diff --git "a/Feature Selection.ipynb" "b/Feature Selection.ipynb"
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h1>Feature Selection</h1>\n",
+    "<p><b>Last Time: </b>\n",
+    "<p>Supervised vs. Unsupervised Learning: https://youtu.be/2Z1B0xESzMw\n",
+    "<p>Intro to Case-Based Reasoning:https://youtu.be/Iy2gO8svdMI\n",
+    "<p>Intro to kNN: https://youtu.be/SDSC4yLLBKM\n",
+    "<p><b>Today:</b>\n",
+    "<p>Finding relationships between features\n",
+    "<p>Feature selection using wrappers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>What's the Purpose of Feature Selection</h2>\n",
+    "<p>Many learning algorithms perform poorly on high-dimensional data. This is known as the <b>curse of dimensionality</b>\n",
+    "    <p>There are other reasons we may wish to reduce the number of features including:\n",
+    "        <p>1. Reducing computational cost\n",
+    "            <p>2. Reducing the cost associated with data collection\n",
+    "                <p>3. Improving Interpretability"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>Dataset: Boston Housing Data</h2>\n",
+    "\n",
+    "<p><b>Dependent Variable: MEDV:</b> Median value of owner-occupied homes in 1000's of dollars\n",
+    "<p><b>Explanatory Variables</b></p>\n",
+    "<p><b>CRIM:</b> per capita crime rate by town\n",
+    "<p><b>ZN:</b> proportion of residential land zoned for lots over 25,000 sq.ft.\n",
+    "<p><b>INDUS:</b> proportion of non-retail business acres per town\n",
+    "<p><b>CHAS:</b> Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
+    "<p><b>NOX:</b> nitric oxides concentration (parts per 10 million)\n",
+    "<p><b>RM:</b> average number of rooms per dwelling\n",
+    "<p><b>AGE:</b> proportion of owner-occupied units built prior to 1940\n",
+    "<p><b>DIS:</b> weighted distances to five Boston employment centres\n",
+    "<p><b>RAD:</b> index of accessibility to radial highways\n",
+    "<p><b>TAX:</b> full-value property-tax rate per 10,000 dollars\n",
+    "<p><b>PTRATIO:</b>  pupil-teacher ratio by town\n",
+    "<p><b>B:</b> 1000(Bk - 0.63)^2 where Bk is the proportion of black residents by town\n",
+    "<p><b>LSTAT:</b> lower status of the population\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.datasets import load_boston"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston_data=load_boston()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston = pd.DataFrame(boston_data.data, columns=boston_data.feature_names)\n",
+    "boston['MEDV'] = boston_data.target\n",
+    "dummies = pd.get_dummies(boston.RAD)\n",
+    "boston = boston.drop(columns='RAD').merge(dummies,left_index=True,right_index=True)\n",
+    "X = boston.drop(columns='MEDV')\n",
+    "y = boston.MEDV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "</style>\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>CRIM</th>\n",
+       "      <th>ZN</th>\n",
+       "      <th>INDUS</th>\n",
+       "      <th>CHAS</th>\n",
+       "      <th>NOX</th>\n",
+       "      <th>RM</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>DIS</th>\n",
+       "      <th>TAX</th>\n",
+       "      <th>PTRATIO</th>\n",
+       "      <th>...</th>\n",
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+       "      <td>61.1</td>\n",
+       "      <td>4.9671</td>\n",
+       "      <td>242.0</td>\n",
+       "      <td>17.8</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>0.524</td>\n",
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+       "      <td>311.0</td>\n",
+       "      <td>15.2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>22.9</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
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+       "      <td>...</td>\n",
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+       "      <td>0.524</td>\n",
+       "      <td>5.631</td>\n",
+       "      <td>100.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.524</td>\n",
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+       "      <td>15.2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18.9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 22 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      CRIM    ZN  INDUS  CHAS    NOX     RM    AGE     DIS    TAX  PTRATIO  \\\n",
+       "0  0.00632  18.0   2.31   0.0  0.538  6.575   65.2  4.0900  296.0     15.3   \n",
+       "1  0.02731   0.0   7.07   0.0  0.469  6.421   78.9  4.9671  242.0     17.8   \n",
