n",
       "      <td>0.084746</td>\n",
       "      <td>0.037289</td>\n",
       "      <td>0.470113</td>\n",
       "      <td>0.547069</td>\n",
       "      <td>0.512881</td>\n",
       "      <td>0.406344</td>\n",
       "      <td>0.558559</td>\n",
       "      <td>0.397626</td>\n",
       "      <td>0.485443</td>\n",
       "      <td>0.328647</td>\n",
       "      <td>0.25641</td>\n",
       "      <td>0.313099</td>\n",
       "      <td>0.235114</td>\n",
       "      <td>0.023766</td>\n",
       "      <td>0.398958</td>\n",
       "      <td>0.340357</td>\n",
       "      <td>0.260465</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.011887</td>\n",
       "      <td>0.101695</td>\n",
       "      <td>0.003663</td>\n",
       "      <td>0.40136</td>\n",
       "      <td>0.50444</td>\n",
       "      <td>0.487119</td>\n",
       "      <td>0.41994</td>\n",
       "      <td>0.598976</td>\n",
       "      <td>0.39632</td>\n",
       "      <td>0.431529</td>\n",
       "      <td>0.198594</td>\n",
       "      <td>0.346154</td>\n",
       "      <td>0.645367</td>\n",
       "      <td>0.146663</td>\n",
       "      <td>0.016071</td>\n",
       "      <td>0.378109</td>\n",
       "      <td>0.322528</td>\n",
       "      <td>0.246512</td>\n",
       "      <td>0.213904</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.011321</td>\n",
       "      <td>0.084746</td>\n",
       "      <td>0.227308</td>\n",
       "      <td>0.42214</td>\n",
       "      <td>0.560391</td>\n",
       "      <td>0.430913</td>\n",
       "      <td>0.255287</td>\n",
       "      <td>0.658613</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.465387</td>\n",
       "      <td>0.316344</td>\n",
       "      <td>0.380342</td>\n",
       "      <td>0.367412</td>\n",
       "      <td>0.266152</td>\n",
       "      <td>0.019013</td>\n",
       "      <td>0.376214</td>\n",
       "      <td>0.320908</td>\n",
       "      <td>0.246512</td>\n",
       "      <td>0.213904</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.011321</td>\n",
       "      <td>0.118644</td>\n",
       "      <td>0.108376</td>\n",
       "      <td>0.400975</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.412178</td>\n",
       "      <td>0.386707</td>\n",
       "      <td>0.578049</td>\n",
       "      <td>0.398457</td>\n",
       "      <td>0.580332</td>\n",
       "      <td>0.495606</td>\n",
       "      <td>0.393162</td>\n",
       "      <td>0.690096</td>\n",
       "      <td>0.349407</td>\n",
       "      <td>0.03033</td>\n",
       "      <td>0.668562</td>\n",
       "      <td>0.570502</td>\n",
       "      <td>0.432558</td>\n",
       "      <td>0.379679</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.169492</td>\n",
       "      <td>0.038462</td>\n",
       "      <td>0.490893</td>\n",
       "      <td>0.546181</td>\n",
       "      <td>0.498829</td>\n",
       "      <td>0.327795</td>\n",
       "      <td>0.521915</td>\n",
       "      <td>0.397982</td>\n",
       "      <td>0.544317</td>\n",
       "      <td>0.393673</td>\n",
       "      <td>0.264957</td>\n",
       "      <td>0.42492</td>\n",
       "      <td>0.34661</td>\n",
       "      <td>0.024898</td>\n",
       "      <td>0.513385</td>\n",
       "      <td>0.439222</td>\n",
       "      <td>0.334884</td>\n",
       "      <td>0.291444</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.015472</td>\n",
       "      <td>0.152542</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.428297</td>\n",
       "      <td>0.525755</td>\n",
       "      <td>0.519906</td>\n",
       "      <td>0.403323</td>\n",
       "      <td>0.523801</td>\n",
       "      <td>0.397982</td>\n",
       "      <td>0.470563</td>\n",
       "      <td>0.342707</td>\n",
       "      <td>0.316239</td>\n",
       "      <td>0.57508</td>\n",
       "      <td>0.200746</td>\n",
       "      <td>0.029199</td>\n",
       "      <td>0.509832</td>\n",
       "      <td>0.435981</td>\n",
       "      <td>0.330233</td>\n",
       "      <td>0.28877</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.015283</td>\n",
       "      <td>0.118644</td>\n",
       "      <td>0.069146</td>\n",
       "      <td>0.470241</td>\n",
       "      <td>0.549734</td>\n",
       "      <td>0.489461</td>\n",
       "      <td>0.330816</td>\n",
       "      <td>0.622148</td>\n",
       "      <td>0.395608</td>\n",
       "      <td>0.526849</td>\n",
       "      <td>0.376098</td>\n",
       "      <td>0.547009</td>\n",
       "      <td>0.469649</td>\n",
       "      <td>0.429199</td>\n",
       "      <td>0.023766</td>\n",
       "      <td>0.612651</td>\n",
       "      <td>0.523501</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.347594</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.018302</td>\n",
       "      <td>0.084746</td>\n",
       "      <td>0.164632</td>\n",
       "      <td>0.492432</td>\n",
       "      <td>0.580817</td>\n",
       "      <td>0.398126</td>\n",
       "      <td>0.413897</td>\n",
       "      <td>0.468116</td>\n",
       "      <td>0.400356</td>\n",
       "      <td>0.343972</td>\n",
       "      <td>0.224956</td>\n",
       "      <td>0.213675</td>\n",
       "      <td>0.683706</td>\n",
       "      <td>0.22459</td>\n",
       "      <td>0.009507</td>\n",
       "      <td>0.926321</td>\n",
       "      <td>0.790924</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.526738</td>\n",
       "      <td>0.418182</td>\n",
       "      <td>0.027736</td>\n",
       "      <td>0.118644</td>\n",
       "      <td>0.222476</td>\n",
       "      <td>0.771036</td>\n",
       "      <td>0.80373</td>\n",
       "      <td>0.681499</td>\n",
       "      <td>0.413897</td>\n",
       "      <td>0.606071</td>\n",
       "      <td>0.413769</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.142857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  total_calories  total_carbs  total_fat  total_protein  total_sodium  total_sugar  goal_calories  goal_carbs  goal_fat  goal_protein  goal_sodium  goal_sugar  foods_len  healtyDistrib  calories_diff  carbs_diff  fat_diff  protein_diff  sodium_diff  sugar_diff  total_calories_1  total_carbs_1  total_fat_1  total_protein_1  total_sodium_1  total_sugar_1  goal_calories_1  goal_carbs_1  goal_fat_1  goal_protein_1  goal_sodium_1  goal_sugar_1  foods_len_1  healtyDistrib_1  calories_diff_1  carbs_diff_1  fat_diff_1  protein_diff_1  sodium_diff_1  sugar_diff_1  total_calories_2  total_carbs_2  total_fat_2  total_protein_2  total_sodium_2  total_sugar_2  goal_calories_2  goal_carbs_2  goal_fat_2  goal_protein_2  goal_sodium_2  goal_sugar_2  foods_len_2  healtyDistrib_2  calories_diff_2  carbs_diff_2  fat_diff_2  protein_diff_2  sodium_diff_2  sugar_diff_2  total_calories_3  total_carbs_3  total_fat_3  total_protein_3  total_sodium_3  total_sugar_3  goal_calories_3  goal_carbs_3  \\\n",
       "0      1.0        0.524046     0.168717    0.15812       0.159744      0.113894      0.01426       0.372187    0.317666   0.24186       0.21123     0.418182    0.011132   0.067797       0.034141       0.363905    0.572824  0.531616      0.483384     0.680708    0.400831          0.401553        0.27768     0.230769         0.364217        0.295058       0.022635         0.433783      0.371151    0.283721        0.245989       0.418182      0.013019     0.084746         0.037289         0.470113      0.547069    0.512881        0.406344       0.558559      0.397626          0.485443       0.328647      0.25641         0.313099        0.235114       0.023766         0.398958      0.340357    0.260465        0.227273       0.418182      0.011887     0.101695         0.003663          0.40136       0.50444    0.487119         0.41994       0.598976       0.39632          0.431529       0.198594     0.346154         0.645367        0.146663       0.016071         0.378109      0.322528   \n",
       "\n",
       "   goal_fat_3  goal_protein_3  goal_sodium_3  goal_sugar_3  foods_len_3  healtyDistrib_3  calories_diff_3  carbs_diff_3  fat_diff_3  protein_diff_3  sodium_diff_3  sugar_diff_3  total_calories_4  total_carbs_4  total_fat_4  total_protein_4  total_sodium_4  total_sugar_4  goal_calories_4  goal_carbs_4  goal_fat_4  goal_protein_4  goal_sodium_4  goal_sugar_4  foods_len_4  healtyDistrib_4  calories_diff_4  carbs_diff_4  fat_diff_4  protein_diff_4  sodium_diff_4  sugar_diff_4  total_calories_5  total_carbs_5  total_fat_5  total_protein_5  total_sodium_5  total_sugar_5  goal_calories_5  goal_carbs_5  goal_fat_5  goal_protein_5  goal_sodium_5  goal_sugar_5  foods_len_5  healtyDistrib_5  calories_diff_5  carbs_diff_5  fat_diff_5  protein_diff_5  sodium_diff_5  sugar_diff_5  total_calories_6  total_carbs_6  total_fat_6  total_protein_6  total_sodium_6  total_sugar_6  goal_calories_6  goal_carbs_6  goal_fat_6  goal_protein_6  goal_sodium_6  goal_sugar_6  foods_len_6  healtyDistrib_6  \\\n",
