Random Forest Models.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DATA LOADING AND CLEANING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>hh_size</th>\n",
       "      <th>med_income</th>\n",
       "      <th>occ_units</th>\n",
       "      <th>med_rent</th>\n",
       "      <th>oo_hsng_units</th>\n",
       "      <th>perc_white</th>\n",
       "      <th>perc_non_white</th>\n",
       "      <th>perc_black</th>\n",
       "      <th>perc_owner_occ</th>\n",
       "      <th>...</th>\n",
       "      <th>Roof Material_nan</th>\n",
       "      <th>Repair Condition_1.0</th>\n",
       "      <th>Repair Condition_2.0</th>\n",
       "      <th>Repair Condition_3.0</th>\n",
       "      <th>Repair Condition_nan</th>\n",
       "      <th>Renovation_1.0</th>\n",
       "      <th>Renovation_2.0</th>\n",
       "      <th>Renovation_nan</th>\n",
       "      <th>threshold_high</th>\n",
       "      <th>threshold_medium</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.95</td>\n",
       "      <td>55160.5</td>\n",
       "      <td>236.0</td>\n",
       "      <td>873.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>0.574837</td>\n",
       "      <td>0.425163</td>\n",
       "      <td>0.234273</td>\n",
       "      <td>0.495763</td>\n",
       "      <td>...</td>\n",
       "      <td>0.801619</td>\n",
       "      <td>0.004049</td>\n",
       "      <td>0.190283</td>\n",
       "      <td>0.004049</td>\n",
       "      <td>0.801619</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1.50</td>\n",
       "      <td>54297.0</td>\n",
       "      <td>1073.0</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>327.0</td>\n",
       "      <td>0.663361</td>\n",
       "      <td>0.336639</td>\n",
       "      <td>0.249125</td>\n",
       "      <td>0.304753</td>\n",
       "      <td>...</td>\n",
       "      <td>0.924528</td>\n",
       "      <td>0.006289</td>\n",
       "      <td>0.069182</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.924528</td>\n",
       "      <td>0.002096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.997904</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.30</td>\n",
       "      <td>42778.0</td>\n",
       "      <td>712.0</td>\n",
       "      <td>1097.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>0.280774</td>\n",
       "      <td>0.719226</td>\n",
       "      <td>0.436694</td>\n",
       "      <td>0.314607</td>\n",
       "      <td>...</td>\n",
       "      <td>0.625442</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.371025</td>\n",
       "      <td>0.003534</td>\n",
       "      <td>0.625442</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.69</td>\n",
       "      <td>39535.0</td>\n",
       "      <td>1424.0</td>\n",
       "      <td>1152.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>0.542930</td>\n",
       "      <td>0.457070</td>\n",
       "      <td>0.300637</td>\n",
       "      <td>0.247893</td>\n",
       "      <td>...</td>\n",
       "      <td>0.787551</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.211096</td>\n",
       "      <td>0.001353</td>\n",
       "      <td>0.787551</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.99</td>\n",
       "      <td>52948.0</td>\n",
       "      <td>611.0</td>\n",
       "      <td>1023.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>0.465461</td>\n",
       "      <td>0.534539</td>\n",
       "      <td>0.326206</td>\n",
       "      <td>0.186579</td>\n",
       "      <td>...</td>\n",
       "      <td>0.694190</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.305810</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.694190</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  hh_size  med_income  occ_units  med_rent  oo_hsng_units  \\\n",
       "0           0     1.95     55160.5      236.0     873.0          117.0   \n",
       "1           2     1.50     54297.0     1073.0    1071.0          327.0   \n",
       "2           3     2.30     42778.0      712.0    1097.0          224.0   \n",
       "3           4     2.69     39535.0     1424.0    1152.0          353.0   \n",
       "4           5     2.99     52948.0      611.0    1023.0          114.0   \n",
       "\n",
       "   perc_white  perc_non_white  perc_black  perc_owner_occ  ...  \\\n",
       "0    0.574837        0.425163    0.234273        0.495763  ...   \n",
       "1    0.663361        0.336639    0.249125        0.304753  ...   \n",
       "2    0.280774        0.719226    0.436694        0.314607  ...   \n",
       "3    0.542930        0.457070    0.300637        0.247893  ...   \n",
       "4    0.465461        0.534539    0.326206        0.186579  ...   \n",
       "\n",
       "   Roof Material_nan  Repair Condition_1.0  Repair Condition_2.0  \\\n",
       "0           0.801619              0.004049              0.190283   \n",
       "1           0.924528              0.006289              0.069182   \n",
       "2           0.625442              0.000000              0.371025   \n",
       "3           0.787551              0.000000              0.211096   \n",
       "4           0.694190              0.000000              0.305810   \n",
       "\n",
       "   Repair Condition_3.0  Repair Condition_nan  Renovation_1.0  Renovation_2.0  \\\n",
       "0              0.004049              0.801619        0.000000             0.0   \n",
       "1              0.000000              0.924528        0.002096             0.0   \n",
       "2              0.003534              0.625442        0.000000             0.0   \n",
       "3              0.001353              0.787551        0.000000             0.0   \n",
       "4              0.000000              0.694190        0.000000             0.0   \n",
       "\n",
       "   Renovation_nan  threshold_high  threshold_medium  \n",
       "0        1.000000               0                 1  \n",
       "1        0.997904               0                 0  \n",
       "2        1.000000               0                 1  \n",
       "3        1.000000               0                 1  \n",
       "4        1.000000               0                 1  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final = pd.read_csv('data/final_df.csv')\n",
    "final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_features = final.iloc[:, 1:-2]\n",
    "threshold_medium = final.iloc[:, -1:]\n",
    "threshold_high = final.iloc[:, -2:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "nans = []\n",
    "for col in full_features.columns:\n",
    "    if len(full_features.loc[full_features[col].isna()]) >= 1:\n",
    "        nans.append(col)\n",
    "for col in nans:\n",
    "    full_features[col].fillna(full_features[col].median(), inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RANDOM FOREST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>param_RF__n_estimators</th>\n",
       "      <th>param_RF__criterion</th>\n",
       "      <th>param_RF__max_depth</th>\n",
       "      <th>param_RF__min_samples_split</th>\n",
       "      <th>rank_test_accuracy</th>\n",
       "      <th>mean_test_accuracy</th>\n",
       "      <th>mean_test_precision</th>\n",
       "      <th>mean_test_recall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.760669</td>\n",
       "      <td>0.645204</td>\n",
       "      <td>0.199154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0.758836</td>\n",
       "      <td>0.635925</td>\n",
       "      <td>0.194450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>0.758230</td>\n",
       "      <td>0.630767</td>\n",
       "      <td>0.192230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>14</td>\n",
       "      <td>0.756397</td>\n",
       "      <td>0.621483</td>\n",
       "      <td>0.192178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>0.755185</td>\n",
       "      <td>0.617306</td>\n",
       "      <td>0.189852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>0.758843</td>\n",