+       "2  0.02729   0.0   7.07   0.0  0.469  7.185   61.1  4.9671  242.0     17.8   \n",
+       "3  0.03237   0.0   2.18   0.0  0.458  6.998   45.8  6.0622  222.0     18.7   \n",
+       "4  0.06905   0.0   2.18   0.0  0.458  7.147   54.2  6.0622  222.0     18.7   \n",
+       "5  0.02985   0.0   2.18   0.0  0.458  6.430   58.7  6.0622  222.0     18.7   \n",
+       "6  0.08829  12.5   7.87   0.0  0.524  6.012   66.6  5.5605  311.0     15.2   \n",
+       "7  0.14455  12.5   7.87   0.0  0.524  6.172   96.1  5.9505  311.0     15.2   \n",
+       "8  0.21124  12.5   7.87   0.0  0.524  5.631  100.0  6.0821  311.0     15.2   \n",
+       "9  0.17004  12.5   7.87   0.0  0.524  6.004   85.9  6.5921  311.0     15.2   \n",
+       "\n",
+       "   ...  MEDV  1.0  2.0  3.0  4.0  5.0  6.0  7.0  8.0  24.0  \n",
+       "0  ...  24.0    1    0    0    0    0    0    0    0     0  \n",
+       "1  ...  21.6    0    1    0    0    0    0    0    0     0  \n",
+       "2  ...  34.7    0    1    0    0    0    0    0    0     0  \n",
+       "3  ...  33.4    0    0    1    0    0    0    0    0     0  \n",
+       "4  ...  36.2    0    0    1    0    0    0    0    0     0  \n",
+       "5  ...  28.7    0    0    1    0    0    0    0    0     0  \n",
+       "6  ...  22.9    0    0    0    0    1    0    0    0     0  \n",
+       "7  ...  27.1    0    0    0    0    1    0    0    0     0  \n",
+       "8  ...  16.5    0    0    0    0    1    0    0    0     0  \n",
+       "9  ...  18.9    0    0    0    0    1    0    0    0     0  \n",
+       "\n",
+       "[10 rows x 22 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "boston.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>Last Time</h2>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 6.51\n",
+      "R_squared: 0.5\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/model_selection/_split.py:297: FutureWarning: Setting a random_state has no effect since shuffle is False. This will raise an error in 0.24. You should leave random_state to its default (None), or set shuffle=True.\n",
+      "  FutureWarning\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.pipeline import make_pipeline\n",
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.neighbors import KNeighborsRegressor\n",
+    "from sklearn.metrics import mean_squared_error, r2_score\n",
+    "from sklearn.model_selection import cross_val_predict\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "from math import sqrt\n",
+    "\n",
+    "cv = KFold(n_splits=10, random_state=0, shuffle=False)\n",
+    "classifier_pipeline = make_pipeline(StandardScaler(), KNeighborsRegressor(n_neighbors=10))\n",
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),2)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),2)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>Filter Features by Variance</h2>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CRIM          73.986578\n",
+       "ZN           543.936814\n",
+       "INDUS         47.064442\n",
+       "CHAS           0.064513\n",
+       "NOX            0.013428\n",
+       "RM             0.493671\n",
+       "AGE          792.358399\n",
+       "DIS            4.434015\n",
+       "TAX        28404.759488\n",
+       "PTRATIO        4.686989\n",
+       "B           8334.752263\n",
+       "LSTAT         50.994760\n",
+       "MEDV          84.586724\n",
+       "1.0            0.038039\n",
+       "2.0            0.045271\n",
+       "3.0            0.069597\n",
+       "4.0            0.170469\n",
+       "5.0            0.175968\n",
+       "6.0            0.048840\n",
+       "7.0            0.032532\n",
+       "8.0            0.045271\n",
+       "24.0           0.193198\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "boston.var()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = X.drop(columns = ['NOX','CHAS'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 6.28\n",