       "0    0.246512        0.213904       0.418182      0.011321     0.084746         0.227308          0.42214      0.560391    0.430913        0.255287       0.658613           0.4          0.465387       0.316344     0.380342         0.367412        0.266152       0.019013         0.376214      0.320908    0.246512        0.213904       0.418182      0.011321     0.118644         0.108376         0.400975           0.5    0.412178        0.386707       0.578049      0.398457          0.580332       0.495606     0.393162         0.690096        0.349407        0.03033         0.668562      0.570502    0.432558        0.379679       0.418182          0.02     0.169492         0.038462         0.490893      0.546181    0.498829        0.327795       0.521915      0.397982          0.544317       0.393673     0.264957          0.42492         0.34661       0.024898         0.513385      0.439222    0.334884        0.291444       0.418182      0.015472     0.152542              0.0   \n",
       "\n",
       "   calories_diff_6  carbs_diff_6  fat_diff_6  protein_diff_6  sodium_diff_6  sugar_diff_6  total_calories_7  total_carbs_7  total_fat_7  total_protein_7  total_sodium_7  total_sugar_7  goal_calories_7  goal_carbs_7  goal_fat_7  goal_protein_7  goal_sodium_7  goal_sugar_7  foods_len_7  healtyDistrib_7  calories_diff_7  carbs_diff_7  fat_diff_7  protein_diff_7  sodium_diff_7  sugar_diff_7  total_calories_8  total_carbs_8  total_fat_8  total_protein_8  total_sodium_8  total_sugar_8  goal_calories_8  goal_carbs_8  goal_fat_8  goal_protein_8  goal_sodium_8  goal_sugar_8  foods_len_8  healtyDistrib_8  calories_diff_8  carbs_diff_8  fat_diff_8  protein_diff_8  sodium_diff_8  sugar_diff_8  total_calories_9  total_carbs_9  total_fat_9  total_protein_9  total_sodium_9  total_sugar_9  goal_calories_9  goal_carbs_9  goal_fat_9  goal_protein_9  goal_sodium_9  goal_sugar_9  foods_len_9  healtyDistrib_9  calories_diff_9  carbs_diff_9  fat_diff_9  protein_diff_9  sodium_diff_9  sugar_diff_9  \\\n",
       "0         0.428297      0.525755    0.519906        0.403323       0.523801      0.397982          0.470563       0.342707     0.316239          0.57508        0.200746       0.029199         0.509832      0.435981    0.330233         0.28877       0.418182      0.015283     0.118644         0.069146         0.470241      0.549734    0.489461        0.330816       0.622148      0.395608          0.526849       0.376098     0.547009         0.469649        0.429199       0.023766         0.612651      0.523501         0.4        0.347594       0.418182      0.018302     0.084746         0.164632         0.492432      0.580817    0.398126        0.413897       0.468116      0.400356          0.343972       0.224956     0.213675         0.683706         0.22459       0.009507         0.926321      0.790924         0.6        0.526738       0.418182      0.027736     0.118644         0.222476         0.771036       0.80373    0.681499        0.413897       0.606071      0.413769   \n",
       "\n",
       "   logged_frequency  start_date  days_missed  is_180_diet  reach_goal  FoodGroup  \n",
       "0             172.0         0.0          0.0          1.0         0.0   0.142857  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f'\\n Data shape - {data.shape} ')\n",
    "print(f' Unique users - {data[\"user_id\"].nunique()} \\n')\n",
    "data.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <span style=\"color:#FF7B07\"> Let's split data and drop some features which we should not use for modeling <br> \n",
    "- ##### <span style=\"color:#FF7B07\"> dropped goal: we already have feature _diff which is linear combination of total and goal nutritient\n",
    "- ##### <span style=\"color:#FF7B07\"> dropped user_id: it's a feature which identifies the user so we don't need it\n",
    "- ##### <span style=\"color:#FF7B07\"> dropped reach_goal: it's our output\n",
    "- ##### <span style=\"color:#FF7B07\"> dropped logged frequency: it's contains information about feature\n",
    "- ##### <span style=\"color:#FF7B07\"> dropped is_180_diet: this feature created for another model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_col = list(filter(lambda x: (\"goal\" in x) or (\"is_180_diet\" in x) or (\"user_id\" in x) or (\"reach_goal\" in x) or (\"logged_frequency\" in x), data.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop(columns=drop_col)\n",
    "y = data['reach_goal']\n",
    "X_train, X_test,y_train,y_test = train_test_split(X, y, test_size=0.3, random_state = 42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#FF7B07\"><div align=\"center\">**Balance Data** <a  name=\"2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> As we saw data is imbalanced so SMOTE algorithm is enough to handle this problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sm = SMOTE(random_state=42)\n",
    "\n",
    "X_train_s,y_train_s =sm.fit_sample(X_train,y_train)\n",
    "X_test_s,y_test_s =sm.fit_sample(X_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax  = plt.subplots(1,2,figsize = (15,5))\n",
    "sns.countplot(x = y_test,ax=ax[0],palette = 'bright',alpha=0.7,).set_title('Test data Before balancing')\n",
    "sns.countplot(x = y_test_s,ax=ax[1],palette = 'bright',alpha=0.7).set_title('Test data After balancing')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax  = plt.subplots(1,2,figsize = (15,5))\n",
    "sns.countplot(x = y_train,ax=ax[0],palette = 'bright',alpha=0.7).set_title('Train data Before balancing')\n",
    "sns.countplot(x = y_train_s,ax=ax[1],palette = 'bright',alpha=0.7).set_title('Train data After balancing')\n",
    "plt.show()\n",
    "\n",
    "X_train, y_train, X_test, y_test = X_train_s, y_train_s, X_test_s, y_test_s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#FF7B07\"><div align=\"center\">**Create & Test Model** <a  name=\"3\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> Before Create a model, let's check our features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>142</th>\n",
       "      <th>5</th>\n",
       "      <th>54</th>\n",
       "      <th>13</th>\n",
       "      <th>93</th>\n",
       "      <th>14</th>\n",
       "      <th>59</th>\n",
       "      <th>0</th>\n",
       "      <th>63</th>\n",
       "      <th>1</th>\n",
       "      <th>12</th>\n",
       "      <th>140</th>\n",
       "      <th>25</th>\n",
       "      <th>7</th>\n",
       "      <th>10</th>\n",
       "      <th>9</th>\n",
       "      <th>11</th>\n",
       "      <th>38</th>\n",
       "      <th>102</th>\n",
       "      <th>110</th>\n",
       "      <th>66</th>\n",
       "      <th>105</th>\n",
       "      <th>41</th>\n",
       "      <th>31</th>\n",
       "      <th>70</th>\n",
       "      <th>141</th>\n",
       "      <th>139</th>\n",
       "      <th>87</th>\n",
       "      <th>19</th>\n",
       "      <th>85</th>\n",
       "      <th>96</th>\n",
       "      <th>4</th>\n",
       "      <th>53</th>\n",
       "      <th>2</th>\n",
       "      <th>98</th>\n",
       "      <th>78</th>\n",
       "      <th>109</th>\n",
       "      <th>33</th>\n",
       "      <th>117</th>\n",
       "      <th>81</th>\n",
       "      <th>137</th>\n",
       "      <th>119</th>\n",
       "      <th>64</th>\n",
       "      <th>111</th>\n",
       "      <th>120</th>\n",
       "      <th>114</th>\n",
       "      <th>92</th>\n",
       "      <th>27</th>\n",
       "      <th>17</th>\n",
       "      <th>22</th>\n",
       "      <th>62</th>\n",
       "      <th>28</th>\n",
       "      <th>15</th>\n",
       "      <th>83</th>\n",
       "      <th>112</th>\n",
       "      <th>136</th>\n",
       "      <th>100</th>\n",
       "      <th>45</th>\n",
       "      <th>36</th>\n",
       "      <th>91</th>\n",
       "      <th>134</th>\n",
       "      <th>138</th>\n",
       "      <th>52</th>\n",
       "      <th>113</th>\n",
       "      <th>76</th>\n",
       "      <th>107</th>\n",
       "      <th>106</th>\n",
       "      <th>3</th>\n",
       "      <th>34</th>\n",
       "      <th>46</th>\n",
       "      <th>23</th>\n",
       "      <th>72</th>\n",
       "      <th>94</th>\n",
       "      <th>125</th>\n",
       "      <th>18</th>\n",
       "      <th>133</th>\n",
       "      <th>73</th>\n",
       "      <th>26</th>\n",
       "      <th>84</th>\n",
       "      <th>21</th>\n",
       "      <th>37</th>\n",
       "      <th>86</th>\n",
       "      <th>6</th>\n",
       "      <th>77</th>\n",
       "      <th>56</th>\n",
       "      <th>39</th>\n",
       "      <th>40</th>\n",
       "      <th>128</th>\n",
       "      <th>95</th>\n",
       "      <th>75</th>\n",
       "      <th>8</th>\n",
       "      <th>68</th>\n",
       "      <th>122</th>\n",
       "      <th>108</th>\n",
       "      <th>42</th>\n",
       "      <th>35</th>\n",
       "      <th>44</th>\n",
       "      <th>65</th>\n",
       "      <th>74</th>\n",
       "      <th>89</th>\n",
       "      <th>50</th>\n",
       "      <th>104</th>\n",
       "      <th>99</th>\n",
       "      <th>69</th>\n",
       "      <th>61</th>\n",
       "      <th>118</th>\n",
       "      <th>80</th>\n",
       "      <th>48</th>\n",
       "      <th>121</th>\n",
       "      <th>103</th>\n",
       "      <th>49</th>\n",
       "      <th>116</th>\n",
       "      <th>71</th>\n",
       "      <th>51</th>\n",
       "      <th>129</th>\n",
       "      <th>16</th>\n",
       "      <th>20</th>\n",
       "      <th>135</th>\n",
       "      <th>32</th>\n",
       "      <th>60</th>\n",
       "      <th>130</th>\n",
       "      <th>101</th>\n",