       "      <td>0.644370</td>\n",
       "      <td>0.187579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.759438</td>\n",
       "      <td>0.646655</td>\n",
       "      <td>0.185254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>0.757010</td>\n",
       "      <td>0.628730</td>\n",
       "      <td>0.185201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0.757624</td>\n",
       "      <td>0.635850</td>\n",
       "      <td>0.180708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>0.756404</td>\n",
       "      <td>0.629466</td>\n",
       "      <td>0.180603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>0.756390</td>\n",
       "      <td>0.633811</td>\n",
       "      <td>0.180550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>0.755185</td>\n",
       "      <td>0.622729</td>\n",
       "      <td>0.178277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0.758222</td>\n",
       "      <td>0.662896</td>\n",
       "      <td>0.171353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0.758825</td>\n",
       "      <td>0.669440</td>\n",
       "      <td>0.171300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0.757613</td>\n",
       "      <td>0.655124</td>\n",
       "      <td>0.169027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>0.757613</td>\n",
       "      <td>0.659886</td>\n",
       "      <td>0.166755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0.758222</td>\n",
       "      <td>0.662827</td>\n",
       "      <td>0.166755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>0.755787</td>\n",
       "      <td>0.640957</td>\n",
       "      <td>0.164429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>0.750935</td>\n",
       "      <td>0.685714</td>\n",
       "      <td>0.095190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "      <td>0.750322</td>\n",
       "      <td>0.680833</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>0.750322</td>\n",
       "      <td>0.680833</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>0.750928</td>\n",
       "      <td>0.697500</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>0.750928</td>\n",
       "      <td>0.697500</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>0.750928</td>\n",
       "      <td>0.697500</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.750928</td>\n",
       "      <td>0.697500</td>\n",
       "      <td>0.095137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>26</td>\n",
       "      <td>0.749715</td>\n",
       "      <td>0.650714</td>\n",
       "      <td>0.092865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "      <td>0.749106</td>\n",
       "      <td>0.642381</td>\n",
       "      <td>0.090539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>34</td>\n",
       "      <td>0.747882</td>\n",
       "      <td>0.715476</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>28</td>\n",
       "      <td>0.749102</td>\n",
       "      <td>0.763333</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>0.749102</td>\n",
       "      <td>0.763333</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>0.749102</td>\n",
       "      <td>0.767143</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "      <td>0.749102</td>\n",
       "      <td>0.763333</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>28</td>\n",
       "      <td>0.749102</td>\n",
       "      <td>0.767143</td>\n",
       "      <td>0.069662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "      <td>0.748492</td>\n",
       "      <td>0.760000</td>\n",
       "      <td>0.067336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>36</td>\n",
       "      <td>0.747273</td>\n",
       "      <td>0.708333</td>\n",
       "      <td>0.067336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0.747882</td>\n",
       "      <td>0.719048</td>\n",
       "      <td>0.065011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0.736911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   param_RF__n_estimators param_RF__criterion param_RF__max_depth  \\\n",
       "19                   1000                gini                   5   \n",
       "24                    100                gini                   5   \n",
       "22                   1000                gini                   5   \n",
       "21                    100                gini                   5   \n",
       "18                    100                gini                   5   \n",
       "25                   1000                gini                   5   \n",
       "48                    100             entropy                   5   \n",
       "20                   5000                gini                   5   \n",
       "51                    100             entropy                   5   \n",
       "23                   5000                gini                   5   \n",
       "45                    100             entropy                   5   \n",
       "26                   5000                gini                   5   \n",
       "46                   1000             entropy                   5   \n",
       "49                   1000             entropy                   5   \n",
       "47                   5000             entropy                   5   \n",
       "50                   5000             entropy                   5   \n",
       "53                   5000             entropy                   5   \n",
       "52                   1000             entropy                   5   \n",
       "12                    100                gini                   3   \n",
       "17                   5000                gini                   3   \n",
       "14                   5000                gini                   3   \n",
       "13                   1000                gini                   3   \n",
       "11                   5000                gini                   3   \n",
       "10                   1000                gini                   3   \n",
       "16                   1000                gini                   3   \n",
       "15                    100                gini                   3   \n",
       "9                     100                gini                   3   \n",
       "42                    100             entropy                   3   \n",
       "41                   5000             entropy                   3   \n",
       "44                   5000             entropy                   3   \n",
       "43                   1000             entropy                   3   \n",
       "38                   5000             entropy                   3   \n",
       "40                   1000             entropy                   3   \n",
       "37                   1000             entropy                   3   \n",
       "39                    100             entropy                   3   \n",
       "36                    100             entropy                   3   \n",
       "3                     100                gini                   1   \n",
       "5                    5000                gini                   1   \n",
       "6                     100                gini                   1   \n",
       "7                    1000                gini                   1   \n",
       "1                    1000                gini                   1   \n",
       "2                    5000                gini                   1   \n",
       "4                    1000                gini                   1   \n",
       "35                   5000             entropy                   1   \n",
       "33                    100             entropy                   1   \n",
       "32                   5000             entropy                   1   \n",
       "31                   1000             entropy                   1   \n",
       "30                    100             entropy                   1   \n",