+      "R_squared: 0.53\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),2)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),2)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>Filter Features by Correlation</h2>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import seaborn as sn\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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/BF5bVfcAJPlD4Mwk+1fVfcPvuiRJ0gh1+CKpQRt6wlpV2/Wt/wDYZsbxDwAfWM9Dnzaj3SSwd4s+SpIkqTtGXWGVJEnSg9Hhi6QGzVuzSpIkjaOpGvyyGZIcluTKJFcnOWEDbV6U5PIklyX5h9k+VSuskiRJ2ixJFjA9n/6hwErgG0lWVNXlfW32At4E/HJV/SjJLrM9rwmrJEnSOBrNRVdPAq5ed7fRJGcBhzM9Nek6/x/w/qr6EUBV3TTbk87phPXkcx/WNP6/PmFV0/gAv7vsc03jv56FTeMfO/HHTeMDvG/y5Kbx3zzx5qbxr3zsPk3jAxx/4jVN499WWzWN/6Yh/FDe58+/3jT+Ze9/QdP4k8dd2jQ+wNZbrmka/+772v9Kunhh2+/V1uPsFg5hmsxDV9/dNP7Dd7qzafy3/3X7nxdvf3XzU4xMkmXAsr5dy6tqed/2HsD1fdsrgSfPCPPYXqz/AhYAb62qz8ymX3M6YZUkSZqzGvwx30tOl2+y4cZtCewFHAwsAb6cZN+qum02ASVJkjRuaiR3ploF7Nm3vaS3r99K4PyqWg18N8l3mE5gv/FgT+osAZIkSdpc3wD2SvKoJIuAI4EVM9r8E9PVVZI8jOkhAtfO5qRWWCVJksbRCC66qqo1SY4FPsv0+NTTquqyJCcBk1W1onfsV5NcDqwF3lBVt8zmvCaskiRJ2mxVdQ5wzox9J/atF/C63jIQJqySJEnjaDMn+p8LOjOGNcnaJBcl+VaSf06yY2//0iSV5M/72j4syeok7xtdjyVJkkaopga/dFRnElbg7qrav6r2AW4FXtV37LvAr/dtvxC4bJidkyRJ0mh0KWHt91WmJ6Zd5y7giiQTve0XAx8feq8kSZK6YqoGv3RU5xLW3j1qn8X9p0g4CzgyyZ5MX3F2wwYevyzJZJLJb95+ddvOSpIkqbkuJaxbJ7kI+D6wK3DujOOfAQ5ler6vj20oSFUtr6qJqpo4YPvHNOusJEnSKNXU1MCXrupSwnp3Ve0PPBIIPzuGlaq6D7gAOB44e/jdkyRJ0ih0blqrqroryWuAf0rytzMO/zXwpaq6NckIeidJktQRHR5zOmidS1gBquqbSS4BjgL+o2//ZTg7gCRJUqenoRq0ziSsVbXdjO3f6NvcZz3tTwdOb9srSZIkjVpnElZJkiQ9APNoSECXLrqSJEmS7scKqyRJ0jjq8DRUg2bCKkmSNI7m0ZCAOZ2wHn/Aqqbxn/6Ve5rGB5h8xy82jX/hm7/XNP7fvPfJTeMDvHnizU3jv33y7U3jb7fkGU3jA9x6/FOaxr/tCz9uGv/kGx/eND7At97y1Kbxj37jhU3jH7h4+6bxAR59X9tfjlcubhoegG0b/36/rRY2jT+Metq5C7duGv8JN2/VNP4JR9zWNL5GY04nrJIkSXPWPJrWyouuJEmS1GlWWCVJksaRY1glSZLUZTWPZglwSIAkSZI6zQqrJEnSOJpHQwJGVmFN8oIkleRxffuelOS8JFcluTDJvybZt3fsrUlWJbmob9lxVP2XJEnScIyywnoU8J+9r29JsivwceB3quorAEmeBvw8cGnvMadU1btG0VlJkqROmUcV1pEkrEm2A54GPBP4Z+AtwLHAGeuSVYCq+s9R9E+SJEndMaohAYcDn6mq7wC3JDkIeAKwqVvBvLZvOMAX19cgybIkk0kmz/jejQPutiRJUkfU1OCXjhrVkICjgPf01s/qbf+MJOcDDwE+V1XH9XZvckhAVS0HlgPc+pvPmD+1ckmSNL84JKCdJDsBhwD7JilgAVDAGcCBwKcBqurJSY4AnjfsPkqSJKk7RjEk4AjgI1X1yKpaWlV7At8FzgWOSfJLfW23GUH/JEmSOq+mauBLV41iSMBRwMkz9n2it//FwMlJ9gBuAm4GTupr99okv9e3/YKq+l7DvkqSJGnEhp6wVtUz17PvvX2bz9jA494KvLVNryRJksZMhyuig+adriRJksbRVHev6h+0kd3pSpIkSdocVlglSZLG0TwaEmCFVZIkSZ02pyusf3Dhjk3jT/7V3k3jA+z6hx9rGv8vd/qlTTeahWcccUrT+ABXPnafpvG3W7Le6wAH5o6VX2oaH+DJ+x7dNP6hi/dsGv/NS9vfte7Qd/6wafyzHpGm8Vffc3fT+ADfuWmnpvFftPgnTeMDrFnTtk5zxeodmsbfZc2apvEBnrnrzU3jf3fVQ5vGf+6n7m0aH+A/3tf8FJtnHlVY53TCKkmSNFdVzZ+E1SEBkiRJ6jQrrJIkSeNoHg0JsMIqSZKkTrPCKkmSNI6ssA5XkrVJLkpyWZKLkxyfZIvesYOT/Etvfdck/9Jrc3mSc0bbc0mSJLXWlQrr3VW1P0CSXYB/AB4CvGVGu5OAc6vqPb22+w21l5IkSR1RVlhHp6puApYBxyaZOXHh7sDKvraXDLNvkiRJnTFVg186qnMJK0BVXQssAHaZcej9wIeSfDHJm5M8Yvi9kyRJ0jB1MmHdkKr6LPBo4P8BjwO+meTh/W2SLEsymWTy2ju+N4JeSpIkDcFUg6WjOpmwJnk0sBa4aeaxqrq1qv6hql4CfAP4lRnHl1fVRFVNPHq7pUPpryRJktrpykVXP9WrmJ4KvK+qqn8Ya5JDgK9V1V1Jtgd+HrhuND2VJEkanfl00VVXEtatk1wELATWAB8B3r2edgcB70uyhunq8Aer6hvD66YkSVJHmLAOV1Ut2Mix84Dzeut/BfzVcHolSZKkLuhEwipJkqQHqMMXSQ1aJy+6kiRJktaxwipJkjSGvOhKkiRJ3TaPhgTM6YT1jONm3ihrsF594lVN4wP84O+WNY2/4pWXNo1/+wePbhof4PgTr2ka/9bjn9I0/pP3bf8anX/pmU3j33PSa5rGP+JTWzeND/C5Vz58041m4XkfuLFpfCiet8WuTc9w51Ztqznn3Ld90/gA27LBa3wHYvXithnEAfe1/7X9zz/crWn8exc3Dc+/f+7EtifQSMzphFWS5ovWyaqk7plPQwK86EqSJEmdZoVVkiRpHM2jMaxWWCVJktRpVlglSZLGUM2jCqsJqyRJ0jiaRwnrSIYEJNk5yUW95ftJVvVt75JkdZJX9LXfPsk1SfbqbS9McmmSJ4+i/5IkSRqekSSsVXVLVe1fVfsDpwKn9G3/NvA14Ki+9rcDbwLe19v1euArVXX+kLsuSZLUCTU1+KWrunjR1VHA8cAeSZas21lVHwdI8kbgFUwnsJIkSZrjOjWGNcmewO5V9fUkHwdeDPx1X5PjgCuAZVV16yj6KEmS1AkdrogOWtcqrC8GPt5bP4u+YQE9hwE3AvtsKECSZUkmk0ye9tVvt+mlJEnSiI1qSECSw5JcmeTqJCes5/gretcaXZTkP5PsPdvn2rWE9SjgmCTfA1YA+/VdaPUI4DXAk4DnJtlvfQGqanlVTVTVxP966uOG1G1JkqS5L8kC4P3Ac4C9gaPWk5D+Q1Xt27s26S+Bd8/2vJ1JWJM8FtiuqvaoqqVVtRT4C/6nynoK8I6qWgm8Dnh/koymt5IkSaM1ogrrk4Crq+raqrqP6U/ED/+ZflX9pG9zW6Bm+1w7k7AynZh+asa+TzCduR8K/BzwIYCq+mfgR8DRQ+2hJEnS/LYHcH3f9srevp+R5FVJrmG6wvqa2Z505BddVdVbN3LsEuDxvc1zZxx7fsNuSZIkdVqLaaiSLAOW9e1aXlXLH2icqno/05+G/w7wv4GXzqZfI09YJUmS9CDU4EdG9pLTjSWoq4A9+7aX9PZtyFnAB2bbry4NCZAkSVK3fQPYK8mjkiwCjmT6QvmfWnfBfM+vA1fN9qRWWCVJksbQKO5MVVVrkhwLfBZYAJxWVZclOQmYrKoVwLFJng2sZvqao1kNBwATVkmSJD0AVXUOcM6MfSf2rR836HPO6YT19hWzrkBv1K31kKbxAe79+Gebxr9py/td2DdQ173joqbxAW6rrdrG/8KPm8Y/dPGem240S/ecNOsLNDdqqxPf2zT+r3z6T5vGB1h9yfWbbjQLd0/NelaXjdqxafRpixrPJLjX2va/kp649W1N47/y3nubxt8nuzWND7Bkdduy3Z1btB2NuPqDs57yc5MWv+sZzc+xOWpq/szu6RhWSZIkddqcrrBKkiTNVaMYwzoqJqySJEljqBpMa9VVDgmQJElSp1lhlSRJGkPzaUiAFVZJkiR12iYrrEnWApf22l4B/BHwr73DuwFrgR/2tp8E3N3X/rvAS6rqtr54FwHfrqojk7wMWDdX197Alb14nwG+DUxU1bG9xy0DXtdr+xPgdVX1nw/iOUuSJI29+TSt1eYMCbi7qvYHSPL3wIv7tt8K3FFV71rXOEl/+zOAVwFv720/num7Ijw9ybZV9WHgw71j3wOeWVU397aP6Yv5POAPgKdV1c1JDgT+KcmTqur7s3j+kiRJY6naTu/cKQ90SMB/AI95AO2/CvTPTH8U8BHgc8DhDyDOHwNvWJfMVtWFwLpkWJIkSXPYZiesSbYEnsP0x/2b034B8CxgRd/uFwNnAR9lOnndXE8ALpixb7K3f+Z5lyWZTDL5kRtueACnkCRJGh81lYEvXbU5CevWvXGnk8B1wIc2s/33