       "      <th>29</th>\n",
       "      <th>24</th>\n",
       "      <th>30</th>\n",
       "      <th>88</th>\n",
       "      <th>82</th>\n",
       "      <th>132</th>\n",
       "      <th>131</th>\n",
       "      <th>43</th>\n",
       "      <th>55</th>\n",
       "      <th>127</th>\n",
       "      <th>126</th>\n",
       "      <th>79</th>\n",
       "      <th>124</th>\n",
       "      <th>123</th>\n",
       "      <th>97</th>\n",
       "      <th>47</th>\n",
       "      <th>67</th>\n",
       "      <th>58</th>\n",
       "      <th>57</th>\n",
       "      <th>115</th>\n",
       "      <th>90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>feature</th>\n",
       "      <td>FoodGroup</td>\n",
       "      <td>total_sugar</td>\n",
       "      <td>sodium_diff_3</td>\n",
       "      <td>sugar_diff</td>\n",
       "      <td>carbs_diff_6</td>\n",
       "      <td>total_calories_1</td>\n",
       "      <td>total_protein_4</td>\n",
       "      <td>total_calories</td>\n",
       "      <td>healtyDistrib_4</td>\n",
       "      <td>total_carbs</td>\n",
       "      <td>sodium_diff</td>\n",
       "      <td>start_date</td>\n",
       "      <td>protein_diff_1</td>\n",
       "      <td>healtyDistrib</td>\n",
       "      <td>fat_diff</td>\n",
       "      <td>carbs_diff</td>\n",
       "      <td>protein_diff</td>\n",
       "      <td>fat_diff_2</td>\n",
       "      <td>total_sodium_7</td>\n",
       "      <td>sodium_diff_7</td>\n",
       "      <td>fat_diff_4</td>\n",
       "      <td>healtyDistrib_7</td>\n",
       "      <td>sugar_diff_2</td>\n",
       "      <td>total_protein_2</td>\n",
       "      <td>total_calories_5</td>\n",
       "      <td>days_missed</td>\n",
       "      <td>sugar_diff_9</td>\n",
       "      <td>total_protein_6</td>\n",
       "      <td>total_sugar_1</td>\n",
       "      <td>total_carbs_6</td>\n",
       "      <td>sodium_diff_6</td>\n",
       "      <td>total_sodium</td>\n",
       "      <td>protein_diff_3</td>\n",
       "      <td>total_fat</td>\n",
       "      <td>total_calories_7</td>\n",
       "      <td>calories_diff_5</td>\n",
       "      <td>protein_diff_7</td>\n",
       "      <td>total_sugar_2</td>\n",
       "      <td>total_sugar_8</td>\n",
       "      <td>protein_diff_5</td>\n",
       "      <td>protein_diff_9</td>\n",
       "      <td>healtyDistrib_8</td>\n",
       "      <td>calories_diff_4</td>\n",
       "      <td>sugar_diff_7</td>\n",
       "      <td>calories_diff_8</td>\n",
       "      <td>total_fat_8</td>\n",
       "      <td>calories_diff_6</td>\n",
       "      <td>sugar_diff_1</td>\n",
       "      <td>total_protein_1</td>\n",
       "      <td>calories_diff_1</td>\n",
       "      <td>foods_len_4</td>\n",
       "      <td>total_calories_2</td>\n",
       "      <td>total_carbs_1</td>\n",
       "      <td>sugar_diff_5</td>\n",
       "      <td>total_calories_8</td>\n",
       "      <td>fat_diff_9</td>\n",
       "      <td>total_fat_7</td>\n",
       "      <td>total_protein_3</td>\n",
       "      <td>calories_diff_2</td>\n",
       "      <td>healtyDistrib_6</td>\n",
       "      <td>calories_diff_9</td>\n",
       "      <td>sodium_diff_9</td>\n",
       "      <td>fat_diff_3</td>\n",
       "      <td>total_carbs_8</td>\n",
       "      <td>foods_len_5</td>\n",
       "      <td>carbs_diff_7</td>\n",
       "      <td>calories_diff_7</td>\n",
       "      <td>total_protein</td>\n",
       "      <td>foods_len_2</td>\n",
       "      <td>total_sodium_3</td>\n",
       "      <td>carbs_diff_1</td>\n",
       "      <td>total_fat_5</td>\n",
       "      <td>fat_diff_6</td>\n",
       "      <td>sugar_diff_8</td>\n",
       "      <td>total_sodium_1</td>\n",
       "      <td>healtyDistrib_9</td>\n",
       "      <td>total_protein_5</td>\n",
       "      <td>sodium_diff_1</td>\n",
       "      <td>total_calories_6</td>\n",
       "      <td>healtyDistrib_1</td>\n",
       "      <td>carbs_diff_2</td>\n",
       "      <td>total_fat_6</td>\n",
       "      <td>foods_len</td>\n",
       "      <td>healtyDistrib_5</td>\n",
       "      <td>total_calories_4</td>\n",
       "      <td>protein_diff_2</td>\n",
       "      <td>sodium_diff_2</td>\n",
       "      <td>total_fat_9</td>\n",
       "      <td>protein_diff_6</td>\n",
       "      <td>total_sugar_5</td>\n",
       "      <td>calories_diff</td>\n",
       "      <td>sodium_diff_4</td>\n",
       "      <td>fat_diff_8</td>\n",
       "      <td>fat_diff_7</td>\n",
       "      <td>total_calories_3</td>\n",
       "      <td>healtyDistrib_2</td>\n",
       "      <td>total_fat_3</td>\n",
       "      <td>carbs_diff_4</td>\n",
       "      <td>total_sodium_5</td>\n",
       "      <td>total_sugar_6</td>\n",
       "      <td>calories_diff_3</td>\n",
       "      <td>foods_len_7</td>\n",
       "      <td>total_carbs_7</td>\n",
       "      <td>sugar_diff_4</td>\n",
       "      <td>total_sugar_4</td>\n",
       "      <td>foods_len_8</td>\n",
       "      <td>fat_diff_5</td>\n",
       "      <td>foods_len_3</td>\n",
       "      <td>carbs_diff_8</td>\n",
       "      <td>total_sugar_7</td>\n",
       "      <td>healtyDistrib_3</td>\n",
       "      <td>total_sodium_8</td>\n",
       "      <td>total_carbs_5</td>\n",
       "      <td>carbs_diff_3</td>\n",
       "      <td>total_protein_9</td>\n",
       "      <td>total_fat_1</td>\n",
       "      <td>foods_len_1</td>\n",
       "      <td>carbs_diff_9</td>\n",
       "      <td>total_sodium_2</td>\n",
       "      <td>total_sodium_4</td>\n",
       "      <td>total_sodium_9</td>\n",
       "      <td>total_protein_7</td>\n",
       "      <td>total_carbs_2</td>\n",
       "      <td>fat_diff_1</td>\n",
       "      <td>total_fat_2</td>\n",
       "      <td>total_sodium_6</td>\n",
       "      <td>sodium_diff_5</td>\n",
       "      <td>foods_len_9</td>\n",
       "      <td>total_sugar_9</td>\n",
       "      <td>total_carbs_3</td>\n",
       "      <td>sugar_diff_3</td>\n",
       "      <td>total_carbs_9</td>\n",
       "      <td>total_calories_9</td>\n",
       "      <td>carbs_diff_5</td>\n",
       "      <td>sodium_diff_8</td>\n",
       "      <td>protein_diff_8</td>\n",
       "      <td>sugar_diff_6</td>\n",
       "      <td>total_sugar_3</td>\n",
       "      <td>protein_diff_4</td>\n",
       "      <td>total_fat_4</td>\n",
       "      <td>total_carbs_4</td>\n",
       "      <td>total_protein_8</td>\n",
       "      <td>foods_len_6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>importance</th>\n",
       "      <td>0.21211</td>\n",
       "      <td>0.0524344</td>\n",
       "      <td>0.0250898</td>\n",
       "      <td>0.0204777</td>\n",
       "      <td>0.0174353</td>\n",
       "      <td>0.015324</td>\n",
       "      <td>0.0153099</td>\n",
       "      <td>0.0150823</td>\n",
       "      <td>0.0146204</td>\n",
       "      <td>0.0141412</td>\n",
       "      <td>0.0135699</td>\n",
       "      <td>0.0129921</td>\n",
       "      <td>0.0121958</td>\n",
       "      <td>0.0119584</td>\n",
       "      <td>0.0117349</td>\n",
       "      <td>0.0116446</td>\n",
       "      <td>0.0115202</td>\n",
       "      <td>0.0114194</td>\n",
       "      <td>0.0109513</td>\n",
       "      <td>0.0102758</td>\n",
       "      <td>0.0101968</td>\n",
       "      <td>0.0101388</td>\n",
       "      <td>0.0099749</td>\n",
       "      <td>0.00972772</td>\n",
       "      <td>0.00962663</td>\n",
       "      <td>0.00929436</td>\n",
       "      <td>0.00907586</td>\n",
       "      <td>0.00900556</td>\n",
       "      <td>0.00897612</td>\n",
       "      <td>0.00896399</td>\n",
       "      <td>0.00880307</td>\n",
       "      <td>0.00850353</td>\n",
       "      <td>0.00833853</td>\n",
       "      <td>0.00831269</td>\n",
       "      <td>0.00825349</td>\n",
       "      <td>0.00800576</td>\n",
       "      <td>0.00797832</td>\n",
       "      <td>0.0078915</td>\n",
       "      <td>0.00776368</td>\n",
       "      <td>0.0076725</td>\n",
       "      <td>0.00766093</td>\n",
       "      <td>0.00746904</td>\n",
       "      <td>0.00745702</td>\n",
       "      <td>0.00743832</td>\n",
       "      <td>0.00731993</td>\n",
       "      <td>0.00731561</td>\n",
       "      <td>0.00725344</td>\n",
       "      <td>0.00724142</td>\n",
       "      <td>0.00719887</td>\n",
       "      <td>0.00716225</td>\n",
       "      <td>0.00713378</td>\n",
       "      <td>0.00708317</td>\n",
       "      <td>0.00706735</td>\n",
       "      <td>0.00693661</td>\n",
       "      <td>0.00683771</td>\n",
       "      <td>0.00653241</td>\n",
       "      <td>0.00649214</td>\n",
       "      <td>0.00647017</td>\n",
       "      <td>0.00579482</td>\n",
       "      <td>0.0052052</td>\n",
       "      <td>0.00501292</td>\n",
       "      <td>0.00470538</td>\n",
       "      <td>0.00469788</td>\n",
       "      <td>0.00468711</td>\n",
       "      <td>0.00457517</td>\n",
       "      <td>0.00452758</td>\n",
       "      <td>0.00450801</td>\n",
       "      <td>0.00444642</td>\n",
       "      <td>0.00440492</td>\n",
       "      <td>0.00426337</td>\n",
       "      <td>0.00417666</td>\n",
       "      <td>0.00413745</td>\n",