       "29                   5000             entropy                   1   \n",
       "28                   1000             entropy                   1   \n",
       "27                    100             entropy                   1   \n",
       "8                    5000                gini                   1   \n",
       "34                   1000             entropy                   1   \n",
       "0                     100                gini                   1   \n",
       "\n",
       "   param_RF__min_samples_split  rank_test_accuracy  mean_test_accuracy  \\\n",
       "19                           2                   1            0.760669   \n",
       "24                          10                   4            0.758836   \n",
       "22                           5                   6            0.758230   \n",
       "21                           5                  14            0.756397   \n",
       "18                           2                  17            0.755185   \n",
       "25                          10                   3            0.758843   \n",
       "48                           5                   2            0.759438   \n",
       "20                           2                  12            0.757010   \n",
       "51                          10                   9            0.757624   \n",
       "23                           5                  13            0.756404   \n",
       "45                           2                  15            0.756390   \n",
       "26                          10                  18            0.755185   \n",
       "46                           2                   7            0.758222   \n",
       "49                           5                   5            0.758825   \n",
       "47                           2                  10            0.757613   \n",
       "50                           5                  10            0.757613   \n",
       "53                          10                   7            0.758222   \n",
       "52                          10                  16            0.755787   \n",
       "12                           5                  19            0.750935   \n",
       "17                          10                  24            0.750322   \n",
       "14                           5                  24            0.750322   \n",
       "13                           5                  20            0.750928   \n",
       "11                           2                  20            0.750928   \n",
       "10                           2                  20            0.750928   \n",
       "16                          10                  20            0.750928   \n",
       "15                          10                  26            0.749715   \n",
       "9                            2                  27            0.749106   \n",
       "42                          10                  34            0.747882   \n",
       "41                           5                  28            0.749102   \n",
       "44                          10                  28            0.749102   \n",
       "43                          10                  28            0.749102   \n",
       "38                           2                  28            0.749102   \n",
       "40                           5                  28            0.749102   \n",
       "37                           2                  33            0.748492   \n",
       "39                           5                  36            0.747273   \n",
       "36                           2                  34            0.747882   \n",
       "3                            5                  37            0.736911   \n",
       "5                            5                  37            0.736911   \n",
       "6                           10                  37            0.736911   \n",
       "7                           10                  37            0.736911   \n",
       "1                            2                  37            0.736911   \n",
       "2                            2                  37            0.736911   \n",
       "4                            5                  37            0.736911   \n",
       "35                          10                  37            0.736911   \n",
       "33                          10                  37            0.736911   \n",
       "32                           5                  37            0.736911   \n",
       "31                           5                  37            0.736911   \n",
       "30                           5                  37            0.736911   \n",
       "29                           2                  37            0.736911   \n",
       "28                           2                  37            0.736911   \n",
       "27                           2                  37            0.736911   \n",
       "8                           10                  37            0.736911   \n",
       "34                          10                  37            0.736911   \n",
       "0                            2                  37            0.736911   \n",
       "\n",
       "    mean_test_precision  mean_test_recall  \n",
       "19             0.645204          0.199154  \n",
       "24             0.635925          0.194450  \n",
       "22             0.630767          0.192230  \n",
       "21             0.621483          0.192178  \n",
       "18             0.617306          0.189852  \n",
       "25             0.644370          0.187579  \n",
       "48             0.646655          0.185254  \n",
       "20             0.628730          0.185201  \n",
       "51             0.635850          0.180708  \n",
       "23             0.629466          0.180603  \n",
       "45             0.633811          0.180550  \n",
       "26             0.622729          0.178277  \n",
       "46             0.662896          0.171353  \n",
       "49             0.669440          0.171300  \n",
       "47             0.655124          0.169027  \n",
       "50             0.659886          0.166755  \n",
       "53             0.662827          0.166755  \n",
       "52             0.640957          0.164429  \n",
       "12             0.685714          0.095190  \n",
       "17             0.680833          0.095137  \n",
       "14             0.680833          0.095137  \n",
       "13             0.697500          0.095137  \n",
       "11             0.697500          0.095137  \n",
       "10             0.697500          0.095137  \n",
       "16             0.697500          0.095137  \n",
       "15             0.650714          0.092865  \n",
       "9              0.642381          0.090539  \n",
       "42             0.715476          0.069662  \n",
       "41             0.763333          0.069662  \n",
       "44             0.763333          0.069662  \n",
       "43             0.767143          0.069662  \n",
       "38             0.763333          0.069662  \n",
       "40             0.767143          0.069662  \n",
       "37             0.760000          0.067336  \n",
       "39             0.708333          0.067336  \n",
       "36             0.719048          0.065011  \n",
       "3              0.000000          0.000000  \n",
       "5              0.000000          0.000000  \n",
       "6              0.000000          0.000000  \n",
       "7              0.000000          0.000000  \n",
       "1              0.000000          0.000000  \n",
       "2              0.000000          0.000000  \n",
       "4              0.000000          0.000000  \n",
       "35             0.000000          0.000000  \n",
       "33             0.000000          0.000000  \n",
       "32             0.000000          0.000000  \n",
       "31             0.000000          0.000000  \n",
       "30             0.000000          0.000000  \n",
       "29             0.000000          0.000000  \n",