gV2BcwGSTAA3V9V1wOeBA5Ls9KB7vgFVtbyqJqpq4iWPeMSgw0uSJGnINidhvbuq9u8tr66q+zanPfBIIPzPx/ZHAY/rjVW9BngI8Nub2c/LgYNm7DsIuGwzHy9JkjSnWGEdgKq6C3gNcHySRcCLgH2ramlVLWV6DOvmDgv4S+DkJDsDJNkfOAb420H3W5IkaRxUDX7pqqY3Dqiqbya5BHgTsKqq+geVfhnYO8nuVXXjJuKsSLIH8JUkBdwO/N6mHidJkqTxt8mEtaq228ixt26qfVX9Rm/1z2bsX8v0PK7rtpfOOH46cHrf9geAD2yqv5IkSfNBlz/CHzTvdCVJkqROazokQJIkSW1UWWGVJEmSOsEKqyRJ0hiqqVH3YHhSXZ7DYJaOeOTzmz65ty1a0zL89DnuW9w0/svvWdQ0/qlb3dM0PsCbGv+HPX3BVk3jv3npD5rGBzj6mq2bxv+VLQZ+D5Cf8cYL3tY0PsDRB72uafz37fOjpvEvu2CXpvGHYesF7X+mbtX45/Ztd7f9mT0Maxt/zLxF40+x/3zh7W1PAHzu+s904rP47zz+sIHnOY+9ohvPbSaHBEiSJKnTHBIgSZI0hrzoSpIkSeoIK6ySJEljaD7dOMCEVZIkaQzN4evm78chAZIkSeq0saqwJlkLXAoEWAscW1VfGW2vJEmShs8hAd11d1XtD5Dk14C/AJ4x2i5JkiSppXFLWPs9BGg7E7ckSVJHTc2jaa3GLWHdOslFwFbA7sAhMxskWQYsAzhgp/149HaPHG4PJUmShsB5WLvr7qrav6oeBxwGnJnkZ96tqlpeVRNVNWGyKkmSNP7GrcL6U1X11SQPAx4O3DTq/kiSJA2T01qNgSSPAxYAt4y6L5IkSWpn3Cqs68awwvTUVi+tqrWj7JAkSdIoeNFVR1XVglH3QZIkScM1VgmrJEmSps2nWQJMWCVJksaQF11JkiRJHWGFVZIkaQx50dUc8eHDp5rG/51/al+g/tgbdm8a/5N/8ZOm8c947Y5N4wPs8+dfbxr/W295atP4h77zh03jA3zulQ9vGn/1Jdc3jX/0Qa9rGh/gzAve3TT+9ksObhr/z3fZs2l8gIe2/ZHKbVssbnsCYMk9bT9DvX5R2wTi0fc1fhOAVYva/m67r3GO9cmjnDxoLprTCaskSdJc5UVXkiRJ6rT5NCTAi64kSZLUaVZYJUmSxtA8mtXKCqskSZK6zQqrJEnSGJpPY1gHnrAmuaOqtpux7xeA/wvsCCwG/gP4BHByr8ljgFXA3cAlVXV0khcAnwIeX1XfTnJ+77E7AVv32gO8oKq+N+jnIUmS1GXOEjB47wVOqapPAyTZt6ouBT7b2z4PeH1VTfY95ijgP3tf31JVT+61PQaYqKpjh9R3SZIkjdCwxrDuDqxct9FLVjcoyXbA04CXA0e27ZokSdL4mWqwdNWwEtZTgC8k+bckr02yqdsfHQ58pqq+A9yS5KDNPVGSZUkmk0x++I+NhEoAACAASURBVFvXzabPkiRJ6oChJKxV9WHg8cA/AgcDX0uysXvwHQWc1Vs/q7e9uedaXlUTVTXxsn1+7kH2WJIkqduKDHzpqqHNElBVNwCnAacl+RawD3DBzHZJdgIOAfZNUsACoJK8oarm05RjkiRJGzQ1j7KioVRYkxyWZGFvfTdgZ/7nKv+ZjgA+UlWPrKqlVbUn8F3g6cPoqyRJkrqlRYV1myQr+7bfDSwB3pPknt6+N1TV9zfw+KP4n+mu1vlEb/+XB9pTSZKkMTXV4Y/wB23gCWtVbahq+7qNPObgvvVnruf4e/vWTwdOf9AdlCRJ0ljxTleSJEljqMsXSQ3asKa1kiRJkh4UK6ySJEljqMsT/Q/anE5YX/bptgXkM3/xJ03jAxz2ziubxv+/225sOtzZO+LdtzaND3DZ+1/QNP7Rb7ywafyzHtH+I53nfeDGpvHvbjy3yr8e8KOm8QG2X3Jw0/i3rzyvaXyA857wpqbxH7JgddP42y++t2l8gK+vfWjT+L+xzS1N41+4Zqem8QEOWnN30/g773BX0/gv+Wj71OZTMy8NHxGHBEiSxkrrZFWSRmlOV1glSZLmqvk0JMAKqyRJkjrNCqskSdIYmk8VVhNWSZKkMeRFV5IkSdJ6JDksyZVJrk5ywnqOL07ysd7x85Msne05B56wJqkkf9e3vWWSHyb5l972Mb3ti/qWvZMsTXJ3km8muSLJ15Mc03vMM5J8dcZ5tkzygySPGPRzkCRJ6rqpDH7ZlCQLgPcDzwH2Bo5KsveMZi8HflRVjwFOAWY9EViLIQF3Avsk2bqq7gYOBVbNaPOxqjq2f0cv+76mqg7obT8a+GSSAGcAS5I8sqr+u/eQZwOXVdUNDZ6DJEmS7u9JwNVVdS1AkrOAw4HL+9ocDry1t3428L4kqaoHPWl3qyEB5wC/3ls/CvjoAw3QeyFeB7ymqqaAjwNH9jU58sHElSRJmgumyMCXJMuSTPYty2acdg/g+r7tlb19621TVWuAHwM7z+a5tkpYzwKOTLIVsB9w/ozjL54xJGDrDcS5EHhcb/2j9BLWJIuB5wKfGHzXJUmSuq9aLFXLq2qib1k+1Ce1AU0S1qq6BFjKdHX1nPU0+VhV7d+3bOg+cD8dTVFVk8B2SX6B6XET51fV/e772f+XwbV3/PfMw5IkSXrwVgF79m0v4f5DP3/aJsmWwA7ArO5b3HKWgBXAu5jdx/YHAFf0ba+rsm5wOED/XwaP3u6Rszi1JElSd001WDbDN4C9kjwqySKmc7IVM9qsAF7aWz8C+MJsxq9C23lYTwNuq6pLkxz8QB/cuwjrXcD/6dv9UaZfhB2YvgJNkiRJQ1JVa5IcC3wWWACcVlWXJTkJmKyqFcCHgI8kuRq4lZ+9BulBaZawVtVK4L0bOPziJE/r234lcAPw80m+CWwF3A68t6pO74t5RZI7gQuq6s42PZckSeq+qYzmxgFVdQ4zhnxW1Yl96/cALxzkOQeesFbVduvZdx5wXm/9dOD0DTx8Qxdf9cfa/0F3TpIkSWPHW7NKkiSNoVkNCh0zJqySJEljaDMvkpoTWs4SIEmSJM2aFVZJkqQxNDWaa65GYk4nrM9Z+5Cm8e+4rv1EBb+25W5N419xe9sRMAcvbl/Enzzu0qbxD1y8fdP4q+/Z0H0zBud5W+zSNP6OTaPDZRfc2/gM8Oe77LnpRrNw3hPe1DT+wZf9RdP4AB/f78RNN5qFtfds0zQ+wF2NfyR9/s5Z3X1yk3ZoGn3af2erpvG/+5NNXl89K4csaBpeIzKnE1ZJkqS5aor5U2I1YZUkSRpD82mWAC+6kiRJUqdZYZUkSRpD8+miKyuskiRJ6jQrrJIkSWPIGweMQJLTktyU5FsbOJ4k701ydZJLkhw47D5KkiR1RTVYuqozCStwOnDYRo4/B9irtywDPjCEPkmSJGnEOjMkoKq+nGTpRpocDpxZVQV8LcmOSXavqhuH0kFJkqQO8aKrbtoDuL5ve2VvnyRJkuawcUpYN0uSZUkmk0x+6c6rRt0dSZKkJqYaLF01TgnrKqD/Zt9Levt+RlUtr6qJqpp4xrZ7Da1zkiRJamOcEtYVwNG92QKeAvzY8auSJGm+mk8V1s5cdJXko8DBwMOSrATeAiwEqKpTgXOA5wJXA3cBLxtNTyVJkkav5tFFV51JWKvqqE0cL+BVQ+qOJEmSOqIzCaskSZI2X5c/wh+0cRrDKkmSpHnICqskSdIYmk8VVhNWSZKkMVSj7sAQzemEtfVfHtdd/9DGZ4ClW7S9BPCOBW3jLxzC/6att1zTNP6j72v7JL5z005N4wPcuVXb57Ao43+p6kMb/8B4yILVTeN/fL8Tm8YHeNElJzWN/9Entn8OrX8vtP6RN58SlAdrPt2udD6Z0wmrJEnSXDWfknMvupIkSVKnWWGVJEkaQ150JUmSpE6bTwmrQwIkSZLUaVZYJUmSxtB8mjWiExXWJHsm+WKSy5NcluS49bRJkvcmuTrJJUkOHEVfJUmSNFxdqbCuAY6vqguTbA9ckOTcqrq8r81zgL16y5OBD/S+SpIkzTtOazVkVXVjVV3YW78duALYY0azw4Eza9rXgB2T7D7krkqSJGnIOpGw9kuyFDgAOH/GoT2A6/u2V3L/pJYky5JMJpn88p1XteqmJEnSSE01WLqqUwlrku2ATwB/VFU/eTAxqmp5VU1U1cSvbLvXYDsoSZLUEdVg6arOJKxJFjKdrP59VX1yPU1WAXv2bS/p7ZMkSdIc1omENUmADwFXVNW7N9BsBXB0b7aApwA/rqobh9ZJSZKkDpmiBr50VVdmCfhl4CXApUku6u37E+DnAKrqVOAc4LnA1cBdwMtG0E9JkiQNWScS1qr6T2CjkzNUVQGvGk6PJEmSuq3LF0kNWicSVkmSJD0w3f0Af/A6MYZVkiRJ2hArrJIkSWNoPg0JsMIqSZKkTpvTFdZ7G99jd3W1v4nvVxetbhr/4HvbfgtctHBt0/gAd9/X9jlcubhpeF60+EHdI+MBOee+7ZvG32tt2/dg6wVrmsYHuG2Ltm/09ovvbRp/7T3bNI0P8NEnntg0/lEXn9Q0PsB7Dmz7HFrf2337YZTUGv9ua/0a3dX+V3NntH4tu2ROJ6ySJElzVZfnTR00hwRIkiSp06ywSpIkjaH5U1+1wipJkqSOs8IqSZI0hpzWSpIkSeqITiSsSbZK8vUkFye5LMmfrafN4iQfS3J1kvOTLB1+TyVJkrphihr40lWdSFiBe4FDquqJwP7AYUmeMqPNy4EfVdVjgFOAk4fcR0mSpM6oBktXdSJhrWl39DYX9paZr9vhwBm99bOBZyWZR1PmSpIkzU+dSFgBkixIchFwE3BuVZ0/o8kewPUAVbUG+DGw83riLEsymWTyv+64qnW3JUmSRmKqwdJVnUlYq2ptVe0PLAGelGSfBxlneVVNVNXEL2+312A7KUmSpKHrTMK6TlXdBnwROGzGoVXAngBJtgR2AG4Zbu8kSZK6wYuuhizJw5Ps2FvfGjgU+PaMZiuAl/bWjwC+UFXdfWUlSZIamk8XXXXlxgG7A2ckWcB0Ev3xqvqXJCcBk1W1AvgQ8JEkVwO3AkeOrruSJEkalk4krFV1CXDAevaf2Ld+D/DCYfZLkiSpq7p8kdSgdWJIgCRJkrQhnaiwSpIk6YGpTo86HSwTVkmSpDE0n4YEzOmE9eYt2v7lsSDt/7J5+r1t36LF1fbbffEQRp1cvHCrpvG3bfw2r1nT/jXalgVN4z9x69uaxgdYO9X2dVpyT9s3+utrH9o0PsBdjb+VWv9yfM+BJ2660Swdd+FJbeNPnNA0/tZbLGoaH2BR4595qxvfo/Ka3NP2BBoJx7BK6rzWyepc0DpZldQ9XZuHNclOSc5NclXv6/3+Uk/yyCQXJrkoyWVJXrE5sf0RJ0mSpEE4Afh8Ve0FfL63PdONwFN7dzd9MnBCkkdsKrAJqyRJ0hjq4I0DDgfO6K2fAbzgfn2uuq+q7u1tLmYzc1ETVkmSJAGQZFmSyb5l2QN4+K5VdWNv/fvArhs4x55JLgGuB06uqhs2FXhOX3QlSZI0V812zOn6VNVyYPmGjif5d2C39Rx684w4laz/6vSquh7YrzcU4J+SnF1VP9hYv0xYJUmSxtAoprWqqmdv6FiSHyTZvapuTLI7cNMmYt2Q5FvA04GzN9a2U0MCkixI8s0k/7KeY4uTfCzJ1UnOT7J0+D2UJEnSBqwAXtpbfynw6ZkNkixJsnVv/aHA04ArNxW4UwkrcBxwxQaOvRz4UVU9BjgFOHlovZIkSeqYavBvlt4JHJrkKuDZvW2STCT5YK/N44Hzk1wMfAl4V1VduqnAnRkSkGQJ8OvA24HXrafJ4cBbe+tnA+9LkqqaP/clkyRJ6qiqugV41nr2TwK/31s/F9jvgcbuTMIK/A3wRmD7DRzfg+mryaiqNUl+DOwM3Dyc7kmSJHXHfLo1ayeGBCR5HnBTVV0wgFg/nY7hgjuuHkDvJEmSuqeDQwKa6UTCCvwy8Pwk3wPOAg5J8ncz2qwC9gRIsiWwA3DLzEBVtbyqJqpq4qDtHtO215IkSWquEwlrVb2pqpZU1VLgSOALVfV7M5r1X3l2RK9Nd/8UkCRJamiqwdJVXRrDej9JTgImq2oF8CHgI0muBm5lOrGVJEnSHNe5hLWqzgPO662f2Lf/HuCFo+mVJElSt0zNow+aO5ewSpIkadPmT7rakTGskiRJ0oZYYZUkSRpDU/OoxmqFVZIkSZ02pyusCxrHv4VFjc8At2yZpvEfft/apvGfe0/7STJa/9V1Wy1sGv+K1Ts0jQ+wenHb9+GV997bNP7b1uzYND7A9Yva/l/7jW3uN230wH3+zp2bxm9dy5lq+xYAcNzECU3jv2fynU3jn3rAiZtuNEvV+H1o/n3UOH6XdHmi/0GzwipJc0DrZFWSRmlOV1glSZLmqvlUTTZhlSRJGkNedCVJkiR1hBVWSZKkMeRFV5IkSVJHdKbCmuR7wO3AWmBNVU3MOB7gPcBzgbuAY6rqwmH3U5IkqQu86Gp0nllVN2/g2HOAvXrLk4EP9L5KkiTNO1UOCeiiw4Eza9rXgB2T7D7qTkmSJKmtLiWsBXwuyQVJlq3n+B7A9X3bK3v7JEmS5p0pauBLV3UpYX1aVR3I9Ef/r0ryKw8mSJJlSSaTTE7ecfVgeyhJkqSh60zCWlWrel9vAj4FPGlGk1XAnn3bS3r7ZsZZXlUTVTUxsd1jWnVXkiRppKYaLF3ViYQ1ybZJtl+3Dvwq8K0ZzVYAR2faU4AfV9WNQ+6qJElSJ1SDf13VlVkCdgU+NT1zFVsC/1BVn0nyCoCqOhU4h+kpra5melqrl42or5IkSRqiTiSsVXUt8MT17D+1b72AVw2zX5IkSV3V5YukBq0TQwIkSZKkDelEhVWSJEkPjDcOkCRJkjrCCqskSdIY6vI0VIM2pxPWXdamafyF1f5bpXUJfOWWi5rGX932LQBgYeNPRFq/y7usWdP4DHDAfW3/q++T3ZrGh3sax4dH39f2nb5wzU5N4+/QNPq01h8+bj+E375bb9H2Z96pB5zYNP4rvnlS0/gAZ+/3p03jr6XtL4Z9s1XT+F3S5WmoBs0hAZIkSeq0OV1hlSRJmquc1kqSJEnqCCuskiRJY2g+TWtlwipJkjSGHBIgSZIkdURnEtYkOyY5O8m3k1yR5KkzjifJe5NcneSSJAeOqq+SJEmjVg3+dVWXhgS8B/hMVR2RZBGwzYzjzwH26i1PBj7Q+ypJkqQ5rBMJa5IdgF8BjgGoqvuA+2Y0Oxw4s6ZHGH+tV5HdvapuHGpnJUmSOmBqHl101ZUhAY8Cfgh8OMk3k3wwybYz2uwBXN+3vbK372ckWZZkMsnkf9x5VbseS5IkjVA1WLqqKwnrlsCBwAeq6gDgTuCEBxOoqpZX1URVTTx9270G2UdJkiSNQFcS1pXAyqo6v7d9NtMJbL9VwJ5920t6+yRJkuadKWrgS1d1ImGtqu8D1yf5hd6uZwGXz2i2Aji6N1vAU4AfO35VkiRp7uvERVc9rwb+vjdDwLXAy5K8AqCqTgXOAZ4LXA3cBbxsVB2VJEkatS5XRAetMwlrVV0ETMzYfWrf8QJeNdROSZIkddR8ujVrJ4YESJIkSRvSmQqrJEmSNt98GhJghVWSJEmdZoVVkiRpDNU8qrDO6YR1UeP3cfdFd7U9AXDpFts3jb/d2qbhuWHL9v+ZDl19d9P45y7cumn8Z+56c9P4AP/8w92axl+yeqpp/LWVpvEBVi1q+4HTQWvafp/+d7ZqGn8ohvA+t/690PopnL3fn7Y9AXDEJW9rGr/1c1g8hO8jDd+cTlglSZLmqvk0S4AJqyRJ0hjyoitJkiSpI6ywSpIkjaH5NCTACqskSZI6zQqrJEnSGHIM65Al+YUkF/UtP0nyRzPaJMl7k1yd5JIkB46qv5IkSaNWDf51VScqrFV1JbA/QJIFwCrgUzOaPQfYq7c8GfhA76skSZLmsE4krDM8C7imqv57xv7DgTNreoTx15LsmGT3qrpx+F2UJEkarSkvuhqpI4GPrmf/HsD1fdsre/t+RpJlSSaTTJ5351WNuihJkqRh6VTCmmQR8HzgHx9sjKpaXlUTVTVx8LZ7Da5zkiRJHeIY1tF5DnBhVf1gPcdWAXv2bS/p7ZMkSZp3HBIwOkex/uEAACuAo3uzBTwF+LHjVyVJkua+ziSsSbYFDgU+2bfvFUle0ds8B7gWuBr4f8Arh95JSZKkjujakIAkOyU5N8lVva8P3UC7n0vyuSRXJLk8ydJNxe7MkICquhPYeca+U/vWC3jVsPslSZKkzXIC8PmqemeSE3rbf7yedmcCb6+qc5NsB0xtKnBnElZJkiRtvg6OYT0cOLi3fgZwHjMS1iR7A1tW1bkAVXXH5gTuzJAASZIkjbVd+64v+j6w63raPBa4Lcknk3wzyV/1bhq1UVZYJUmSxlCLaaiSLAOW9e1aXlXL+47/O7Dbeh765p/pW1UlWV8HtwSeDhwAXAd8DDgG+NDG+mXCKkmSNIZaDAnoJafLN3L82Rs6luQH6+5CmmR34Kb1NFsJXFRV1/Ye80/AU5jPCetU2sa/Yu32bU8AVONBG3svuL1p/B9NtX+NHr7TnU3jP+HmrZrG/+6q9V5EOVD3Lm4b/84t2n6j7rTJ4fizd1/jnxc773BX0/jf/cnWTeMPQ+uf2QCrG5+j9YjCtbR/kc7e70+bxj/ikrc1jf+3B57YNL42agXwUuCdva+fXk+bbwA7Jnl4Vf0QOASY3FRgx7BKkiSNoa5Na8V0onpokquAZ/e2STKR5IMAVbUWeD3w+SSXAmF6utKNmtMVVkmSJA1HVd0CPGs9+yeB3+/bPhfY74HENmGVJEkaQ1VDGC/VESaskiRJY2iq+ajp7nAMqyRJkjqtMwlrktcmuSzJt5J8NMlWM44