       "      <td>0.00412099</td>\n",
       "      <td>0.00399985</td>\n",
       "      <td>0.00370855</td>\n",
       "      <td>0.00362619</td>\n",
       "      <td>0.00357902</td>\n",
       "      <td>0.00356419</td>\n",
       "      <td>0.00353635</td>\n",
       "      <td>0.00350598</td>\n",
       "      <td>0.0034904</td>\n",
       "      <td>0.00344337</td>\n",
       "      <td>0.00344086</td>\n",
       "      <td>0.00341593</td>\n",
       "      <td>0.00336219</td>\n",
       "      <td>0.00314847</td>\n",
       "      <td>0.00314136</td>\n",
       "      <td>0.00310963</td>\n",
       "      <td>0.00288503</td>\n",
       "      <td>0.00259841</td>\n",
       "      <td>0.00247658</td>\n",
       "      <td>0.00236083</td>\n",
       "      <td>0.00235602</td>\n",
       "      <td>0.00229403</td>\n",
       "      <td>0.00224663</td>\n",
       "      <td>0.00223857</td>\n",
       "      <td>0.00223307</td>\n",
       "      <td>0.00221216</td>\n",
       "      <td>0.00203923</td>\n",
       "      <td>0.00196335</td>\n",
       "      <td>0.00196335</td>\n",
       "      <td>0.00196335</td>\n",
       "      <td>0.0019518</td>\n",
       "      <td>0.00158135</td>\n",
       "      <td>0.00157068</td>\n",
       "      <td>0.0013089</td>\n",
       "      <td>0.00126042</td>\n",
       "      <td>0.00116794</td>\n",
       "      <td>0.00116202</td>\n",
       "      <td>0.00114529</td>\n",
       "      <td>0.00113008</td>\n",
       "      <td>0.0011049</td>\n",
       "      <td>0.00104712</td>\n",
       "      <td>0.000981675</td>\n",
       "      <td>0.000981675</td>\n",
       "      <td>0.000981675</td>\n",
       "      <td>0.0008726</td>\n",
       "      <td>0.0008726</td>\n",
       "      <td>0.00065445</td>\n",
       "      <td>0.000631487</td>\n",
       "      <td>0.000628272</td>\n",
       "      <td>0.000627068</td>\n",
       "      <td>0.000310444</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  142          5              54          13            93                14               59              0                63           1            12          140             25             7          10          9             11          38              102            110         66               105           41               31                70           141           139              87             19             85             96            4               53          2                 98               78              109            33             117             81              137              119              64            111              120          114              92            27               17               22           62                28             15            83                112         136          100              45               36               91               134            138         52             113          76            107  \\\n",
       "feature     FoodGroup  total_sugar  sodium_diff_3  sugar_diff  carbs_diff_6  total_calories_1  total_protein_4  total_calories  healtyDistrib_4  total_carbs  sodium_diff  start_date  protein_diff_1  healtyDistrib   fat_diff  carbs_diff  protein_diff  fat_diff_2  total_sodium_7  sodium_diff_7  fat_diff_4  healtyDistrib_7  sugar_diff_2  total_protein_2  total_calories_5  days_missed  sugar_diff_9  total_protein_6  total_sugar_1  total_carbs_6  sodium_diff_6  total_sodium  protein_diff_3   total_fat  total_calories_7  calories_diff_5  protein_diff_7  total_sugar_2  total_sugar_8  protein_diff_5  protein_diff_9  healtyDistrib_8  calories_diff_4  sugar_diff_7  calories_diff_8  total_fat_8  calories_diff_6  sugar_diff_1  total_protein_1  calories_diff_1  foods_len_4  total_calories_2  total_carbs_1  sugar_diff_5  total_calories_8  fat_diff_9  total_fat_7  total_protein_3  calories_diff_2  healtyDistrib_6  calories_diff_9  sodium_diff_9  fat_diff_3  total_carbs_8  foods_len_5  carbs_diff_7   \n",
       "importance    0.21211    0.0524344      0.0250898   0.0204777     0.0174353          0.015324        0.0153099       0.0150823        0.0146204    0.0141412    0.0135699   0.0129921       0.0121958      0.0119584  0.0117349   0.0116446     0.0115202   0.0114194       0.0109513      0.0102758   0.0101968        0.0101388     0.0099749       0.00972772        0.00962663   0.00929436    0.00907586       0.00900556     0.00897612     0.00896399     0.00880307    0.00850353      0.00833853  0.00831269        0.00825349       0.00800576      0.00797832      0.0078915     0.00776368       0.0076725      0.00766093       0.00746904       0.00745702    0.00743832       0.00731993   0.00731561       0.00725344    0.00724142       0.00719887       0.00716225   0.00713378        0.00708317     0.00706735    0.00693661        0.00683771  0.00653241   0.00649214       0.00647017       0.00579482        0.0052052       0.00501292     0.00470538  0.00469788     0.00468711   0.00457517    0.00452758   \n",
       "\n",
       "                        106            3            34              46            23           72          94            125             18               133              73             26                84               21            37           86          6                77                56              39             40           128             95             75             8              68          122         108               42               35           44            65              74             89               50           104            99            69             61           118         80           48            121            103              49              116            71            51               129          16           20            135             32              60              130              101            29          24           30              88             82           132            131            43            55             127  \\\n",
       "feature     calories_diff_7  total_protein  foods_len_2  total_sodium_3  carbs_diff_1  total_fat_5  fat_diff_6  sugar_diff_8  total_sodium_1  healtyDistrib_9  total_protein_5  sodium_diff_1  total_calories_6  healtyDistrib_1  carbs_diff_2  total_fat_6   foods_len  healtyDistrib_5  total_calories_4  protein_diff_2  sodium_diff_2  total_fat_9  protein_diff_6  total_sugar_5  calories_diff  sodium_diff_4  fat_diff_8  fat_diff_7  total_calories_3  healtyDistrib_2  total_fat_3  carbs_diff_4  total_sodium_5  total_sugar_6  calories_diff_3  foods_len_7  total_carbs_7  sugar_diff_4  total_sugar_4  foods_len_8  fat_diff_5  foods_len_3  carbs_diff_8  total_sugar_7  healtyDistrib_3  total_sodium_8  total_carbs_5  carbs_diff_3  total_protein_9  total_fat_1  foods_len_1  carbs_diff_9  total_sodium_2  total_sodium_4  total_sodium_9  total_protein_7  total_carbs_2  fat_diff_1  total_fat_2  total_sodium_6  sodium_diff_5  foods_len_9  total_sugar_9  total_carbs_3  sugar_diff_3  total_carbs_9   \n",
       "importance       0.00450801     0.00444642   0.00440492      0.00426337    0.00417666   0.00413745  0.00412099    0.00399985      0.00370855       0.00362619       0.00357902     0.00356419        0.00353635       0.00350598     0.0034904   0.00344337  0.00344086       0.00341593        0.00336219      0.00314847     0.00314136   0.00310963      0.00288503     0.00259841     0.00247658     0.00236083  0.00235602  0.00229403        0.00224663       0.00223857   0.00223307    0.00221216      0.00203923     0.00196335       0.00196335   0.00196335      0.0019518    0.00158135     0.00157068    0.0013089  0.00126042   0.00116794    0.00116202     0.00114529       0.00113008       0.0011049     0.00104712   0.000981675      0.000981675  0.000981675    0.0008726     0.0008726      0.00065445     0.000631487     0.000628272      0.000627068    0.000310444           0            0               0              0            0              0              0             0              0   \n",
       "\n",
       "                         126           79             124             123           97             47              67           58             57               115          90   \n",
       "feature     total_calories_9  carbs_diff_5  sodium_diff_8  protein_diff_8  sugar_diff_6  total_sugar_3  protein_diff_4  total_fat_4  total_carbs_4  total_protein_8  foods_len_6  \n",
       "importance                 0             0              0               0             0              0               0            0              0                0            0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = DecisionTreeRegressor()\n",
    "model.fit(X_train, y_train)\n",
    "importance = model.feature_importances_\n",
    "importance_df = pd.DataFrame(columns=['feature','importance'])\n",
    "importance_df['feature'] = X_train.columns\n",
    "importance_df['importance'] = importance\n",
    "importance_df.sort_values(by=['importance'],ascending = False).T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> As you see the most important feature is the FoodGroup <br> It should be noted that we have many features and need to drop some of them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "matrix = data[['total_carbs', 'total_fat', 'total_protein', 'total_sodium', 'total_sugar', 'foods_len', \n",