       "28             0.000000          0.000000  \n",
       "27             0.000000          0.000000  \n",
       "8              0.000000          0.000000  \n",
       "34             0.000000          0.000000  \n",
       "0              0.000000          0.000000  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test =  train_test_split(full_features, threshold_high, \n",
    "                                                        test_size=0.2, random_state=0)\n",
    "\n",
    "GRID = {'RF__n_estimators': [100, 1000, 5000], 'RF__criterion': ['gini', 'entropy'], 'RF__max_depth': [1, 3, 5], \n",
    "                      'RF__min_samples_split': [2,5,10], 'RF__random_state': [0]}\n",
    "\n",
    "pipe = Pipeline([('RF', RandomForestClassifier())])\n",
    "grid_model = GridSearchCV(estimator=pipe,\n",
    "                          param_grid=GRID,\n",
    "                          cv=10,\n",
    "                          return_train_score=True,\n",
    "                          refit='recall',\n",
    "                          scoring=('accuracy', 'precision', 'recall')\n",
    ")\n",
    "\n",
    "\n",
    "grid_model = grid_model.fit(x_train, np.ravel(y_train))\n",
    "predicted_y = grid_model.predict(x_test)\n",
    "cv_results = pd.DataFrame(grid_model.cv_results_)\n",
    "ranked_cv=cv_results.sort_values(by=['rank_test_recall'])\n",
    "ranked_cv[['param_RF__n_estimators', 'param_RF__criterion', 'param_RF__max_depth', 'param_RF__min_samples_split', 'rank_test_accuracy',\n",
    "           'mean_test_accuracy', 'mean_test_precision', 'mean_test_recall']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test =  train_test_split(full_features, threshold_high, \n",
    "                                                        test_size=0.2, random_state=0)\n",
    "best_high = RandomForestClassifier(criterion='gini', max_depth=5, min_samples_split=2,\n",
    "                                    n_estimators=1000, random_state=0)\n",
    "best_high = best_high.fit(x_train, np.ravel(y_train))\n",
    "best_high_predicted = best_high.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importances = best_high.feature_importances_[:10]\n",
    "\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "# Sort the labels in a corresponding fashion\n",
    "labels = x_train.columns.values\n",
    "names = [labels[i] for i in indices]\n",
    "\n",
    "#len(importances)\n",
    "# Plot\n",
    "sns.set(rc={'figure.figsize':(20, 10)})\n",
    "plt.figure()\n",
    "plt.barh(range(len(importances)),importances[indices])\n",
    "plt.yticks(range(len(importances)), names)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Test Accuracy: 0.7689\n",
      "Test Precision: 0.6829\n",
      "Test Recall: 0.2545\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt # Don't overwrite plt !\n",
    "from sklearn.metrics import plot_confusion_matrix, accuracy_score, precision_score, recall_score\n",
    "\n",
    "cm = plot_confusion_matrix(\n",
    "    estimator=best_high, \n",
    "    X=x_test, y_true=y_test, labels=[1,0], \n",
    "    display_labels=['High Lead Results', 'No High Lead Results'])\n",
    "plt.grid(linestyle='')\n",
    "plt.title('Confusion Matrix for Predicting Block Groups with Lead Results 15.0+ ppb\\n' + \n",
    "         '(on testing data, among block groups with lead test results)')\n",
    "plt.show()\n",
    "\n",
    "accuracy = accuracy_score(y_true=y_test, y_pred=best_high_predicted)\n",
    "precision = precision_score(y_true=y_test, y_pred=best_high_predicted)\n",
    "recall = recall_score(y_true=y_test, y_pred=best_high_predicted)\n",
    "\n",
    "print(f'''\n",
    "Test Accuracy: {round(accuracy, 4)}\n",
    "Test Precision: {round(precision, 4)}\n",
    "Test Recall: {round(recall, 4)}\n",
    "''')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### WEIGHTED RANDOM FOREST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>param_RF__n_estimators</th>\n",
       "      <th>param_RF__criterion</th>\n",
       "      <th>param_RF__max_depth</th>\n",
       "      <th>param_RF__min_samples_split</th>\n",
       "      <th>param_RF__class_weight</th>\n",
       "      <th>rank_test_recall</th>\n",
       "      <th>mean_test_accuracy</th>\n",
       "      <th>mean_test_precision</th>\n",
       "      <th>mean_test_recall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>balanced_subsample</td>\n",
       "      <td>1</td>\n",
       "      <td>0.655325</td>\n",
       "      <td>0.416855</td>\n",
       "      <td>0.756818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>balanced_subsample</td>\n",
       "      <td>1</td>\n",
       "      <td>0.655325</td>\n",
       "      <td>0.416855</td>\n",
       "      <td>0.756818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>balanced_subsample</td>\n",
       "      <td>1</td>\n",
       "      <td>0.655325</td>\n",
       "      <td>0.416855</td>\n",
       "      <td>0.756818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>balanced</td>\n",
       "      <td>4</td>\n",
       "      <td>0.655928</td>\n",
       "      <td>0.416951</td>\n",
       "      <td>0.754493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>balanced</td>\n",
       "      <td>4</td>\n",
       "      <td>0.655928</td>\n",
       "      <td>0.416951</td>\n",
       "      <td>0.754493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>balanced</td>\n",
       "      <td>104</td>\n",
       "      <td>0.707099</td>\n",
       "      <td>0.459504</td>\n",
       "      <td>0.648203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>balanced</td>\n",
       "      <td>105</td>\n",
       "      <td>0.708322</td>\n",
       "      <td>0.461964</td>\n",
       "      <td>0.641279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>balanced</td>\n",
       "      <td>106</td>\n",
       "      <td>0.706493</td>\n",
       "      <td>0.459671</td>\n",
       "      <td>0.638953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>balanced_subsample</td>\n",
       "      <td>107</td>\n",
       "      <td>0.712594</td>\n",
       "      <td>0.467072</td>\n",
       "      <td>0.636681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>balanced</td>\n",
       "      <td>108</td>\n",
       "      <td>0.710144</td>\n",
       "      <td>0.463015</td>\n",
       "      <td>0.632082</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>108 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   param_RF__n_estimators param_RF__criterion param_RF__max_depth  \\\n",
       "83                   5000             entropy                   1   \n",
       "89                   5000             entropy                   1   \n",
       "86                   5000             entropy                   1   \n",
       "32                   5000             entropy                   1   \n",
       "35                   5000             entropy                   1   \n",
       "..                    ...                 ...                 ...   \n",
       "25                   1000                gini                   5   \n",
       "18                    100                gini                   5   \n",
       "24                    100                gini                   5   \n",
       "72                    100                gini                   5   \n",
       "21                    100                gini                   5   \n",
       "\n",
       "   param_RF__min_samples_split param_RF__class_weight  rank_test_recall  \\\n",
       "83                           2     balanced_subsample                 1   \n",
       "89                          10     balanced_subsample                 1   \n",
       "86                           5     balanced_subsample                 1   \n",
       "32                           5               balanced                 4   \n",
       "35                          10               balanced                 4   \n",