vTvKxJFcnOX9z7jsrSZI0V1XVwJeu6kTCmmQP4DXARFXtAywAjpzR7OXAj6rqMcApwMnD7aUkSZJGoRMJa8+WwNZJtgS2AW6Ycfxwpu9LC3A28KwkQ5i1T5IkqXumqIEvXdWJhLWqVgHvYvoWXTcCP66qz81otgdwfa/9GuDHwM7D7KckSVJXOCRgyJI8lOkK6qOARwDbJvm9BxlrWZLJJJNfuvOqQXZTkiRJI9CJhJXpuyF8t6p+WFWrgU8CvzSjzSpgT4DesIEdgFtmBqqq5VU1UVUTz9h2r8bdliRJGo2pqoEvXdWVhPU64ClJtumNS30WcMWMNuvuTwtwBPCF6nLtWpIkSQPRiRsHVNX5Sc4GLgTWAN8Elic5CZisqhXAh4CPJLkauJX7zyIgSZI0b1SHL5IatE4krABV9RbgLTN2n9h3/B7ghUPtlCRJkkauMwmrJEmSNt98GhlpwipJkjSGujxv6qB15aIrSZIkab2ssEqSJI2h+TQkIHP5yd61/LVNn9zr37GqZXgA3nX8w5rGP+cdP24a/7l/skPT+ABv/+vbmsY/4Xlt4z/3U/c2jQ/w758/cdONZmH1B9/dNP5vfaz9a/TJ39mmafyXfHR10/gAh1Tb/29TjW+GfdcQbrZ9Te5pGn+qaXTYd2qrxmeAxY3TgtWN3+dXXnhS2xMACx/26E7cGv5hD3nswN+tm3/ynU48t5mssErSHNA6WZXUPV2e6H/QTFglSZLG0Fz+lHwmL7qSJElSp1lhlSRJGkNOayVJkiR1hBVWSZKkMeQY1kaS7Jnki0kuT3JZkuNmHD8+SSVZ71xOSV6a5Kre8tLh9FqSJKl7pqoGvnTVsCusa4Djq+rCJNsDFyQ5t6ouT7In8KvAdet7YJKdgLcAE0D1Hruiqn40rM5LkiRp+IZaYa2qG6vqwt767cAVwB69w6cAb4QNjiD+NeDcqrq1l6SeCxzWuMuSJEmdVA3+ddXILrpKshQ4ADg/yeHAqqq6eCMP2QO4vm97Jf+T7EqSJGmOGknCmmQ74BPAHzE9TOBPgIHcOzLJsiSTSSZP+/KlgwgpSZLUOfNpDOvQE9YkC5lOVv++qj4J/DzwKODiJN8DlgAXJtltxkNXAXv2bS/p7fsZVbW8qiaqauJ//cq+LZ6CJEmShmioF10lCfAh4IqqejdAVV0K7NLX5nvARFXdPOPhnwXekeShve1fBd7UvNOSJEkd5LRW7fwy8BLgkCQX9ZbnbqhxkokkHwSoqluBtwHf6C0n9fZJkiTNO/PpoquhVlir6j+BbKLN0r71SeD3+7ZPA05r1T9JkqT/v70zD5ejrPLwe0hYwhIkQsIaUVCDgpKwZURFZB8yiDoqibKNgM5EjbII6szwIIoLIhocl4yBAAMJIEqCaERZFDQBYoIkLCICQsIiIAoSJCT5zR/n66Rvp29nqa/qdt8+7/PUk+qqm9+pruruOnW+850TtB/R6SoIgiAIgqADiZSAIAiCIAiCIGgTIsIaBEEQBEHQgXRThDUc1iAIgiAIgg6ke9zVSAkIgiAIgiAI2h1JsdQtwEmh37/fQ5yjvtfvD+8hzlF72Oh0/f7wHuIcxVLFEhHWVTkp9PvcRqfrV2Gj0/WrsNHp+lXYiPfQ9/pV2Oh0/SpsVPEeggKEwxoEQRAEQRC0NeGwBkEQBEEQBG1NOKyrMin0+9xGp+tXYaPT9auw0en6VdiI99D3+lXY6HT9KmxU8R6CAlhKNg6CIAiCIAiCtiQirEEQBEEQBEFbEw5rEARBEARB0NaEwxoEXYyZ7dVi39FVHks7Y2bDK7Cxddk2giAIOpWuzWE1s/e02i/phwX1j1mN/iVF9HuxuT6wK7BI0p9z61eNmQ2UtLSvj6MVZjZY0nO97Bsu6ZESbL4SeDvwiKTfFtS6C/g18BlJf03bdgW+DfxF0pFFj7fO1lBgPPDGtOlu4NuSnsxlo8HelsAzyvAjZ2ZzJY3KcFitbDwBLACmAlfXrkenYWbDgO3Sy0UlXt8hAJL+0mn6VZyjsm1U9B7KvAabA4dS9x6An3Xq964b6GaHdTlwZ1oArG63JP1bQf0Letl1BLCdpIFF9JON7wIXSLo7fflmAcuAIcCpkqYW1D8RuFnSH8zMgAuB9wIPA8dJmlvoDbiNa4GPSfpTw/YDgW9I2rWg/sRW+yV9oqD+CkfGzG6QdECzfQVt/Bg4Q9ICM9sGmAvMAXYCJkn6RgHtgcBpeNHss4HdgH8GTpH046LHXmdnX+ByYApQc7L3AI4FPijp1wX1RwNfBv6Cv49LgS3xUaRjJM0sqD9P0sgiGmtgYwBwIHAUfg1m487rdEkvZrRTiqNhZrsD3wU2x2/+ANsDfwX+I9PvxXDgq8ABSdeAwcCN+Hfk4TbXr+IclWqjAv1Sr0GycQxwJnA9Pd/DQcBZZQSUggz0dautvlqAI4Fp+I3/v4CdS7RlwIeA+cAVwJsy6d5dt/5J4Jq0vjUwL4P+AmD9tD4OdzReid9Ub8n0Hj4IPAh8Dlgf2Ba4ErgN2COD/hLcwTsDOAZ3kFYsGfTnNVtv9jrTdf4scEla3wy4K5ON04DlwEJg2xyaDfqzgZFNtu8O3JZBfw5wMPA+4FlgdNo+ItN34c/AxN6WEs7XBsC7cIf1CeCyDJq7p+twL/CLtNyXto3KoH8nsE+T7aOB32U6L7OADwAD6rYNwJ382R2gX8U5KtVGBfqlXoOk93vgFU22bwHcn8NGLPmXrs1hlXSNpKOA/YA/AueZ2a1mtl8uG2Y20MxOwG8QBwL/KukDku7KZGJJ3fpBwDUAkp7IpL9U0stpfQzuKD0j6RfAJjkMSLoMGAkMx8/TLPxGOloFh7sT2+D19Q4Bjsad4umSLpZ0cQZ99bLe7PW68nLd+gHATwAkPY87meuMme1kZjOBdwK7AF8DfmVmxxfRbcJgSfMaN0q6E3e8izJQ0vWSrgKekDQ76d+XQRvgRfyBrbclK5KWAPfg34nn8GtTlCnABEm7SDowLSPwh92LMuhvIum2xo3pWmT5vQC2lHSFpGV1+sskTcMfpttdv4pzVLaNsvXLvgbgQaRmv8/L6TnaGrQRhYel+wH/AP6G3xReBWyUQ9TMxgMTgBuAQ5VhGKMJfzWzMfiQxr7Ah5PtgcCgDPrL0xD0s7ij9MW6fTn0a7wB2Bu4HdgTGIZ/Nl9u9Z/WBEnP4MNX3zWz7fGn9HvM7HRJlxbVB4aa2cn4j1xtnfR6qwz6AI+a2cfx6OcoYCaAmQ3CHfAi/AwfZvtBev17M7sS+LqZnSBp34L6NczMtpD0bMPGIeSZ/FnvuDcOn+d4cHgm0wNOS8xsB/wzOha/+U8FjsjkePfqaJhZDkfjp2Z2HXAJ8GjatgM+slEoJaOO35rZt4GLG2wcC6zyQNSG+lWco7JtlK1f9jUAv5fNNbPr62wMxwM/Z2eyEWSmm3NY34nfGPbGI3rTJM3JqL8ckL003AAAD4hJREFUH0Z8ip43TMNzZN+Uwcbr8CHJrfF8zylp+yHAwZJOKag/BvgePhxzraQT0/b9gE9LOryIftKajEdYx0ualW6cZ+E5fJ+UdH1RG8nOKNwJOAiPiJ0n6Z4Mume22i/prAw2hgKfx6PF/1M7J2a2P5428bUC2ptK+nsv+w5M0fTCmNlJwInAqXiKBngO61eACyV9r6D+MuAF/Ps1CFhc2wVsJKmQY29msyWNbrL9rcBYSeOL6Cet3+C5pVcBUzONMNTrT8Tznps5Gg9J+lgGG4fhqQz1E1lmSPpJUe2kvwH+YF5vYyFwLTBZ0kvtrJ9slHqOqrBRpn4V1yDZ2QIfeWucdPVs7/8r6Eu62WFdDtwF3Io7lD1OhIpPxvko/rTZ7AR/QNJXi+hXRYrWblb/JTazjfH8oucz6H8KzwFc1rB9N3wG+dsK6n8eOBwfWp0GzFSbVx7oa8xsJzxn+ShJb1zd36+F7hjg0/SsEnCupGtz2agCMxuJn5/3AQ8BP5TU2yTLtdF9O54bXtqPchXOUhAEQRl0s8N6HC2GCosO/6WIzy+BoyUtatiXa/b4BayaQ/k0cJOkW4vqN7FneK7jOGCMpGGZdEsrd5QeTB5iZcStdr6yRLrN7I3ATpJmpNfn47NnAb6lfJUUWn1Wj8hgY1t8osM4vFLAl3BHbH5R7f5AGs0Ym5an8cmTp0p6VWY7xwKfwCeLgT9oTVSHz1o2s5Mkldqr3czGKGNliz7Qr+IclWqjAv1Sr0GyMUnSSWXaCNaNrs1hrQ2fl8hdeP7ZbDP7VF2OIORL6m6WwjAEONfMrlCBckf1pJJB4/DKCkNw5/LUTNr15Y5qN+U9gNvMrHC5I+DVBf//6vgy7tzVOASvOrEx8N/4OSvKOg/5r440VD8Wj7hdiQ/FTc+RytBgp/HhqgdFRzQq4D7gFvxB7QFYMTqQjeSsfhI4GU+bMDxn+VwzU6ac695sl+0sVTGRZS+gTGembP0qzlHZNsrWL/