    "          'healtyDistrib', 'calories_diff', 'carbs_diff', 'fat_diff', 'protein_diff', 'sodium_diff', 'sugar_diff', \n",
    "          'start_date', 'FoodGroup']].corr()\n",
    "f, ax = plt.subplots(figsize=(12, 6))\n",
    "with sns.axes_style(\"white\"):\n",
    "    sns.heatmap(matrix,mask=np.triu(matrix,1),annot=True,fmt=\".2f\", vmax=.8,cbar=False,cmap=\"coolwarm\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> Heatmap is not enough in this case because we have a lot of features <br> But what we can see it that calories and carbs are depended on each other so we may drop one of them"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> firstly create baseline model and check metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def classification_metrics(yTrueTrain,yPredictTrain,yTrueTest,yPredictTest,heatmap=False)->None:\n",
    "    \"\"\"\n",
    "    this function prints accuracy, precision, recall, F1 scre \n",
    "    and create confusion matrix  heatmap for both train and test sets\n",
    "    \n",
    "    Arguments:\n",
    "    yTrueTrain -- the true value of prediction from the train set\n",
    "    yPredictTrain -- predicted value from the train set\n",
    "    yTrueTest -- he true value of prediction from the test set\n",
    "    yPredictTest -- predicted value from the test set\n",
    "    heatmap -- boolean which tells us if plot heatmap or not\n",
    "    \n",
    "    Returns:\n",
    "    None\n",
    "    \"\"\"\n",
    "    print(\"train data:\\t  \"+ \"\\t\"*6+ \"test data:\\t\\n\")\n",
    "    print((\"accuracy:\\t {0} \"+ \"\\t\"*6+ \"accuracy:\\t {1}\").format(accuracy_score(yTrueTrain, yPredictTrain).round(2), \n",
    "                                                                 accuracy_score(yTrueTest, yPredictTest).round(2)))\n",
    "          \n",
    "    print((\"precision:\\t {0} \"+ \"\\t\"*6+ \"precision:\\t {1}\").format(precision_score(yTrueTrain, yPredictTrain).round(2), \n",
    "                                                                   precision_score(yTrueTest, yPredictTest).round(2)))\n",
    "    \n",
    "    print((\"recall:\\t\\t {0} \"+ \"\\t\"*6+ \"recall:\\t\\t {1}\").format(recall_score(yTrueTrain, yPredictTrain).round(2), \n",
    "                                                                 recall_score(yTrueTest, yPredictTest).round(2)))\n",
    "    \n",
    "    print((\"F1:\\t\\t {0} \"+ \"\\t\"*6+ \"F1:\\t\\t {1}\").format(f1_score(yTrueTrain, yPredictTrain).round(2), \n",
    "                                                         f1_score(yTrueTest, yPredictTest).round(2)))\n",
    "    if(heatmap):\n",
    "        f, ax  = plt.subplots(1,2,figsize = (18,6))\n",
    "        sns.heatmap(confusion_matrix(yTrueTrain,yPredictTrain),cmap='coolwarm',annot=True,ax=ax[0])\n",
    "        sns.heatmap(confusion_matrix(yTrueTest,yPredictTest),cmap='coolwarm',annot=True,ax=ax[1])\n",
    "        plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "decision_tree = DecisionTreeClassifier(max_depth=3,random_state=42)\n",
    "decision_tree.fit(X_train, y_train)\n",
    "\n",
    "y_pred_train = decision_tree.predict(X_train)\n",
    "y_pred_test = decision_tree.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train data:\t  \t\t\t\t\t\ttest data:\t\n",
      "\n",
      "accuracy:\t 0.75 \t\t\t\t\t\taccuracy:\t 0.74\n",
      "precision:\t 0.81 \t\t\t\t\t\tprecision:\t 0.79\n",
      "recall:\t\t 0.64 \t\t\t\t\t\trecall:\t\t 0.65\n",
      "F1:\t\t 0.72 \t\t\t\t\t\tF1:\t\t 0.71\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABNcAAAGGCAYAAABYAWfRAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAA+9UlEQVR4nO3debxXVb3/8dfnHEaRUQURcAw1MWfN0tTrkGYmltnFMr1llwa92fQrqW42Ud4GbdQb5dRghllXspzN67UcclZEFMUUQUABmadz1u+PvdUvejgHD1++Z7t4PR+P/eD7Xd+1px6hbz97rbUjpYQkSZIkSZKk166pqy9AkiRJkiRJer2yuCZJkiRJkiR1ksU1SZIkSZIkqZMsrkmSJEmSJEmdZHFNkiRJkiRJ6iSLa5IkSZIkSVInddvQJ/hz953Shj6HpK717aMmdPUlSNrAbv3TwdFV565Xlnjnqqlddg85MuNJeTPfSRsHM159OHJNkiRJkiRJ6qQNPnJNkiRpfUT3Ln8YKUmSpDrLKeNZXJMkSZXW1C2f4CVJkqRCThnPaaGSJEmSJElSJzlyTZIkVVp091mgJElSbnLKeBbXJElSpeU0ZUCSJEmFnDKexTVJklRpOS12K0mSpEJOGS+fMXiSJEmSJElSgzlyTZIkVVpOUwYkSZJUyCnjWVyTJEmVltOUAUmSJBVyynhOC5UkSZIkSZI6yZFrkiSp0nKaMiBJkqRCThnP4pokSaq0aM4neEmSJKmQU8azuCZJkiqtKaPgJUmSpEJOGc811yRJkiRJkqROcuSaJEmqtGjK56mmJEmSCjllPItrkiSp0qLZgfaSJEm5ySnj5XMnkiRJkiRJUoM5ck2SJFVaTovdSpIkqZBTxrO4JkmSKi2n9TgkSZJUyCnjWVyTJEmVltNTTUmSJBVyyniuuSZJkiRJkiR1kiPXJElSpUVGTzUlSZJUyCnjWVyTJEmVFk0OtJckScpNThkvnzuRJEmSJEmSGsyRa5IkqdJyepOUJEmSCjllPItrkiSp0nJ6k5QkSZIKOWU8i2uSJKnScnqqKUmSpEJOGc811yRJkiRJkqROsrgmSZIqLZqa6rJ1eJ6ICyNiTkQ8VNP23Yh4JCIeiIg/RsSAmt/GRcS0iJgaEUfWtO8dEQ+Wv/0oIvJ5LCtJklQnjcp4jVCNq5AkSVqLaIq6bOvgYuCoV7RdD+yaUtoNeBQYBxARuwBjgFHlPudFRHO5z/nAWGBkub3ymJIkSRu9Bma8Dc7imiRJEpBSugWY94q261JKq8uvtwPDy8+jgctSSitSStOBacB+ETEU6JdSui2llIBfAsc15AYkSZLUJXyhgSRJqrQKvUnqw8Dvys/DKIptL5pRtq0qP7+yXZIkSTUqlPHWm8U1SZJUafUa7h8RYymma75oQkppwjru+yVgNfCbF5va6JbaaZckSVKNqkzprAeLa5IkaaNQFtLWqZhWKyJOAY4BDiunekIxIm1ETbfhwMyyfXgb7ZIkScqUxTVJklRpXfkWqIg4CvgCcHBKaWnNT5OASyPiHGArihcX3JlSaomIRRGxP3AHcDLw40ZftyRJUtVV5U2f9WBxTZIkVVqjpgxExG+BQ4DNI2IGcBbF20F7AtdHBMDtKaWPpZQmR8RE4GGK6aKnpZRaykN9nOLNo72Bq8tNkiRJNRo5LTQingQWAS3A6pTSPhExiGI93W2BJ4H3pZTml/3HAaeW/T+ZUrq2veNbXJMkSZXWqOCVUjqxjeYL2uk/HhjfRvtdwK51vDRJkqTsdMGaa/+SUnqu5vuZwI0ppbMj4szy+xciYhdgDDCKYobCDRGxY82D1FfJZwyeJEmSJEmStG5GA5eUny8BjqtpvyyltCKlNB2YBuzX3oEcuSZJkiotpzdJSZIkqdDgjJeA6yIiAT8rX3Q1JKU0CyClNCsiBpd9hwG31+w7o2xbK4trkiSp0nJa7FaSJEmFemW8iBgLjK1pmlAWz2odkFKaWRbQro+IR9o7ZBttqY22l1hckyRJkiRJ0utSWUh7ZTHtlX1mln/OiYg/UkzznB0RQ8tRa0OBOWX3GcCImt2HAzPbO76PgiVJUqU1NUddNkmSJFVHozJeRPSJiL4vfgbeDjwETAJOKbudAlxZfp4EjImInhGxHTASuLO9czhyTZIkVZprrkmSJOWngRlvCPDHiICiDnZpSumaiPgHMDEiTgWeAk4ASClNjoiJwMPAauC09t4U+uJBJUmSKss11yRJkvLTqIyXUnoC2L2N9ueBw9ayz3hg/Lqew7QqSZIkSZIkdZIj1yRJUqU5LVSSJCk/OWU8i2uSJKnScgpekiRJKuSU8ZwWKkmSJEmSJHWSI9ckSVKl+UIDSZKk/OSU8SyuSZKkSstpyoAkSZIKOWU8i2uSJKnScnqqKUmSpEJOGS+fO5EkSZIkSZIazJFrkiSp2iKfKQOSJEkqZZTxLK5JkqRKy2k9DkmSJBVyynhOC5UkSZIkSZI6yZFrkiSp0nJa7FaSJEmFnDKexTVJklRpOU0ZkCRJUiGnjGdxTZIkVVpOTzUlSZJUyCnj5XMnkiRJkiRJUoM5ck2SJFVaTlMGJEmSVMgp41lckyRJlZZT8JIkSVIhp4zntFBJkiRJkiSpkxy5JkmSqi2jxW4lSZJUyijjWVyTJEmVFpHPlAFJkiQVcsp4FtckSVKl5fSadkmSJBVyynj53IkkSZIkSZLUYI5ckyRJlZbTm6QkSZJUyCnjWVyTJEnVltGUAUmSJJUyynj53IkkSZIkSZLUYI5ckyRJlZbTlAFJkiQVcsp4FtckSVKlRTjQXpIkKTc5ZTyLa5IkqdoyeqopSZKkUkYZL58yoSRJkiRJktRgjlyTJEmVFhm9SUqSJEmFnDKexTVJklRpOS12K0mSpEJOGS+fMqEkSZIkSZLUYI5ckyRJ1ZbRm6QkSZJUyijj5XMnkiQpS9EUddkkSZJUHY3MeBHRHBH3RsRV5fevRsQzEXFfuR1d03dcREyLiKkRceS6HN+Ra5IkqdoyWuxWkiRJpcZmvDOAKUC/mrZzU0rfq+0UEbsAY4BRwFbADRGxY0qppb2Dm1YlSZIkSZKUpYgYDrwT+MU6dB8NXJZSWpFSmg5MA/braCeLa5IkqdIioi6bJEmSqqOBGe8HwOeB1le0nx4RD0TEhRExsGwbBjxd02dG2dYui2uSJKnamprqs0mSJKk66pTxImJsRNxVs4198RQRcQwwJ6V09yvOfj6wA7AHMAv4/ou7tHGlqaNbcc01SZIkSZIkvS6llCYAE9by8wHAseULC3oB/SLi1ymlk17sEBE/B64qv84ARtTsPxyY2dE1WFwTu/38Www++hBWznmeW/Z816t+H/Kuw9jxa2eQWltJq1t4+LPfYv7fXln0fW2aenRn94u+Q/+9RrFy3gLuff+nWfbPZ+i99VbsffmPobmZpm7dePK8X/PUhMvW61zSxm7w5j358qd3ZtDA7qQEk66ZxeV/emaNPge+eTM+8oFtSQlaWhI/+sU0Hnh44Xqdt3u34Muf2ZmddujLwkWr+Mp3HubZOSt4w3Z9+NwndqTPJs20tCR+OfEpbrp17nqdS3nzTZ9S5/zLYzeyevESUkuR4f62//Fr/D7ooP3Y5w/nsfTJGQA8+8frmTb+p+t1zrVlvH6778yuP/kq3fpuSmptZdq3z2fW5Vev17mkjd24T+7IW/fdjPkvrOLk0+961e9HHDyYDxxf1AiWLW/h++c9xrQnl6zXOc13qqdGZLyU0jhgHEBEHAJ8LqV0UkQMTSnNKru9G3io/DwJuDQizqF4ocFI4M6OzmNxTcy45A88ed6v2ePC/2rz9+duuo3Zf7oRgL5v2om9Lv0B//umd6zTsXtvM4zdL/g2tx9+8hrtIz58AqsWLOTmN76doe87mp2/9Tnu/cCnWT5rLn9/2xhaV66iuc8mHHTfn5j9p5tYMWvO+t2ktBFraUn85MLHefTxxfTu3cyF5+7FP+6bz5NPL32pz933z+fWO54HYIdt+/D1L+zCBz7+j3U6/paDe/KlT+3Mf3zx/jXaj3n7UBYtXs2Yj97JYW/bgo//2/ac9Z0prFjRyjfPeYQZs5ax2aAeXHDuXtx57zwWL2n3BTzamIVTOqXOuv3wU1j1/Py1/j7v1ru467iPvebjvtaM17J0Ofd96AssnfZPeg4dzIF3XMHc625l9QuLXvO5JRX+cuNsrvjzTL786Z3b/H3W7OX8x7j7WbRkNfvvPYjPn74jYz937zod23ynhujajPediNiDYsrnk8BHAVJKkyNiIvAwsBo4raM3hcI6FNciYmeKtyUMK086E5iUUprSyRtQxcy79S56b7P29flalrz8H+DNfXpDenm68bD3H8u2p3+Q6NGdBXfez0Onfw1aX7lG4KsNedehPPqNnwDw7BXXsusPvwJAWrXqpcnMTT17EK6RI6235+ev5Pn5KwFYtqyFJ59eyuab9VyjuLZs+ct/b3v1bCbV/D1/+yGDee+7htG9WxMPP7qQ75//2Lr8NefAN2/GhZf+E4Cb/zaXT39sJABPz1z28rXNW8mCF1YxoF8PFi9Z1uZxJBy5tkGY8dSeeme8JY89+VKfFbPmsHLuPHpsMcjimrQe7p/8AlsO7rnW3x965OVZCJMfWcgWm7/c13ynSmhwxksp3QzcXH7+YDv9xgPjX8ux261cRMQXgMsoFnS7E/hH+fm3EXHmazmRXt+GjD6cgx+8mn2v/Bn3j/0iAJvuvD1DT3gHfz/oRG7d5zhoaWXY+189rbQtvbYawvKnixGYqaWFVS8sovtmxcs5eg3fkrfdM4nDpt/M49/7uaPWpDracnBPdtxhUx6e+uopnwftvxm/OX9fvnvWrnz7h48CsM3wTTjsbYP5+Ofv40Nn3E1ra+LtBw9Zp3NtsVlP5jy3HICWVliyZDX9+635TOeNI/vSrVvwzLMGL6mRzHgbiQRvvvoCDrzjCkZ85H1tdhm4/x687e4r2fdPP2fTXd4AbLiM96L++76Jpu7dWfr4U52/N0mvyTFv35Lb754HmO+kDaGjkWunAqNSSqtqG8u5p5OBszfUhalaZl95A7OvvIFBB+7DTl89gzuO+hCbHfoW+u+1Kwfc/nsAmnv1YsWcYlrZ3pf/hN7bDaepe3d6bz2UA+/6HwCe/PEvmXHJH6Ct1+WWI2WWz3iW/9vrWHoOHcw+V/yUWVdcy8ryuJI6r3evJsaPG8UPf/44S5e9emTzLbc/zy23P8/uo/rz7ydty6f+8wH23n0AO+2wKb84Zy8AevZoYv6C4l8J3/riKIYO6UW3bsGQLXpx0Q/3BuDySTP4y42z2/trDsBmA3vwn5/ZmfE/eGSNdumVwmmhG4IZbyPw94NPZMWsOfTYYhBvvuYiljzyBPNufXldpoX3TuamHQ6lZclStjjqIPb5/U+5eZcjN1jGA+i55RbscdF3uf/UL+A//KXG2PNNA3jnEVvyiS/cB2C+U2XklPE6Kq61Uizg9s9XtA8tf2tT+drTsQCnNw3mqKYB63GJqpJ5t97FJttvTffNBhIRzPjVH5n65XNe1e/uE04H1r4ex/JnnqXXiKEsf2Y20dxM9/59WTVvwRp9Vsyaw6KHH2PQgfvw7B+u3WD3JG0MmpuDb44bxXU3z+GW255rt+/9k19gq6G96N+vGxFw9U2z+dkvp7+q3xe/NRlY+5occ55bweDNezH3+ZU0N0GfPt1YuGg1AJv0buY7Z+3Kz389nclTnRKkDjgtdEMw420EXhz9v3LuPJ79n+sZsO9uaxTXVi96eWHzudfcQvz4rA2a8br17cO+k37G1LN+wII77n/loSVtADts24cz/2NHPvfVB1/KYeY7VUZGGa+jMuGngBsj4uqImFBu1wA3AmesbaeU0oSU0j4ppX0MXa9/m+yw9Uuf++25C009urPq+fk8d9NtDH3PkfTYYhAA3Qf2p/fWW63TMWdfdRPDP/huALY8/kie++vtAPQaNoSmXsVaAN0G9GPgW/ZiyaOv/oe+pNdm3Cd35J9PL+V3V85o8/dhQ3u99HnHHTale7cmXli4mrvvX8AhB2zOgP7dAei7aTeGbLH2tT1q/e2O53nHYcUUg0MO2IJ7HigW1O7WLfjWl0ZxzU2z+evf2i/0SdpgPoUZL2vNm/SmedM+L33e4ogDWDT5sTX69Byy+Uuf++/7JqKpaYNlvOjenb1//1Nm/PpKnr3imvW+P0kdG7JFT8aPG8U3znlkjTXRzHdS/bU7ci2ldE1E7AjsR7HYbQAzgH+sy9sS9Pqwx6++z2YH70ePzQdy6PT/5bGv/5joXvxf46kJl7Hlu49k+EmjaV29mtZly7nnA58GYPGUx5l61g/Y7+oLiaYm0qpVPPTJr7PsqZkdnvPpC3/PHhd/l0OmXMeq+S+8dMxNd96BN373zGJscQRPnHshix56dMPdvLQR2G2Xfhx16JZMm774paH9P/vl9JdC1JXXzOKQt27BUYcOYfXqxIqVrZz1nYcBePLppfz8V09y7td3I6J48+g5//0Ys+eu6PC8V10/i//8zBu57Gf7sXDxKr76nWKN9EMP3II9RvWnf9/uHH3YlgCM/8EjTJu+fq+GV758uU39mfHy12PIZuzz+58CEM3NzLzsKuZe939sPXYMUGa8449km7EnklpaaFm2nHtP+gywYTLeVie8g0Fv24fumw1g+MlF8e2BU89k4f2PbIjblzYKX/3cG9njTf0Z0K87f7hofy649Em6NRcjga68Zhb/NmYb+vfrxmc/Xrx0oKUl8ZHP3GO+U2XklPEibeCJ0H/uvpMzraXMffuoCV19CZI2sFv/dHCXjdtfeuFZdckSm3z4a/nMPagAM56UN/OdtHEw49VHR2uuSZIkda2MnmpKkiSplFHGy+dOJEmSJEmSpAZz5JokSaq26PKR/pIkSaq3jDKeI9ckSVKlRVNTXbYOzxNxYUTMiYiHatoGRcT1EfFY+efAmt/GRcS0iJgaEUfWtO8dEQ+Wv/0oIqPkKEmSVCeNyniNUI2rkCRJ6noXA0e9ou1M4MaU0kjgxvI7EbELMAYYVe5zXkQ0l/ucD4wFRpbbK48pSZKkjFhckyRJ1RZN9dk6kFK6BZj3iubRwCXl50uA42raL0sprUgpTQemAftFxFCgX0rptlS8kv2XNftIkiTpRQ3KeI3gmmuSJKnamrp0VuWQlNIsgJTSrIgYXLYPA26v6TejbFtVfn5luyRJkmp1bcarK4trkiSp0qJOTyQjYizFdM0XTUgpTejs4dpoS+20S5IkqUa9Ml4VWFyTJEkbhbKQ9lqLabMjYmg5am0oMKdsnwGMqOk3HJhZtg9vo12SJEmZyqdMKEmS8tQU9dk6ZxJwSvn5FODKmvYxEdEzIrajeHHBneUU0kURsX/5ltCTa/aRJEnSi7o249WVI9ckSVK1NWjKQET8FjgE2DwiZgBnAWcDEyPiVOAp4ASAlNLkiJgIPAysBk5LKbWUh/o4xZtHewNXl5skSZJqOS1UkiQpLymlE9fy02Fr6T8eGN9G+13ArnW8NEmSJFWYxTVJklRtUY3h/pIkSaqjjDKexTVJklRtTflMGZAkSVIpo4xncU2SJFVbRutxSJIkqZRRxsvnTiRJkiRJkqQGc+SaJEmqtoq8Yl2SJEl1lFHGs7gmSZKqLaMpA5IkSSpllPHyuRNJkiRJkiSpwRy5JkmSqi2j17RLkiSplFHGs7gmSZKqLaPXtEuSJKmUUcazuCZJkqoto6eakiRJKmWU8fIpE0qSJEmSJEkN5sg1SZJUbRm9SUqSJEmljDKexTVJklRtGa3HIUmSpFJGGS+fO5EkSZIkSZIazJFrkiSp2jJa7FaSJEmljDKeI9ckSVK1RVN9NkmSJFVHAzNeRDRHxL0RcVX5fVBEXB8Rj5V/DqzpOy4ipkXE1Ig4cl2Ob9KUJEnVFlGfTZIkSdXR2Ix3BjCl5vuZwI0ppZHAjeV3ImIXYAwwCjgKOC8imjs6uMU1SZIkSZIkZSkihgPvBH5R0zwauKT8fAlwXE37ZSmlFSml6cA0YL+OzuGaa5IkqdoyepOUJEmSSnXKeBExFhhb0zQhpTSh5vsPgM8DfWvahqSUZgGklGZFxOCyfRhwe02/GWVbuyyuSZKkSktO6ZQkScpOvTJeWUib0NZvEXEMMCeldHdEHLIOh2vrolJHO1lckyRJkiRJUo4OAI6NiKOBXkC/iPg1MDsihpaj1oYCc8r+M4ARNfsPB2Z2dBLnWUiSpGrzbaGSJEn5aUDGSymNSykNTyltS/GigptSSicBk4BTym6nAFeWnycBYyKiZ0RsB4wE7uzoVhy5JkmSqs3CmCRJUn66NuOdDUyMiFOBp4ATAFJKkyNiIvAwsBo4LaXU0tHBLK5JkqRKc801SZKk/DQ646WUbgZuLj8/Dxy2ln7jgfGv5dg+CpYkSZIkSZI6yZFrkiSp2pwWKkmSlJ+MMp7FNUmSVG1OC5UkScpPRhkvnzKhJEmSJEmS1GCOXJMkSdXW5LNASZKk7GSU8SyuSZKkSvNtoZIkSfnJKeNZXJMkSdWW0WK3kiRJKmWU8fK5E0mSJEmSJKnBHLkmSZIqLWX0VFOSJEmFnDKexTVJklRtGa3HIUmSpFJGGS+fMqEkSZIkSZLUYI5ckyRJlZbTlAFJkiQVcsp4FtckSVK1ZTRlQJIkSaWMMp7FNUmSVG0ZPdWUJElSKaOMl8+dSJIkSZIkSQ3myDVJklRpKaMpA5IkSSrklPEsrkmSpGrLaMqAJEmSShllvHzuRJIkSZIkSWowR65JkqRKS+QzZUCSJEmFnDKexTVJklRpKaMpA5IkSSrklPEsrkmSpGrLKHhJkiSplFHGy+dOJEmSJEmSpAZz5JokSaq0nF7TLkmSpEJOGc/imiRJqrSc1uOQJElSIaeMl8+dSJIkSZIkSQ3myDVJklRtGU0ZkCRJUimjjGdxTZIkVVpOUwYkSZJUyCnjWVyTJEmVlsjnqaYkSZIKOWW8fMqEkiRJkiRJUoM5ck2SJFVaTlMGJEmSVMgp41lckyRJ1ZbRYreSJEkqZZTx8ikTSpIkSZIkSQ1mcU2SJFVaoqkumyRJkqqjURkvInpFxJ0RcX9ETI6Ir5XtX42IZyLivnI7umafcRExLSKmRsSRHZ3DaaGSJKnSUkZTBiRJklRoYMZbARyaUlocEd2BWyPi6vK3c1NK36vtHBG7AGOAUcBWwA0RsWNKqWVtJ/AxriRJqrQUTXXZ1kVEfLp8ovlQRPy2fNI5KCKuj4jHyj8H1vR/TU81JUmSVGhUxkuFxeXX7uWW2tllNHBZSmlFSmk6MA3Yr71zWFyTJEkCImIY8Elgn5TSrkAzxVPLM4EbU0ojgRvL7698qnkUcF5ENHfFtUuSJGntIqI5Iu4D5gDXp5TuKH86PSIeiIgLax6gDgOertl9Rtm2VhbXJElSpSWiLts66gb0johuwCbATIqnl5eUv18CHFd+fs1PNSVJklSoV8aLiLERcVfNNvZV50qpJaW0BzAc2C8idgXOB3YA9gBmAd8vu7cVHNsb6eaaa5IkqdrWdUpnR8qgVRu2JqSUJrx0npSeiYjvAU8By4DrUkrXRcSQlNKsss+siBhc7jIMuL3meB0+1ZQkSVKhXhmvzHMTOuxY9F0QETcDR9WutRYRPweuKr/OAEbU7Dac4oHrWjlyTZIkbRRSShNSSvvUbGuEsHIqwGhgO4rFa/tExEntHPI1P9WUJElSY0XEFhExoPzcGzgceCQihtZ0ezfwUPl5EjAmInpGxHbASODO9s7hyDVJklRpDXyT1OHA9JTSXICI+APwVmB2RAwtR60NpVirAzrxVFOSJEmFBma8ocAl5dq4TcDElNJVEfGriNiD4uHok8BHAVJKkyNiIvAwsBo4rb03hYLFNUmSVHGvYb209fUUsH9EbEIxLfQw4C5gCXAKcHb555Vl/0nApRFxDsVItw6fakqSJKnQqIyXUnoA2LON9g+2s894YPy6nsPimiRJqrR6rcfR4XlSuiMifg/cQ/GU8l6K9Ts2BSZGxKkUBbgTyv6v+ammJEmSCo3KeI1gcU2SJKmUUjoLOOsVzSsoRrG11f81PdWUJElSfiyuSZKkSmvgtFBJkiQ1SE4Zz+KaJEmqtJymDEiSJKmQU8bL504kSZIkSZKkBnPkmiRJqrScpgxIkiSpkFPGs7gmSZIqLacpA5IkSSrklPEsrkmSpErL6ammJEmSCjllvA1eXJtz3dQNfQpJXeyGeed29SVI2uAO7uoLUMU88T+PdPUlSNqArpv79a6+BEkNYcarB0euSZKkSkuRz1NNSZIkFXLKeBbXJElSpaWUT/CSJElSIaeMl8/qcZIkSZIkSVKDOXJNkiRVWvJZoCRJUnZyyngW1yRJUqXl9CYpSZIkFXLKeBbXJElSpeUUvCRJklTIKePlMwZPkiRJkiRJajBHrkmSpErL6ammJEmSCjllPItrkiSp0nIKXpIkSSrklPGcFipJkiRJkiR1kiPXJElSpaWUz1NNSZIkFXLKeBbXJElSpeU0ZUCSJEmFnDKexTVJklRpOQUvSZIkFXLKeK65JkmSJEmSJHWSI9ckSVKl5fRUU5IkSYWcMp7FNUmSVGk5LXYrSZKkQk4Zz2mhkiRJkiRJUic5ck2SJFVaa0ZTBiRJklTIKeNZXJMkSZWW03ockiRJKuSU8ZwWKkmSJEmSJHWSI9ckSVKl5bTYrSRJkgo5ZTyLa5IkqdJymjIgSZKkQk4Zz+KaJEmqtJyeakqSJKmQU8ZzzTVJkiRJkiSpkyyuSZKkSktEXTZJkiRVR6MyXkT0iog7I+L+iJgcEV8r2wdFxPUR8Vj558CafcZFxLSImBoRR3Z0DotrkiSp0lKKumySJEmqjgZmvBXAoSml3YE9gKMiYn/gTODGlNJI4MbyOxGxCzAGGAUcBZwXEc3tncDimiRJkiRJkrKUCovLr93LLQGjgUvK9kuA48rPo4HLUkorUkrTgWnAfu2dw+KaJEmqtNY6bZIkSaqORma8iGiOiPuAOcD1KaU7gCEppVkA5Z+Dy+7DgKdrdp9Rtq2VbwuVJEmV5pROSZKk/NQr40XEWGBsTdOElNKENc+VWoA9ImIA8MeI2LW9Q7bRltq7BotrkiSp0nwZgSRJUn7qlfHKQtqEDjsWfRdExM0Ua6nNjoihKaVZETGUYlQbFCPVRtTsNhyY2d5xnRYqSZIkSZKkLEXEFuWINSKiN3A48AgwCTil7HYKcGX5eRIwJiJ6RsR2wEjgzvbO4cg1SZJUaU4LlSRJyk8DM95Q4JLyjZ9NwMSU0lURcRswMSJOBZ4CTiiuK02OiInAw8Bq4LRyWulaWVyTJEmV5rRQSZKk/DQq46WUHgD2bKP9eeCwtewzHhi/rudwWqgkSZIkSZLUSY5ckyRJldba7ruZJEmS9HqUU8azuCZJkirNaaGSJEn5ySnjWVyTJEmV5gsNJEmS8pNTxnPNNUmSJEmSJKmTHLkmSZIqLWW0HockSZIKOWU8i2uSJKnSWjNaj0OSJEmFnDKe00IlSZIkSZKkTnLkmiRJqrScFruVJElSIaeMZ3FNkiRVWk7rcUiSJKmQU8azuCZJkiotZbQehyRJkgo5ZTzXXJMkSZIkSZI6yZFrkiSp0lozmjIgSZKkQk4Zz+KaJEmqtJwWu5UkSVIhp4zntFBJkiRJkiSpkxy5JkmSKi2nN0lJkiSpkFPGs7gmSZIqrTWjN0lJkiSpkFPGc1qoJEmqtJTqs62LiBgQEb+PiEciYkpEvCUiBkXE9RHxWPnnwJr+4yJiWkRMjYgjN9T/BpIkSblpZMbb0CyuSZIkveyHwDUppZ2B3YEpwJnAjSmlkcCN5XciYhdgDDAKOAo4LyKau+SqJUmS1GUsrkmSpEpLKeqydSQi+gEHARcU500rU0oLgNHAJWW3S4Djys+jgctSSitSStOBacB+db15SZKkTDUq4zWCa65JkqRKa23ccP/tgbnARRGxO3A3cAYwJKU0CyClNCsiBpf9hwG31+w/o2yTJElSBxqY8TY4R65JkqSNQkSMjYi7araxr+jSDdgLOD+ltCewhHIK6NoO2UZbRjFRkiRJ68KRa5IkqdLqtVBtSmkCMKGdLjOAGSmlO8rvv6cors2OiKHlqLWhwJya/iNq9h8OzKzP1UqSJOWtKi8jqAdHrkmSpEpLRF22Ds+T0rPA0xGxU9l0GPAwMAk4pWw7Bbiy/DwJGBMRPSNiO2AkcGc9712SJClXjcp4jeDINUmSVGkNXo/jP4DfREQP4AngQxQPIydGxKnAU8AJACmlyRExkaIAtxo4LaXU0tCrlSRJep3Kac01i2uSJEmllNJ9wD5t/HTYWvqPB8ZvyGuSJElStVlckyRJlZbTehySJEkq5JTxLK5JkqRKyyl4SZIkqZBTxvOFBpIkSZIkSVInOXJNkiRVWmuqxlugJEmSVD85ZTyLa5IkqdJymjIgSZKkQk4Zz+KaJEmqtJyClyRJkgo5ZTzXXJMkSZIkSZI6yeKaJEmqtNZUn02SJEnV0aiMFxEjIuKvETElIiZHxBll+1cj4pmIuK/cjq7ZZ1xETIuIqRFxZEfncFqoJEmqtJTRYreSJEkqNDDjrQY+m1K6JyL6AndHxPXlb+emlL5X2zkidgHGAKOArYAbImLHlFLL2k7gyDVJkiRJkiRlKaU0K6V0T/l5ETAFGNbOLqOBy1JKK1JK04FpwH7tncPimiRJqrSU6rNJkiSpOuqV8SJibETcVbONXds5I2JbYE/gjrLp9Ih4ICIujIiBZdsw4Oma3WbQfjHOaaGSJKnaXC9NkiQpP/XKeCmlCcCEjvpFxKbAFcCnUkoLI+J84BtAKv/8PvBhoK35qu1ercU1SZJUaY46kyRJyk8jM15EdKcorP0mpfSH4vxpds3vPweuKr/OAEbU7D4cmNne8Z0WKkmSJEmSpCxFRAAXAFNSSufUtA+t6fZu4KHy8yRgTET0jIjtgJHAne2dw5FrkiSp0hy5JkmSlJ8GZrwDgA8CD0bEfWXbF4ETI2IPiimfTwIfLa4rTY6IicDDFG8aPa29N4WCxTVJklRxrrkmSZKUn0ZlvJTSrbS9jtpf2tlnPDB+Xc/htFBJkiRJkiSpkxy5JkmSKs1poZIkSfnJKeNZXJMkSZXW2trVVyBJkqR6yynjWVyTJEmVltNTTUmSJBVyyniuuSZJkiRJkiR1kiPXJElSpeX0VFOSJEmFnDKexTVJklRpjXpNuyRJkhonp4zntFBJkiRJkiSpkxy5JkmSKi3Vbc5A1Ok4kiRJWl85ZTyLa+K8Lx5Kz159iKYmmpqa+bcv/mGN3/859Q7+cP4n6L/5cAB23PMIDnzn6et1ztWrVnLVxZ/n2acm07vPAEZ/5FwGbD6c2U9P4dpLv8rK5YuJpibe+o6P88Z9jl6vc0mC3/ztAa74xxQScPy+b+SkA3Zb4/dFy1fwxYk38eyCxaxubeWUt+3OcXvvvF7nXLm6hS9dfhNTnplL/0168Z0TD2fYwH48MvM5xl/5fyxesZLmpuAjh+zFUbu9Yb3OpbzltB6H1CiL5s/ihku/wNJFzxHRxKi3vI/dDzp5jT5PPHQjd1z9QyKaiKZm3nbcF9lq+73X67wtq1dy/aVfYO7Tk+nVZwBHnnwO/QYNZ+4zU7j5919l1fIlRFMT+xz+MUbuacaT6qGltZUPXHwtgzftzY/ed0ibfSbPfJ6Tf3kdZx93AEfsvPV6nW/l6hb+86rbmDJrHv179+S/jjuArQZsytTZ8xl/zZ0sWbma5ghOfesojtxlm/U6l/KWU8azuCYATvzMJWyy6aC1/j585D6ccNrPXvNxFzw3gz9fMo4PfPZXa7Q/8LfL6bVJPz72jet5+B9/5uY/fo/j/v0HdO/Ri2P+7b8YNGRbFi2YzcXfOp7tdjmQXpv0e83nllR47Nl5XPGPKfzmE++he3Mzn7j4z7xtp63ZZvMBL/X53e2T2X7wQH588juYt3gZo8+9jHfuPpLu3Zo7PP4z8xfyld//lQv+ffQa7X+8awr9evfkqs+9n6vvn8YPrrmD7554BL16dOObJ/wL22w+gDkLl3DiT6/grSNH0K93z3rfujLR2trVVyC9/jQ1N3PA6C8wePgoVi5fzO/OPZ4RO76VQVu+/DBj+Mj92W7UoUQEz82cyjW//BQnnXn1Oh1/4bwZ3PDbcbzntDUz3sN3/J6evfvxwS9dx6P3/pm/X/V9jjr5XLp178UR7/8vBmyxLYtfmM3Ec97L1jsfSM/eZjxpfV1611S226wfS1asavP3ltZWfnjzfbxluy1f03FnLljMV/58O7/4wOFrtP/P/Y/Tt1cPJn38WK55+El+ePN9/NdxB9KrWzPfeNdb2GZQP+YsWsoHLrqGt24/lL69enT63pS3nDKea65pvTx0x5Vc8u33cuE3R3PNb75Ca2vLOu332AM38aa3vBuAnfc6kn8+chspJQYN2Y5BQ7YFoO+AIWzSdxBLF83bUJcvbRSmz53PblsPoXeP7nRrbmLv7bbipoenr9EngKUrVpJSYunKVfTv3ZPmpuJfEVfd+yjvP+8K3vfjy/n6H/+XlnX8t+BfpzzJsXvtCMARu27PnY8/Q0qJbTcf8FJhb3C/Pgzq05v5S5bV7X4lSdCn32AGDx8FQI9emzJo8A4sfmH2Gn169OxDRDGVZtXKpUTNtJqpd01i4rkncNn3juOvE9c94z3x0I3svO9xALxhtyOZ8ViR8QYO3o4BW2wLwKb9h9B700EsW2zGk9bX7IVLuXXaTN69+w5r7XPZXY9y2E4jGNSn1xrtf35oOiddfA3/esFf+ObVd65zxrv5sRm8a9ftADh8562588nZpJTYZrN+bDOoKJgP7rsJA/v0Yt7S5Z28M+n1xeKaiIDf/fBULvrWe7jv/37XZp9nnriPC75xLBN//BHmznwMgOdmPc6Uu67mpM//lg9/+Uoimph855/W6ZyLFsym78ChADQ1d6Nn774sWzJ/jT4zpz9Aa8sqBm6xfsOWpY3dG4YM4u7ps1iwdDnLVq7i1qlP8eyCJWv0GfOWXXlizgIOP/tXvPdHE/n8MQfQ1BQ8MWc+1z74OJd89Dgm/scJNDcFf7nvsXU675wXlrBl/00B6NbcxKa9erDgFQHrwadns6qlhRGD+tfnZpWllOqzSRurhfNmMPeZKWy5ze6v+u3xB67n12e/g6t+/jEOHTMegHmzH+ex+/7C8Z+8lDGf+x+iqZlH7163jLfkhTn0HfByxuvRqy/LlyxYo8/sfxYZr/9mZjxpfX33hrs541/2pCnaXnNqzqKl3PToDN6755pLcDzx3AtcN+WfXPTBt/O7U4+mKYK/TH5ync45Z9EytuzXB4BuTU1s2rM7C5atWKPPQzOfY3VLKyMG9n3tN6WNRk4Zr9PTQiPiQymli+p5MeoaJ/2/39J3wBCWLHyey374IQZtuT1bj9z3pd+33HoUnxh/Ez169eHxB/+XP5x/Gh/9xnX885HbmP3UQ1zy7fcCsHrVcjbpuxkAV5x/Gi88P4OW1atYOH8WF36zmC62z6Ens9tbj2/zb0Dt09LFL8zhqov/H+885b+IJmvA0vrYfvBAPnTwHnz0wqvYpEd3dhy6Gd2a1wxgf3/0aXbeajN+8ZF38fS8hXz0wqvYa9uh3PH4M0x5Zi4fOK9Yi3H5qtUM6tMbgE/9+hpmzl/EqtWtzHphEe/78eUAvP+tb+K4vXemrX/PRU3wm7twCV+6/Ca++d5DaWrq+kVIVV05vab99cCMl5eVK5Zw9cWf5G3HjaNHr01f9fsOux3BDrsdwTOP/4M7rv4Rx338ImY8ehtzZkzm8nNPAIqM17tcPuQvF57OwnkzaGlZxeL5s7jse8cBsNtBH2SX/drOeLXrTC9ZOIfrL/08h594thlPWk+3PPYMgzbpxS5DB3HXP2e32acovu3x0oyEF9355LM8/Ox8Trr4GgBWrG5hUJ9iiY7PXHELzyxYzKqWVp5duJR/veAvALx/350YvdsObWe8mr/ocxcv48t/uo2vH/OWtRb9JMgr463PmmtfA9oMXhExFhgLcPJnfsYhx4xdj9NoQ+s7YAgAffptxo57HMGs6Q+sUVzr2fvlILbDmw7m2t9+jaWL55FI7Lr/uznk3Z991TGP//hPgbWvudZ34JYsmj+LfgO3pLVlNSuWLaJXnwEArFi2mMt/8lEOOvZTDNt+jzrfrbRxes8+b+Q9+7wRgB9dewdD+vdZ4/cr75nKhw/ak4hg6836M2xgX6bPnU9KiXfttRNnHPnmVx3zBycdBax9zbUh/fvw7AuLGdJ/U1a3tLJ4+Ur6l+uqLV6+ktN/eTWnH7Efu209ZEPcsqTOW6eM96+n/zcHHGXGq7KWllVcffEn2XGvd7HDbm9vt++wHfblhuefYtni+SQSO+9zHG895tUZ7+gP/wRY+5prfQYMYdGCWWw6oMh4K5cvotcmAwBYuXwxV/38Y+z/jk+x5bZ71OUepY3Zfc/M5X+nzeDW82aycnULS1as4kuT/s74Y9/6Up+HZ83jzCv/BsCCpSu49fGZdGsKEvCuN23HJw/Z41XHPef4g4C1r7k2pG9vnl24hCH9NmF1ayuLV6yif+9iXbXFK1bxyYk3c9pBu7PbsM03zI1LFdTu46KIeGAt24PAWv9rKKU0IaW0T0ppHwtr1bZyxVJWLF/80ucnp/yNLYaNXKPP4hfmvvSK3JnTH4DUSu8+A9l2p7cw9Z5rWbLweQCWLVnAC88/s07nfcNuh/LgbX8E4JF7rmWbnfYnImhZvZI//Pdp7Lr/aHbe+x31uk1po/f84mJNs1kLFnHj5Om8Y/c1/55v2X9T7nh8RtF30VKefG4Bwwf14807DOOGhx5/af8Xli5n5vxF63TOQ3belkn3PArA9Q89wX7bb0VEsGp1C5/+9bW8a88defub1r4+iPSinKYMVEU9Mp6FtWpLKXHT777MoME7sOchH2qzz4K5/3wp482ZMZnW1avo1WcAI0a+hccfuI6li4qMt3zJAhbOW7eMt92oQ3nkH/8DwLQHrmX4G17OeH+56HR22mc0b9jjqPW/QUl88pA9uPb0d/OXT4zm7NEHsO82Q9YorAH8+ROj+Uu5Hb7zCMYduS//suMI9tt2S2545CnmLSmW7Hhh2QpmvrCkrdO8ysEjh/Onh4r1e2945Cn23WZIkfFaWvjsFbdwzK7bccQbnfatjuWU8ToauTYEOBKY/4r2AP6+Qa5IDbV04fNc8d+nAZBaW9hl32PYftRB3HvLbwHY86ATmXrPtdx7y2+Jpma69+jFsR85h4hg863ewEGjP8XvfvRhUmqlqbk7bx/zFfpvNqzD8+5+wHv500X/j//+zyPovUl/Rn/kXACm3H01Tz92F8uWLHip+PbOU85myIg3bqD/BaSNw2d/cy0vLF1Bt+YmvnjsgfTr3ZOJd0wG4H1vHsXYQ/fmP3//V47/4URSSnzqyP0Z2Kc3A/v05rQj9uPjF11Fa0p0a2rii8e+ja3WYf2Md++zM1+6/CaO+d6l9NukJ98ZcwQA1z74OPc8OYsXli1n0j1TAfj68f/Czlv5dFNtS3WbM+DUlBpmvMzNmn4PU++6ks2G7vjS1M39j/40ixfMAmDXt47h8QeuY+pdV9LU3I3m7j058uRziQgGbfkG9n/HGUz62allxuvGwe/5Cv0GdZzxdnnze7n+0s/zq/Fvp+cm/Tny5HMAmHbfNcx8/C6WL1nAI/8oMt5hJ36bLYaZ8aR6u/yeYn3cE/YaudY+O2zen9MO2p2PX3YTKUG35uDMt+/LVq+Y3dCW43bfgS//6e8ce/4k+vXuwdmjDwTguilPcc/Tc1iwbAWTHnwCgK8f8xZ2GjKwDnelHOWU8SK1U+aLiAuAi1JKt7bx26Uppfd3dIKL/trmlGxJGTlx3rldfQmSNrBex3+6y1LLd66oT/L6/PEu7veiemS8H/+5Ks+KJW0Ip879eldfgqQG2OTfzjLj1UG7I9dSSqe281uHoUuSJEnVY8aTJEmqn/V5oYEkSdIG5/goSZKk/OSU8SyuSZKkSmvN6T3tkiRJAvLKeO2+LVSSJEmSJEnS2jlyTZIkVVpOUwYkSZJUyCnjWVyTJEmVllPwkiRJUiGnjGdxTZIkVVprTslLkiRJQF4ZzzXXJEmSJEmSpE5y5JokSaq01NrVVyBJkqR6yynjWVyTJEmVljKaMiBJkqRCThnPaaGSJEmSJElSJzlyTZIkVVprRlMGJEmSVMgp41lckyRJlZbTlAFJkiQVcsp4FtckSVKlteaTuyRJklTKKeO55pokSZIkSZKyFBEjIuKvETElIiZHxBll+6CIuD4iHiv/HFizz7iImBYRUyPiyI7O4cg1SZJUaSmnx5qSJEkCGprxVgOfTSndExF9gbsj4nrg34AbU0pnR8SZwJnAFyJiF2AMMArYCrghInZMKbWs7QSOXJMkSZWWUn02SZIkVUejMl5KaVZK6Z7y8yJgCjAMGA1cUna7BDiu/DwauCyltCKlNB2YBuzX3jksrkmSJEmSJCl7EbEtsCdwBzAkpTQLigIcMLjsNgx4uma3GWXbWjktVJIkVVqr00IlSZKyU6+MFxFjgbE1TRNSShPa6LcpcAXwqZTSwohY6yHbaGv3Yi2uSZKkSsvpNe2SJEkq1CvjlYW0VxXTakVEd4rC2m9SSn8om2dHxNCU0qyIGArMKdtnACNqdh8OzGzv+E4LlSRJlZZa67NJkiSpOhqV8aIYonYBMCWldE7NT5OAU8rPpwBX1rSPiYieEbEdMBK4s71zOHJNkiRJkiRJuToA+CDwYETcV7Z9ETgbmBgRpwJPAScApJQmR8RE4GGKN42e1t6bQsHimiRJqrhWp4VKkiRlp1EZL6V0K22vowZw2Fr2GQ+MX9dzWFyTJEmV5pprkiRJ+ckp47nmmiRJUo2IaI6IeyPiqvL7oIi4PiIeK/8cWNN3XERMi4ipEXFk1121JEmSuorFNUmSVGmtraku22twBjCl5vuZwI0ppZHAjeV3ImIXYAwwCjgKOC8imuty05IkSZnrgoy3wVhckyRJlZZSfbZ1ERHDgXcCv6hpHg1cUn6+BDiupv2ylNKKlNJ0YBqwXx1uWZIkKXuNzHgbmmuuSZKkSkuNfSL5A+DzQN+atiEppVkAKaVZETG4bB8G3F7Tb0bZJkmSpA40OONtUI5ckyRJG4WIGBsRd9VsY1/x+zHAnJTS3et6yDba8kmJkiRJWieOXJMkSZVWr9e0p5QmABPa6XIAcGxEHA30AvpFxK+B2RExtBy1NhSYU/afAYyo2X84MLMuFytJkpS5emW8KnDkmiRJqrTUmuqydXielMallIanlLaleFHBTSmlk4BJwCllt1OAK8vPk4AxEdEzIrYDRgJ31vv+JUmSctSojNcIjlyTJElq39nAxIg4FXgKOAEgpTQ5IiYCDwOrgdNSSi1dd5mSJEnqChbXJElSpXXFE8mU0s3AzeXn54HD1tJvPDC+YRcmSZKUiaqMOqsHi2uSJKnSMspdkiRJKuWU8SyuSZKkSsvpqaYkSZIKOWU8X2ggSZIkSZIkdZIj1yRJUqWljF7TLkmSpEJOGc/imiRJqrTWjKYMSJIkqZBTxnNaqCRJkiRJktRJjlyTJEmVltOUAUmSJBVyyngW1yRJUqXl9CYpSZIkFXLKeBbXJElSpeUUvCRJklTIKeO55pokSZIkSZLUSY5ckyRJldaa0XockiRJKuSU8SyuSZKkSstpyoAkSZIKOWU8p4VKkiRJkiRJneTINUmSVGk5vaZdkiRJhZwynsU1SZJUaa0ZTRmQJElSIaeMZ3FNkiRVWk7rcUiSJKmQU8ZzzTVJkiRJkiSpkxy5JkmSKi2n9TgkSZJUyCnjWVyTJEmVllpbu/oSJEmSVGc5ZTynhUqSJEmSJEmd5Mg1SZJUaTm9SUqSJEmFnDKexTVJklRpOa3HIUmSpEJOGc/imiRJqrScXtMuSZKkQk4ZzzXXJEmSJEmSlKWIuDAi5kTEQzVtX42IZyLivnI7uua3cRExLSKmRsSR63IOR65JkqRKy+mppiRJkgoNzHgXAz8BfvmK9nNTSt+rbYiIXYAxwChgK+CGiNgxpdTS3gksrkmSpEprTfm8pl2SJEmFRmW8lNItEbHtOnYfDVyWUloBTI+IacB+wG3t7eS0UEmSJEmSJG1sTo+IB8ppowPLtmHA0zV9ZpRt7bK4JkmSKi21prpskiRJqo56ZbyIGBsRd9VsY9fh9OcDOwB7ALOA75ft0daldnQwp4VKkqRKszAmSZKUn3plvJTSBGDCa9xn9oufI+LnwFXl1xnAiJquw4GZHR3PkWuSJKnSUkp12SRJklQdXZnxImJozdd3Ay++SXQSMCYiekbEdsBI4M6OjufINUmSJEmSJGUpIn4LHAJsHhEzgLOAQyJiD4opn08CHwVIKU2OiInAw8Bq4LSO3hQKFtckSVLFtbb6tlBJkqTcNCrjpZRObKP5gnb6jwfGv5ZzWFyTJEmV5pprkiRJ+ckp47nmmiRJkiRJktRJjlyTJEmVlpLTQiVJknKTU8azuCZJkiotpykDkiRJKuSU8SyuSZKkSsspeEmSJKmQU8ZzzTVJkiRJkiSpkxy5JkmSKq01o/U4JEmSVMgp41lckyRJlZbTlAFJkiQVcsp4TguVJEmSJEmSOsmRa5IkqdJSaz5TBiRJklTIKeNZXJMkSZWW05QBSZIkFXLKeBbXJElSpaWMFruVJElSIaeM55prkiRJkiRJUic5ck2SJFVaa0ZTBiRJklTIKeNZXJMkSZWW02K3kiRJKuSU8ZwWKkmSJEmSJHWSI9ckSVKl5fQmKUmSJBVyyngW1yRJUqXl9CYpSZIkFXLKeBbXJElSpeX0VFOSJEmFnDKea65JkiRJkiRJneTINUmSVGk5vUlKkiRJhZwyXqSUzzA8VUNEjE0pTejq65C04fj3XJI2Pv6zX8qff8+lznFaqDaEsV19AZI2OP+eS9LGx3/2S/nz77nUCRbXJEmSJEmSpE6yuCZJkiRJkiR1ksU1bQjO0Zfy599zSdr4+M9+KX/+PZc6wRcaSJIkSZIkSZ3kyDVJkiRJkiSpkyyuqa4i4qiImBoR0yLizK6+Hkn1FREXRsSciHioq69FktQY5jspf2Y8af1YXFPdREQz8FPgHcAuwIkRsUvXXpWkOrsYOKqrL0KS1BjmO2mjcTFmPKnTLK6pnvYDpqWUnkgprQQuA0Z38TVJqqOU0i3AvK6+DklSw5jvpI2AGU9aPxbXVE/DgKdrvs8o2yRJkvT6ZL6TJKkDFtdUT9FGm6+jlSRJev0y30mS1AGLa6qnGcCImu/DgZlddC2SJElaf+Y7SZI6YHFN9fQPYGREbBcRPYAxwKQuviZJkiR1nvlOkqQOWFxT3aSUVgOnA9cCU4CJKaXJXXtVkuopIn4L3AbsFBEzIuLUrr4mSdKGY76TNg5mPGn9REoumSBJkiRJkiR1hiPXJEmSJEmSpE6yuCZJkiRJkiR1ksU1SZIkSZIkqZMsrkmSJEmSJEmdZHFNkiRJkiRJ6iSLa5IkSZIkSVInWVyTJEmSJEmSOsnimiRJkiRJktRJ/x9Ba6aB5w/74AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "classification_metrics(y_train,y_pred_train,y_test,y_pred_test,True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> The model is quite good, but we have a little bit of low recall"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> Let's see if we are able to reduce some features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "pca = PCA().fit(X_train)\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(np.cumsum(pca.explained_variance_ratio_), color='k', lw=2)\n",
    "plt.xlabel('Number of components')\n",
    "plt.ylabel('Total explained variance')\n",
    "plt.xlim(0, 50)\n",
    "plt.yticks(np.arange(0, 1.1, 0.1))\n",
    "plt.axvline(8, c='b')\n",
    "plt.axhline(0.965, c='r')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> This graph shows that we only need approximately 10 features to consist 98 % of data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#FF7B07\"><div align=\"center\">**Reduce Data Features & Test** <a  name=\"4\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> To reduce features, I write a method that will check every combination of features, <br> check average accuracy based on cross-validation also this method check Decision Tree depth range 2-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this method returns depth length and average accuracy based on cross validation\n",
    "\n",
    "def get_accuracy_based_on_depth(depth_range,X_train,y_train,cv):\n",
    "    accuracies = []\n",
    "    for depth in depth_range:\n",
    "        fold_accuracy = []\n",
    "        tree_model = DecisionTreeClassifier(max_depth = depth,random_state = 42)\n",
    "\n",
    "        for train_fold, valid_fold in cv.split(X_train):\n",
    "            f_train_x = X_train.iloc[train_fold] \n",
    "            f_train_y = y_train.iloc[train_fold]\n",
    "\n",
    "            f_valid_x = X_train.iloc[valid_fold]\n",
    "            f_valid_y = y_train.iloc[valid_fold]\n",
    "\n",
    "            model = tree_model.fit(X = f_train_x,y = f_train_y) # We fit the model with the fold train data\n",
    "            valid_acc = model.score(X = f_valid_x,y = f_valid_y) # We calculate accuracy with the fold validation data\n",
    "            fold_accuracy.append(valid_acc)\n",
    "\n",
    "        avg = sum(fold_accuracy)/len(fold_accuracy)\n",
    "        accuracies.append(avg)\n",
    "\n",
    "    df = pd.DataFrame({\"Max Depth\": depth_range, \"Average Accuracy\": accuracies})\n",
    "    df = df[[\"Max Depth\", \"Average Accuracy\"]]\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this method consider every subset of length two, \n",
    "# for all of them it finds the best depth (depth where the average accuracy is max) \n",