       "..                         ...                    ...               ...   \n",
       "25                          10               balanced               104   \n",
       "18                           2               balanced               105   \n",
       "24                          10               balanced               106   \n",
       "72                           2     balanced_subsample               107   \n",
       "21                           5               balanced               108   \n",
       "\n",
       "    mean_test_accuracy  mean_test_precision  mean_test_recall  \n",
       "83            0.655325             0.416855          0.756818  \n",
       "89            0.655325             0.416855          0.756818  \n",
       "86            0.655325             0.416855          0.756818  \n",
       "32            0.655928             0.416951          0.754493  \n",
       "35            0.655928             0.416951          0.754493  \n",
       "..                 ...                  ...               ...  \n",
       "25            0.707099             0.459504          0.648203  \n",
       "18            0.708322             0.461964          0.641279  \n",
       "24            0.706493             0.459671          0.638953  \n",
       "72            0.712594             0.467072          0.636681  \n",
       "21            0.710144             0.463015          0.632082  \n",
       "\n",
       "[108 rows x 9 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test =  train_test_split(full_features, threshold_high, \n",
    "                                                        test_size=0.2, random_state=0)\n",
    "\n",
    "GRID = {'RF__n_estimators': [100, 1000, 5000], 'RF__criterion': ['gini', 'entropy'], 'RF__max_depth': [1, 3, 5], \n",
    "                      'RF__min_samples_split': [2,5,10], 'RF__random_state': [0], \n",
    "                      'RF__class_weight': ['balanced', 'balanced_subsample']}\n",
    "\n",
    "pipe = Pipeline([('RF', RandomForestClassifier())])\n",
    "grid_model = GridSearchCV(estimator=pipe,\n",
    "                          param_grid=GRID,\n",
    "                          cv=10,\n",
    "                          return_train_score=True,\n",
    "                          refit='accuracy',\n",
    "                          scoring=('accuracy', 'precision', 'recall')\n",
    ")\n",
    "\n",
    "\n",
    "grid_model = grid_model.fit(x_train, np.ravel(y_train))\n",
    "predicted_y = grid_model.predict(x_test)\n",
    "cv_results = pd.DataFrame(grid_model.cv_results_)\n",
    "ranked_cv=cv_results.sort_values(by=['rank_test_recall'])\n",
    "ranked_cv[['param_RF__n_estimators', 'param_RF__criterion', 'param_RF__max_depth', 'param_RF__min_samples_split', \n",
    "           'param_RF__class_weight', 'rank_test_recall', 'mean_test_accuracy', 'mean_test_precision', 'mean_test_recall']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_weighted = RandomForestClassifier(criterion='entropy', max_depth=1, min_samples_split=2,\n",
    "                                    n_estimators=5000, class_weight='balanced_subsample', random_state=0)\n",
    "best_weighted = best_weighted.fit(x_train, y_train)\n",
    "best_weight_predicted = best_weighted.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importances = best_weighted.feature_importances_[:10]\n",
    "\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "# Sort the labels in a corresponding fashion\n",
    "labels = x_train.columns.values\n",
    "names = [labels[i] for i in indices]\n",
    "\n",
    "# Plot\n",
    "sns.set(rc={'figure.figsize':(20, 10)})\n",
    "plt.figure()\n",
    "plt.barh(range(len(importances)),importances[indices])\n",
    "plt.yticks(range(len(importances)), names)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Test Accuracy: 0.6521\n",
      "Test Precision: 0.4218\n",
      "Test Recall: 0.8091\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt # Don't overwrite plt !\n",
    "from sklearn.metrics import plot_confusion_matrix, accuracy_score, precision_score, recall_score\n",
    "\n",
    "cm = plot_confusion_matrix(\n",
    "    estimator=best_weighted, \n",
    "    X=x_test, y_true=y_test, labels=[1,0], \n",
    "    display_labels=['High Lead Results', 'No High Lead Results'])\n",
    "plt.grid(linestyle='')\n",
    "plt.title('Confusion Matrix for Predicting Block Groups with Lead Results 15.0+ ppb\\n' + \n",
    "         '(on testing data, among block groups with lead test results)')\n",
    "plt.show()\n",
    "\n",
    "accuracy = accuracy_score(y_true=y_test, y_pred=best_weight_predicted)\n",
    "precision = precision_score(y_true=y_test, y_pred=best_weight_predicted)\n",
    "recall = recall_score(y_true=y_test, y_pred=best_weight_predicted)\n",
    "\n",
    "print(f'''\n",
    "Test Accuracy: {round(accuracy, 4)}\n",
    "Test Precision: {round(precision, 4)}\n",
    "Test Recall: {round(recall, 4)}\n",
    "''')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RANDOM FOREST w/ SMOTE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>param_RF__n_estimators</th>\n",
       "      <th>param_RF__criterion</th>\n",
       "      <th>param_RF__max_depth</th>\n",
       "      <th>param_RF__min_samples_split</th>\n",
       "      <th>rank_test_recall</th>\n",
       "      <th>mean_test_accuracy</th>\n",
       "      <th>mean_test_precision</th>\n",
       "      <th>mean_test_recall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.668725</td>\n",
       "      <td>0.423458</td>\n",
       "      <td>0.699101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.668725</td>\n",
       "      <td>0.423458</td>\n",
       "      <td>0.699101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0.668725</td>\n",
       "      <td>0.423458</td>\n",
       "      <td>0.699101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0.670554</td>\n",
       "      <td>0.423503</td>\n",
       "      <td>0.682875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0.670554</td>\n",
       "      <td>0.423503</td>\n",
       "      <td>0.682875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0.670554</td>\n",
       "      <td>0.423503</td>\n",
       "      <td>0.682875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0.666899</td>\n",
       "      <td>0.420754</td>\n",
       "      <td>0.678013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>0.666899</td>\n",
       "      <td>0.420754</td>\n",
       "      <td>0.678013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0.666899</td>\n",
       "      <td>0.420754</td>\n",
       "      <td>0.678013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>0.668115</td>\n",
       "      <td>0.421757</td>\n",
       "      <td>0.677960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>0.668115</td>\n",
       "      <td>0.421757</td>\n",
       "      <td>0.677960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0.668115</td>\n",
       "      <td>0.421757</td>\n",
       "      <td>0.677960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>0.696116</td>\n",
       "      <td>0.449056</td>\n",
       "      <td>0.662051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>14</td>\n",
       "      <td>0.697332</td>\n",
       "      <td>0.450569</td>\n",
       "      <td>0.661998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>0.670558</td>\n",
       "      <td>0.423181</td>\n",
       "      <td>0.661839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>0.670558</td>\n",
       "      <td>0.423181</td>\n",
       "      <td>0.661839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>0.670558</td>\n",
       "      <td>0.423181</td>\n",
       "      <td>0.661839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>0.698548</td>\n",
       "      <td>0.451655</td>\n",
       "      <td>0.659672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>0.671175</td>\n",
       "      <td>0.423242</td>\n",