sagKfBBW1IN0dYS41a1aKoKTJzGV4iarykxbkirC1sDwJ+o4J1I83sHHzY8xHc+f4RMEdSNifQzGYD/944gzzV+vuepH1y2WrQXw/PPbysoM4cSXvWvV6R62hmt0p6a8FDbbS3FYCkpzLpLcErM5xSy+E2swclvSaHfp2dY1vtr2JCUxHM7Eg8531fPNVnGvD9Er4LRzVO0DSzHfEc+1VyaDPa/kjRPOKkMwJ/+LmtPjfazA5VwVq4dVp746Mjd5jZG/Di7/eVldZgZpdIatkIpoD2W/F5FAsy5uvvA9wr6bl0LzgDf/C5BzhH0t8K6n8C+JGkR1f7x+umvwH+XXtM0i/MbBzwFny0YZJWVq7JbXeo+kHDnf5M10ZYKTFqVY+k+83sn4AvAPNsNR2wMtl80UfvC3MCcD/wHXzS1UtmlvsJp9dyR2ZWuNyRmQ3GI8LbATOAnwMfA04Bfoc/TBShxzE2OBVDC2qvIE3u+jg+o97MbCneNOLzBaW3w5tBnGfeGvRKilceaMbrJX22BN1KkHQNcE2aFPguPBI61My+g9+8czgbgxud1WT74fQ5LpMlq/+T1iRHZjzuWEw2swmSpqfd55BhBnn6HhwGDDSznwP7ADcBZ5jZSElfbCmwev0ZjZuA/c3sFZAlkHG7pL3T+on4+foRcKaZjZL05SL6iQuBN6f1b+LpUF/BK71cBLTs8rgGnI2f7z/igYyrcj1AJy7CfZON04PupsAP8ePfCziuqAFLHbTqNwG3p/x0U0nd04KCqA2KwbbbAuybQWOVYuXAO/Ai+c+XeOwDgeNxB7Oo1gA8enExPkvzUuBxvOZlruO9F9iiyfYheNSkqP50PN3gI7gzdjOeW7x7puO/id6LaN+cycbJuKP96rptr8FLUn2qoPbcuvXtcUd+Trou52S8znNzafXFAkxpsm0LvEPYDZls/HZd9mWy/UgGjfnApml9x/Q5mpBe52qiMT/9Lm2MlyIcnLYPIkMTDTwV4//Sb/V+6d/H0/p+GfTrG43cAWyV1jcB5mc6R/fWv5+GfXfmeA/4g/PBwGS8Es5MvOzUZhn070r/DgSeJDUQwJ3KXI1SanMb6peX078P5rARS/6layOs5m0Q349HmGbK216OwTsJDcJLLRVhlRxASTeb2R6481QYM3seT2uoD6cuxh2ywjbkM/dnAjPNbEO8ecAgYJF5G9JxRW0A5wPXm1mzckfnZ9B/jaTdAMzs+/jNZ7ikf2TQBjgduMLMptDz+I/FJzHl4GjgIElP1zZIetDMPoS3FixynlZ8diQtBM7Do62vxXNbczEglZFpGvpX+0c0VpmcJ6+cMSktOdjFzJo1FTH8AaUQvWjX9HNMoFxPKQ1AHhV+B/ADM3sV+XIbl6bfpcVm9kdJzyV7L6YJlkXZE6+f/TngNPlIz4uSfplBG2C99D1YD4/kPQUg6YU0apKDBWZ2vKSLgN+Z2Z6S5qT0tBzD6ZK0HP/tud7M1sej3mPxkcui9afXS2kBm+APJpvjLZc3JN/oz2l4icPTlCaWmtlDypjiE+Snax1W/MlwB7xY/UQzewz/sTpDPvxXiN400k0ux7APknJ0CFpTWy8BVwNXp6H6d2fSnZTO/dn0rBLwBeUpd7TiB1rSMjNbmNFZRdLtaVLaeHyoSvjx19rA3p7BzPr1zmqd7afSzaIIW9nKZgeNNK3Puo6MwOvfNnNcRAaHrGQ2rg0XNtupDNUgyNPNqhXD8EmBjXUmDfhNBv0nzWx3efcyJP09BQEuxCtP5GCJmW0saTH+YAiAmW1Owa5vAMkRO9/Mrkr/Pkne++TmrPweyMy2kfS4mW1KPqf+BOCbZvafeEWLWWb2KF5794QM+j2OU55TOgOYYV7ysCiT8UmOA/AHh6vM7EF81GpaBn0knWdmV+DX+FHgTPJ1JgxKopsnXS0A3iRpuZlthPfr3kneGaljMK+Tehgry+Dcgxc/Lvy03sKRAUDS14vaKBtbWVAeehaVr5W1ypYbaCubE9Tqc14t6VsZdHudpFd0Ap+ZPY7nKDd1JFU8R7ZmZ54KTgLsS9Joxh30fp7emcHGCKWOVma2oeoKpJvZaKV2swX0JwMXqUnJOzO7vOiIiXknuaVq0hrazPZV8Yofq5yXuu1bAtsocxk2MzscTxErNf86OXrDJD2UUXMwXiVlILBQGcoEJt3XSbo/h1YLG9sCSHos5Q8fiKet5AgANNo6Ah9Z3VHS1rn1g3x0s8Pa40Zf9MbfF5jZdsCN+DD3PPxmOhLvfLW/pMcK6td3cfoIPct9ZHFmzOy/W+yWpLZuk2cV1OdscLp77KJgF6eqPvetHFYzG5brZloWVTjc9deiP/w+BUE7Y3UVLYBleMBqgWWsaBHkpZsd1sXAA7WXeMvC2muUoXVq2aS8yTvVUG81zdbdQ1LLUkJraauUG7aZNWsfuwleD/SVkjbNbTMnKW/uFuDDWlmfM3tZqLKoKvJpZseprvZxipq8F6/vu4ukbcs+hiJU5LCusNFor9Mj1EHQTjRUtNgdnxw4Pe2Lh8M2pZtzWN+M53Q11pLbAU8P6ARGSzqucaOkiWb2+8y2SnmykXRebT3lxk7AqxxMwycAtTvvwWsG3mRmtfqcVRQAz8UBVRiRNMW8JuS7cCd1JF4S7EjgV1UcQ0FOr3+Rcod3BRYpX+3Gxq51ve0LgqAYJ+JBnb+b1zn+gZntKOmbdNbvd1fRzQ7r+cBnJP2pfmPK+zkf+Jc+Oaq148UW+xa32NdWpJp4JwMfxEtojUqT09oeVVOfszSqmp1vZpcDb8NnFl+Ap7I8IOnmKuxn4D1mtkjS3WmCzyx8GHGImZ0qaWoGG9ub2UT8hllbJ73eLoN+EAROFRUtgsx0s8M6rFmCvqT56YmrE9jczJoVgTag8GQiM5vPysjOzo1lcXKkTZjZuXiUchKwm+q643QSkl7AW8xensrWvA+PyrW1w1ohb8Bnp9+L14lcZvmbUJTJ2yR9NK0fD9wv6UjzZgs/xQuoF+W0uvXGtsvN2jAHQbBuVFHRIshMN+ew/kHSa3vZ94Cknas+prXFzC5qtV/S8QX1X0uLtIlazmZBG8uBl4Cl9Bz2zD6LP+hb0iSHsXh92qeB1wO7tvuEK1glv/Q6vLvPlMZ9QRC0P1VUtAjy080O61TgRkn/27D9BLxIe66i7x2Lmf0YT5uY37B9N7wLUiekTQRtiHkDjXF4JHqhpLf08SG1xMxuwnOqF+HdzUZIeiKVlVsgaURLgTWz0dgWtAcq2BY0CIKgk+lmh3UY3sN5CV7IGbxxwAbAu5s9ebUbZnZMi92SdGlB/Tsk7dXLvvlKHaSCYF1Jk5c+k6vea1mk8mUT8ZJx36iLrh4CHCypWbWLtbXxFD6aMRUvtdNYoD1Xt6UgCIKOo2tzWNMw5FvMbH98ti/AdZJu7MPDWluaOpPAEfgkjUIOK/CKFvsGFdQOuog0mXE8/rmcAfw8vT4F6K1laNuQCqUf2mT7z8wsV4eqrfF2kWPx6PN1wFRJd2fSD4Ig6Fi6NsLa3zAzw2fZn453u/qipEKOQKRNBLkws+n4pKtZeCmtoXgEcUJt4kOnYmaPSBqeWXND3HE9FzhLGTqmBUEQdDLhsHY4KYfuOOBUYDbwJUlZarD2h7SJoD2oTyExswF4d7bhkv7Rt0dWHDN7VNIOmbQ2BA7HndUd8Wj0hZIW5dAPgiDoVLo2JaA/YGbj8UL7NwCHSno4p34/SZsI2oOXayuppNXC/uCsJrI89ZvZJfj37Cd4VHVBDt0gCIL+QERYO5hUEurPwFM0LwnV9u1lg+7AzJYBL9Re4jnQi+mQ8mVm9jzNHVMDBkkq/PCfvs+1cxQl3oIgCOqICGtn8+q+PoAgWEM2kvTy6v+sPZG0WQU21ivbRhAEQacSEdYgCErHzOZKGtXXxxEEQRB0JhFh7WBWM0wZQ4hBOxH9uYMgCIJ1JiKsQRCUjpktBL7e235Jve4LgiAIgoiwBkFQBQOATYlIaxAEQbAORIQ1CILSiRzWIAiCoAgxKzUIgiqIyGoQBEGwzkSENQiC0jGzbYH3AzsD84HJkpb27VEFQRAEnUI4rEEQlI6ZXYF3u7oFOAz4k6QJfXtUQRAEQacQDmsQBKVjZvMl7ZbWBwK3R05rEARBsKZEDmsQBFWwostVpAIEQRAEa0tEWIMgKB0zWwa8UHsJDAIWE00ugiAIgjUgHNYgCIIgCIKgrYmUgCAIgiAIgqCtCYc1CIIgCIIgaGvCYQ2CIAiCIAjamnBYgyAIgiAIgrYmHNYgCIIgCIKgrfl/h+XJsNTiXUcAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 864x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig_dims = (12, 8)\n",
+    "fig, ax = plt.subplots(figsize=fig_dims)\n",