    "# and prints the metric if they are more than metric_threshold\n",
    "\n",
    "\n",
    "def get_max_accuracy_based_on_features(X_train, X_test, y_train, y_test, col_set, metric_threshold = 0.7):\n",
    "    cv = KFold(n_splits=10,shuffle = True,random_state=42)\n",
    "    accuracies = list()\n",
    "\n",
    "    X_train_temp = X_train.copy()\n",
    "    X_test_temp = X_test.copy()\n",
    "    depth_range = range(2, 6)\n",
    "    \n",
    "    test_feature_subset = list(itertools.combinations(col_set, 2))\n",
    "\n",
    "    for sub in test_feature_subset:\n",
    "        drop_col = list(filter(lambda x: (sub[0] in x) or (sub[1] in x), X_train_temp.columns))\n",
    "        X_train = X_train_temp.drop(columns = drop_col)\n",
    "        X_test = X_test_temp.drop(columns = drop_col)\n",
    "\n",
    "        df = get_accuracy_based_on_depth(depth_range,X_train,y_train,cv)\n",
    "\n",
    "        optimal_length = df[df['Average Accuracy']==df['Average Accuracy'].max()]['Max Depth'].values[0]\n",
    "        decision_tree = DecisionTreeClassifier(max_depth=optimal_length,random_state=42)\n",
    "        decision_tree.fit(X_train, y_train)\n",
    "        y_pred_test = decision_tree.predict(X_test)\n",
    "\n",
    "        accuracy = accuracy_score(y_test, y_pred_test).round(2)\n",
    "        precision = precision_score(y_test, y_pred_test).round(2)\n",
    "        recall = recall_score(y_test, y_pred_test).round(2)\n",
    "        f1 = f1_score(y_test, y_pred_test).round(2) \n",
    "        \n",
    "        if ((accuracy>=metric_threshold) and (precision>=metric_threshold) and (recall>=metric_threshold) and (f1>=metric_threshold)):\n",
    "            print(f\"Accuracy: {accuracy}  Precision: {precision}  Recall: {recall}  F1:  {f1} --- {sub} Tree_depth {optimal_length}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.71  F1:  0.7 --- ('sugar', '_diff') Tree_depth 2\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.71  F1:  0.7 --- ('sugar', 'carbs') Tree_depth 2\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.71  F1:  0.7 --- ('_diff', 'total') Tree_depth 2\n",
      "Accuracy: 0.71  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('carbs', 'total') Tree_depth 5\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.71  F1:  0.7 --- ('protein', 'total') Tree_depth 5\n"
     ]
    }
   ],
   "source": [
    "get_max_accuracy_based_on_features(X_train,X_test,y_train,y_test,{'_diff','total','calories','FoodGroup','sodium','sugar','fat','carbs','protein'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> As we saw there are various combinations to reach max accuracy but I'm gonna choose to drop {carbs,total} becouse of 4 reasons:\n",
    "\n",
    "- ##### <span style=\"color:#00CC00\"> Without these features metrics are more than without other combinations above\n",
    "- ##### <span style=\"color:#00CC00\"> To drop column \"total\" is easy becouse we have it's information in _diff columns\n",
    "- ##### <span style=\"color:#00CC00\"> To drop colum  \"carbs\" is also easy becouse heatmap showed that carbs and calories were too much dependent\n",
    "- ##### <span style=\"color:#00CC00\"> The method is more general when depth will be 5 and won't be depended with only 2 features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "73\n"
     ]
    }
   ],
   "source": [
    "drop_col = list(filter(lambda x: (\"carbs\" in x) or (\"total\" in x), X_train.columns))\n",
    "X_train = X_train.drop(columns=drop_col)\n",
    "X_test = X_test.drop(columns=drop_col)\n",
    "print(len(X_train.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> Features are too much and let's see if we could drop other features too. <br> We use first 10 days info as an input , it may be important only first(when user started to log) and 10th (when user adapted to log) days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_col = list(filter(lambda x: (\"_1\" in x) or (\"_2\" in x) or (\"_3\" in x) or (\"_4\" in x) or (\"_5\" in x) or (\"_6\" in x) or (\"_7\" in x) or (\"_8\" in x), X_train.columns))\n",
    "X_train = X_train.drop(columns=drop_col)\n",
    "X_test = X_test.drop(columns=drop_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.71  F1:  0.71 --- ('sodium', 'sugar') Tree_depth 4\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('sodium', '_diff') Tree_depth 3\n",
      "Accuracy: 0.71  Precision: 0.7  Recall: 0.73  F1:  0.71 --- ('sugar', 'calories') Tree_depth 4\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('sugar', '_diff') Tree_depth 3\n",
      "Accuracy: 0.71  Precision: 0.7  Recall: 0.73  F1:  0.71 --- ('sugar', 'protein') Tree_depth 4\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('calories', '_diff') Tree_depth 3\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('_diff', 'protein') Tree_depth 3\n",
      "Accuracy: 0.7  Precision: 0.7  Recall: 0.72  F1:  0.71 --- ('_diff', 'fat') Tree_depth 3\n"
     ]
    }
   ],
   "source": [
    "get_max_accuracy_based_on_features(X_train,X_test,y_train,y_test,{'_diff','calories','FoodGroup','sodium','sugar','fat','protein'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> As we see, data had too much noise and after reducing features, we have 8 combinations which we can drop. <br> We choose to drop {protein, sugar} because recall is rised and also tree depth is quite well too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_col = list(filter(lambda x: (\"protein\" in x) or (\"sugar\" in x), X_train.columns))\n",
    "X_train = X_train.drop(columns=drop_col)\n",
    "X_test = X_test.drop(columns=drop_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "decision_tree = DecisionTreeClassifier(max_depth=4,random_state=42)\n",
    "decision_tree.fit(X_train, y_train)\n",
    "\n",
    "y_pred_train = decision_tree.predict(X_train)\n",
    "y_pred_test = decision_tree.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> Features quantity is reduced and let's see the visualization of decision tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2520x1296 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import tree\n",
    "fig = plt.figure(figsize=(35,18))\n",
    "_ = tree.plot_tree(decision_tree, feature_names=X_train.columns,class_names=['0','1'],filled=True,fontsize = 17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train data:\t  \t\t\t\t\t\ttest data:\t\n",
      "\n",
      "accuracy:\t 0.74 \t\t\t\t\t\taccuracy:\t 0.71\n",
      "precision:\t 0.74 \t\t\t\t\t\tprecision:\t 0.7\n",
      "recall:\t\t 0.74 \t\t\t\t\t\trecall:\t\t 0.73\n",
      "F1:\t\t 0.74 \t\t\t\t\t\tF1:\t\t 0.71\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "classification_metrics(y_train,y_pred_train,y_test,y_pred_test,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used features:\n",
      " ['foods_len' 'healtyDistrib' 'calories_diff' 'fat_diff' 'sodium_diff'\n",
      " 'foods_len_9' 'healtyDistrib_9' 'calories_diff_9' 'fat_diff_9'\n",
      " 'sodium_diff_9' 'start_date' 'days_missed' 'FoodGroup']\n"
     ]
    }
   ],
   "source": [
    "print(f\"used features:\\n {X_train.columns.values}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> We can notice that features quantity is really reduced ( there are 13 of them) but despite this, metrics are same as the baseline model. <br> Also decision tree is depth of 4 and the model is not depended only 1 or 2 features. <br> Also, the fun fact is that all of the rest features are produced by us"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#FF7B07\"> Becouse of the reduced features we can now implement logistic regression too and see the results of it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LogisticRegression(random_state=0)\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "y_pred_train = model.predict(X_train)\n",
    "y_pred_test = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train data:\t  \t\t\t\t\t\ttest data:\t\n",
      "\n",
      "accuracy:\t 0.66 \t\t\t\t\t\taccuracy:\t 0.65\n",
      "precision:\t 0.66 \t\t\t\t\t\tprecision:\t 0.64\n",
      "recall:\t\t 0.66 \t\t\t\t\t\trecall:\t\t 0.68\n",
      "F1:\t\t 0.66 \t\t\t\t\t\tF1:\t\t 0.66\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "classification_metrics(y_train,y_pred_train,y_test,y_pred_test,True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### <span style=\"color:#00CC00\"> As we see the result of logistic regression is a bit worse than decision tree . May be the reason is that data is complex and model didn't adapted the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#FF7B07\"><div align=\"center\">**Summary** <a  name=\"5\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <span style=\"color:#00CC00\"> In this notebook we predicted if the user will reach a goal or not. <br> \n",
    "- ##### <span style=\"color:#00CC00\"> Firstly we run baseline model and see the result. \n",
    "- ##### <span style=\"color:#00CC00\"> After that, because of the large quantity of features, we tried to reduce data with various techniques \n",
    "- ##### <span style=\"color:#00CC00\"> and at last, we have 13 features and get same metrics as baseline model \n",
    "- ##### <span style=\"color:#FF7B07\"> Accuracy: 0.71 Precision: 0.70 Recall: 0.73 F1: 0.71"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}