       "      <td>0.659619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>0.671175</td>\n",
       "      <td>0.423242</td>\n",
       "      <td>0.659619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>0.671175</td>\n",
       "      <td>0.423242</td>\n",
       "      <td>0.659619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "      <td>0.697332</td>\n",
       "      <td>0.449422</td>\n",
       "      <td>0.652801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>22</td>\n",
       "      <td>0.697942</td>\n",
       "      <td>0.449960</td>\n",
       "      <td>0.652801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>22</td>\n",
       "      <td>0.697942</td>\n",
       "      <td>0.449960</td>\n",
       "      <td>0.652801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>0.695499</td>\n",
       "      <td>0.446290</td>\n",
       "      <td>0.650423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>25</td>\n",
       "      <td>0.695503</td>\n",
       "      <td>0.446394</td>\n",
       "      <td>0.650423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>0.695503</td>\n",
       "      <td>0.446466</td>\n",
       "      <td>0.650423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "      <td>0.698555</td>\n",
       "      <td>0.449762</td>\n",
       "      <td>0.648097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>28</td>\n",
       "      <td>0.699771</td>\n",
       "      <td>0.451068</td>\n",
       "      <td>0.648097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>0.699161</td>\n",
       "      <td>0.450584</td>\n",
       "      <td>0.648097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>31</td>\n",
       "      <td>0.700377</td>\n",
       "      <td>0.450832</td>\n",
       "      <td>0.643499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>31</td>\n",
       "      <td>0.700987</td>\n",
       "      <td>0.451579</td>\n",
       "      <td>0.643499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>31</td>\n",
       "      <td>0.700377</td>\n",
       "      <td>0.450832</td>\n",
       "      <td>0.643499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "      <td>0.699161</td>\n",
       "      <td>0.449497</td>\n",
       "      <td>0.643446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0.697942</td>\n",
       "      <td>0.447930</td>\n",
       "      <td>0.643446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>34</td>\n",
       "      <td>0.698551</td>\n",
       "      <td>0.448677</td>\n",
       "      <td>0.643446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>37</td>\n",
       "      <td>0.711944</td>\n",
       "      <td>0.465238</td>\n",
       "      <td>0.634249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>38</td>\n",
       "      <td>0.714993</td>\n",
       "      <td>0.468765</td>\n",
       "      <td>0.627326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>39</td>\n",
       "      <td>0.708914</td>\n",
       "      <td>0.460074</td>\n",
       "      <td>0.620455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>0.713784</td>\n",
       "      <td>0.467493</td>\n",
       "      <td>0.620402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>41</td>\n",
       "      <td>0.710717</td>\n",
       "      <td>0.462469</td>\n",
       "      <td>0.620349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>100</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>42</td>\n",
       "      <td>0.711341</td>\n",
       "      <td>0.463633</td>\n",
       "      <td>0.618129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>43</td>\n",
       "      <td>0.713174</td>\n",
       "      <td>0.465881</td>\n",
       "      <td>0.615803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>0.710735</td>\n",
       "      <td>0.462447</td>\n",
       "      <td>0.615751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>0.707694</td>\n",
       "      <td>0.459095</td>\n",
       "      <td>0.615751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>100</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>46</td>\n",
       "      <td>0.711948</td>\n",
       "      <td>0.464286</td>\n",
       "      <td>0.613478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>46</td>\n",
       "      <td>0.711345</td>\n",
       "      <td>0.462870</td>\n",
       "      <td>0.613478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>5000</td>\n",
       "      <td>entropy</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>48</td>\n",
       "      <td>0.708906</td>\n",
       "      <td>0.459819</td>\n",
       "      <td>0.611152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>49</td>\n",
       "      <td>0.714390</td>\n",
       "      <td>0.467268</td>\n",
       "      <td>0.611099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>49</td>\n",
       "      <td>0.712565</td>\n",
       "      <td>0.464672</td>\n",
       "      <td>0.611099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>0.713171</td>\n",
       "      <td>0.465311</td>\n",
       "      <td>0.608774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>52</td>\n",
       "      <td>0.710140</td>\n",
       "      <td>0.461155</td>\n",
       "      <td>0.604281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>0.711959</td>\n",
       "      <td>0.463331</td>\n",
       "      <td>0.604228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1000</td>\n",
       "      <td>gini</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>53</td>\n",
       "      <td>0.712572</td>\n",
       "      <td>0.464418</td>\n",
       "      <td>0.604228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   param_RF__n_estimators param_RF__criterion param_RF__max_depth  \\\n",
       "27                    100             entropy                   1   \n",
       "30                    100             entropy                   1   \n",
       "33                    100             entropy                   1   \n",
       "0                     100                gini                   1   \n",
       "3                     100                gini                   1   \n",
       "6                     100                gini                   1   \n",
       "29                   5000             entropy                   1   \n",
       "32                   5000             entropy                   1   \n",
       "35                   5000             entropy                   1   \n",
       "34                   1000             entropy                   1   \n",
       "31                   1000             entropy                   1   \n",
       "28                   1000             entropy                   1   \n",
       "36                    100             entropy                   3   \n",
       "39                    100             entropy                   3   \n",
       "5                    5000                gini                   1   \n",
       "2                    5000                gini                   1   \n",
       "8                    5000                gini                   1   \n",
       "42                    100             entropy                   3   \n",
       "7                    1000                gini                   1   \n",
       "4                    1000                gini                   1   \n",
       "1                    1000                gini                   1   \n",
       "38                   5000             entropy                   3   \n",
       "41                   5000             entropy                   3   \n",
       "44                   5000             entropy                   3   \n",
       "40                   1000             entropy                   3   \n",
       "43                   1000             entropy                   3   \n",
       "37                   1000             entropy                   3   \n",
       "9                     100                gini                   3   \n",
       "12                    100                gini                   3   \n",
       "15                    100                gini                   3   \n",
       "11                   5000                gini                   3   \n",
       "14                   5000                gini                   3   \n",
       "17                   5000                gini                   3   \n",
       "13                   1000                gini                   3   \n",
       "10                   1000                gini                   3   \n",
       "16                   1000                gini                   3   \n",
       "51                    100             entropy                   5   \n",
       "18                    100                gini                   5   \n",
       "45                    100             entropy                   5   \n",
       "52                   1000             entropy                   5   \n",
       "24                    100                gini                   5   \n",
       "48                    100             entropy                   5   \n",
       "49                   1000             entropy                   5   \n",
       "47                   5000             entropy                   5   \n",
       "46                   1000             entropy                   5   \n",
       "21                    100                gini                   5   \n",
       "50                   5000             entropy                   5   \n",
       "53                   5000             entropy                   5   \n",
       "20                   5000                gini                   5   \n",
       "26                   5000                gini                   5   \n",
       "23                   5000                gini                   5   \n",
       "19                   1000                gini                   5   \n",
       "22                   1000                gini                   5   \n",
       "25                   1000                gini                   5   \n",
       "\n",
       "   param_RF__min_samples_split  rank_test_recall  mean_test_accuracy  \\\n",
       "27                           2                 1            0.668725   \n",
       "30                           5                 1            0.668725   \n",
       "33                          10                 1            0.668725   \n",
       "0                            2                 4            0.670554   \n",
       "3                            5                 4            0.670554   \n",
       "6                           10                 4            0.670554   \n",
       "29                           2                 7            0.666899   \n",
       "32                           5                 7            0.666899   \n",
       "35                          10                 7            0.666899   \n",
       "34                          10                10            0.668115   \n",
       "31                           5                10            0.668115   \n",
       "28                           2                10            0.668115   \n",
       "36                           2                13            0.696116   \n",
       "39                           5                14            0.697332   \n",
       "5                            5                15            0.670558   \n",
       "2                            2                15            0.670558   \n",
       "8                           10                15            0.670558   \n",
       "42                          10                18            0.698548   \n",
       "7                           10                19            0.671175   \n",
       "4                            5                19            0.671175   \n",
       "1                            2                19            0.671175   \n",
       "38                           2                22            0.697332   \n",
       "41                           5                22            0.697942   \n",
       "44                          10                22            0.697942   \n",
       "40                           5                25            0.695499   \n",
       "43                          10                25            0.695503   \n",
       "37                           2                25            0.695503   \n",
       "9                            2                28            0.698555   \n",
       "12                           5                28            0.699771   \n",
       "15                          10                28            0.699161   \n",
       "11                           2                31            0.700377   \n",
       "14                           5                31            0.700987   \n",
       "17                          10                31            0.700377   \n",
       "13                           5                34            0.699161   \n",
       "10                           2                34            0.697942   \n",
       "16                          10                34            0.698551   \n",
       "51                          10                37            0.711944   \n",
       "18                           2                38            0.714993   \n",
       "45                           2                39            0.708914   \n",
       "52                          10                40            0.713784   \n",
       "24                          10                41            0.710717   \n",
       "48                           5                42            0.711341   \n",
       "49                           5                43            0.713174   \n",
       "47                           2                44            0.710735   \n",
       "46                           2                44            0.707694   \n",
       "21                           5                46            0.711948   \n",
       "50                           5                46            0.711345   \n",
       "53                          10                48            0.708906   \n",
       "20                           2                49            0.714390   \n",
       "26                          10                49            0.712565   \n",
       "23                           5                51            0.713171   \n",
       "19                           2                52            0.710140   \n",
       "22                           5                53            0.711959   \n",
       "25                          10                53            0.712572   \n",
       "\n",
       "    mean_test_precision  mean_test_recall  \n",
       "27             0.423458          0.699101  \n",
       "30             0.423458          0.699101  \n",
       "33             0.423458          0.699101  \n",
       "0              0.423503          0.682875  \n",
       "3              0.423503          0.682875  \n",
       "6              0.423503          0.682875  \n",
       "29             0.420754          0.678013  \n",
       "32             0.420754          0.678013  \n",
       "35             0.420754          0.678013  \n",
       "34             0.421757          0.677960  \n",
       "31             0.421757          0.677960  \n",
       "28             0.421757          0.677960  \n",
       "36             0.449056          0.662051  \n",
       "39             0.450569          0.661998  \n",
       "5              0.423181          0.661839  \n",
       "2              0.423181          0.661839  \n",
       "8              0.423181          0.661839  \n",
       "42             0.451655          0.659672  \n",
       "7              0.423242          0.659619  \n",
       "4              0.423242          0.659619  \n",
       "1              0.423242          0.659619  \n",
       "38             0.449422          0.652801  \n",
       "41             0.449960          0.652801  \n",
       "44             0.449960          0.652801  \n",
       "40             0.446290          0.650423  \n",
       "43             0.446394          0.650423  \n",
       "37             0.446466          0.650423  \n",
       "9              0.449762          0.648097  \n",
       "12             0.451068          0.648097  \n",
       "15             0.450584          0.648097  \n",
       "11             0.450832          0.643499  \n",
       "14             0.451579          0.643499  \n",
       "17             0.450832          0.643499  \n",
       "13             0.449497          0.643446  \n",
       "10             0.447930          0.643446  \n",
       "16             0.448677          0.643446  \n",
       "51             0.465238          0.634249  \n",
       "18             0.468765          0.627326  \n",
       "45             0.460074          0.620455  \n",
       "52             0.467493          0.620402  \n",
       "24             0.462469          0.620349  \n",
       "48             0.463633          0.618129  \n",
       "49             0.465881          0.615803  \n",
       "47             0.462447          0.615751  \n",
       "46             0.459095          0.615751  \n",
       "21             0.464286          0.613478  \n",
       "50             0.462870          0.613478  \n",
       "53             0.459819          0.611152  \n",
       "20             0.467268          0.611099  \n",
       "26             0.464672          0.611099  \n",
       "23             0.465311          0.608774  \n",
       "19             0.461155          0.604281  \n",
       "22             0.463331          0.604228  \n",
       "25             0.464418          0.604228  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from imblearn.pipeline import Pipeline\n",
    "from imblearn.over_sampling import SMOTE\n",
    "\n",
    "x_train, x_test, y_train, y_test =  train_test_split(full_features, threshold_high, \n",
    "                                                        test_size=0.2, random_state=0)\n",
    "\n",
    "GRID = {'RF__n_estimators': [100, 1000, 5000], 'RF__criterion': ['gini', 'entropy'], 'RF__max_depth': [1, 3, 5], \n",
    "                      'RF__min_samples_split': [2,5,10], 'RF__random_state': [0]}\n",
    "\n",
    "pipe = Pipeline([('SM', SMOTE(random_state=0)),\n",
    "                ('RF', RandomForestClassifier())])\n",
    "grid_model = GridSearchCV(estimator=pipe,\n",
    "                          param_grid=GRID,\n",
    "                          cv=10,\n",
    "                          return_train_score=True,\n",
    "                          refit='recall',\n",
    "                          scoring=('accuracy', 'precision', 'recall')\n",
    ")\n",
    "\n",
    "\n",
    "grid_model = grid_model.fit(x_train, np.ravel(y_train))\n",
    "predicted_y = grid_model.predict(x_test)\n",
    "cv_results = pd.DataFrame(grid_model.cv_results_)\n",
    "ranked_cv=cv_results.sort_values(by=['rank_test_recall'])\n",
    "ranked_cv[['param_RF__n_estimators', 'param_RF__criterion', 'param_RF__max_depth', 'param_RF__min_samples_split', 'rank_test_recall',\n",
    "           'mean_test_accuracy', 'mean_test_precision', 'mean_test_recall']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_smote = RandomForestClassifier(criterion='entropy', max_depth=1, min_samples_split=2,\n",
    "                                    n_estimators=100, random_state=0)\n",
    "best_smote = best_smote.fit(x_train, np.ravel(y_train))\n",
    "best_smote_predicted = best_smote.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importances = best_smote.feature_importances_[:10]\n",
    "\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "# Sort the labels in a corresponding fashion\n",
    "labels = x_train.columns.values\n",
    "names = [labels[i] for i in indices]\n",
    "\n",
    "# Plot\n",
    "sns.set(rc={'figure.figsize':(20, 10)})\n",
    "plt.figure()\n",
    "plt.barh(range(len(importances)),importances[indices])\n",
    "plt.yticks(range(len(importances)), names)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### POLICY RECOMMENDATIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-16-d79f32ae0fc4>:6: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  best_high = best_high.fit(x_train, y_train)\n"
     ]
    }
   ],
   "source": [
    "#Model to be used for prioritization predictions\n",
    "x_train, x_test, y_train, y_test =  train_test_split(full_features, threshold_high, \n",
    "                                                        test_size=0.2, random_state=0)\n",
    "best_high = RandomForestClassifier(criterion='gini', max_depth=5, min_samples_split=2,\n",
    "                                    n_estimators=1000, random_state=0)\n",
    "best_high = best_high.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_data = pd.read_csv('data/final_assessments_block_group.csv', sep='\\t')\n",
    "\n",
    "block_geo = gpd.read_file('data/Boundaries - Census Blocks - 2010.geojson')\n",
    "block_geo.head()\n",
    "block_geo['Block Group'] = block_geo['geoid10'].map(lambda x: str(x)[:12])\n",
    "bg_geo = block_geo.dissolve(by='Block Group')\n",
    "\n",
    "full_data['GEOID'] = full_data['GEOID'].astype(str)\n",
    "full_geo = full_data.iloc[:, 1:].merge(bg_geo.loc[:, \"geometry\"], left_on='GEOID', right_index=True)\n",
    "\n",
    "geometries = pd.DataFrame(full_geo['geometry'], index=full_geo.index)\n",
    "full_geo.drop(labels=['GEOID', 'geometry'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "nans = []\n",
    "for col in full_geo.columns:\n",
    "    if len(full_geo.loc[full_geo[col].isna()]) >= 1:\n",
    "        nans.append(col)\n",
    "for col in nans:\n",
    "    full_geo[col].fillna(full_geo[col].median(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Likelihood of Lead Pipes by Block Group'}>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_high_predict = best_high.predict_proba(full_geo)\n",
    "for_map_rf = gpd.GeoDataFrame(pd.concat([geometries, pd.Series(best_high_predict[:,1])], axis=1))\n",
    "for_map_rf.columns=['geometry', 'Likelihood of Lead Pipes']\n",
    "\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "sns.set(rc={'figure.figsize':(12, 10)})\n",
    "sns.set_theme(style=\"white\")\n",
    "plt.title(\"Likelihood of Lead Pipes by Block Group\")\n",
    "for_map_rf.plot(column='Likelihood of Lead Pipes', ax=ax, legend=True,  cmap='Blues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Likelihood of Lead Pipes by Block Group'}>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_weighted_predict = best_weighted.predict_proba(full_geo)\n",
    "for_map_weighted = gpd.GeoDataFrame(pd.concat([geometries, pd.Series(best_weighted_predict[:,1])], axis=1))\n",
    "for_map_weighted.columns=['geometry', 'Likelihood of Lead Pipes']\n",
    "\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "sns.set(rc={'figure.figsize':(12, 10)})\n",
    "sns.set_theme(style=\"white\")\n",
    "plt.title(\"Likelihood of Lead Pipes by Block Group\")\n",
    "for_map_weighted.plot(column='Likelihood of Lead Pipes', ax=ax, legend=True,  cmap='Blues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Likelihood of Lead Pipes by Block Group'}>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_smote_predict = best_smote.predict_proba(full_geo)\n",
    "for_map_smote = gpd.GeoDataFrame(pd.concat([geometries, pd.Series(best_smote_predict[:,1])], axis=1))\n",
    "for_map_smote.columns=['geometry', 'Likelihood of Lead Pipes']\n",
    "\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "sns.set(rc={'figure.figsize':(12, 10)})\n",
    "sns.set_theme(style=\"white\")\n",
    "plt.title(\"Likelihood of Lead Pipes by Block Group\")\n",
    "for_map_smote.plot(column='Likelihood of Lead Pipes', ax=ax, legend=True,  cmap='Blues')"
   ]
  }
 ],
 "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
}