+    "sn.heatmap(boston.corr(), ax=ax)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CRIM       0.388305\n",
+       "ZN         0.360445\n",
+       "INDUS      0.483725\n",
+       "CHAS       0.175260\n",
+       "NOX        0.427321\n",
+       "RM         0.695360\n",
+       "AGE        0.376955\n",
+       "DIS        0.249929\n",
+       "TAX        0.468536\n",
+       "PTRATIO    0.507787\n",
+       "B          0.333461\n",
+       "LSTAT      0.737663\n",
+       "MEDV       1.000000\n",
+       "1.0        0.040453\n",
+       "2.0        0.104444\n",
+       "3.0        0.167352\n",
+       "4.0        0.065711\n",
+       "5.0        0.187356\n",
+       "6.0        0.039411\n",
+       "7.0        0.092802\n",
+       "8.0        0.190053\n",
+       "24.0       0.396297\n",
+       "Name: MEDV, dtype: float64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abs(boston.corr()[\"MEDV\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['RM', 'PTRATIO', 'LSTAT']"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abs(boston.corr()[\"MEDV\"][abs(boston.corr()[\"MEDV\"])>0.5].drop('MEDV')).index.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'TAX', 'PTRATIO', 'B', 'LSTAT', 2.0, 3.0, 5.0, 8.0, 24.0]\n",
+      "RMSE: 6.47\n",
+      "R_squared: 0.5\n",
+      "['CRIM', 'ZN', 'INDUS', 'NOX', 'RM', 'AGE', 'DIS', 'TAX', 'PTRATIO', 'B', 'LSTAT', 24.0]\n",
+      "RMSE: 5.27\n",
+      "R_squared: 0.67\n",
+      "['CRIM', 'ZN', 'INDUS', 'NOX', 'RM', 'AGE', 'TAX', 'PTRATIO', 'B', 'LSTAT', 24.0]\n",
+      "RMSE: 5.42\n",
+      "R_squared: 0.65\n",
+      "['INDUS', 'NOX', 'RM', 'TAX', 'PTRATIO', 'LSTAT']\n",
+      "RMSE: 4.89\n",
+      "R_squared: 0.72\n",
+      "['RM', 'PTRATIO', 'LSTAT']\n",
+      "RMSE: 4.73\n",
+      "R_squared: 0.74\n",
+      "['RM', 'LSTAT']\n",
+      "RMSE: 4.8\n",
+      "R_squared: 0.73\n",
+      "['LSTAT']\n",
+      "RMSE: 5.7\n",
+      "R_squared: 0.61\n"
+     ]
+    }
+   ],
+   "source": [
+    "vals = [0.1,0.2,0.3,0.4,0.5,0.6,0.7]\n",
+    "for val in vals:\n",
+    "    features = abs(boston.corr()[\"MEDV\"][abs(boston.corr()[\"MEDV\"])>val].drop('MEDV')).index.tolist()\n",
+    "    \n",
+    "    X = boston.drop(columns='MEDV')\n",
+    "    X=X[features]\n",
+    "    \n",
+    "    print(features)\n",
+    "\n",
+    "    y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "    print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),2)))\n",
+    "    print(\"R_squared: \" + str(round(r2_score(y,y_pred),2)))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>Feature Selection Using a Wrapper</h2>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston = pd.DataFrame(boston_data.data, columns=boston_data.feature_names)\n",
+    "boston['MEDV'] = boston_data.target\n",
+    "boston['RAD'] = boston['RAD'].astype('category')\n",
+    "dummies = pd.get_dummies(boston.RAD)\n",
+    "boston = boston.drop(columns='RAD').merge(dummies,left_index=True,right_index=True)\n",
+    "X = boston.drop(columns='MEDV')\n",
+    "y = boston.MEDV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mlxtend.feature_selection import SequentialFeatureSelector as SFS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{21: {'feature_idx': (0,\n",
+       "   1,\n",
+       "   2,\n",
+       "   3,\n",
+       "   4,\n",
+       "   5,\n",
+       "   6,\n",
+       "   7,\n",
+       "   8,\n",
+       "   9,\n",
+       "   10,\n",
+       "   11,\n",
+       "   12,\n",
+       "   13,\n",
+       "   14,\n",
+       "   15,\n",
+       "   16,\n",
+       "   17,\n",
+       "   18,\n",
+       "   19,\n",
+       "   20),\n",
+       "  'cv_scores': array([ -20.01483529,  -38.77619216,  -19.22183529,  -66.60270392,\n",
+       "          -59.90746667,  -61.32327843,  -15.753274  , -107.234396  ,\n",
+       "          -20.92415   ,  -13.922834  ]),\n",
+       "  'avg_score': -42.36809657647059,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'CHAS',\n",
+       "   'NOX',\n",
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+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   1.0,\n",
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+       "   5.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   8.0,\n",
+       "   24.0)},\n",
+       " 20: {'feature_idx': (0,\n",
+       "   1,\n",
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+       "   3,\n",
+       "   4,\n",
+       "   5,\n",
+       "   6,\n",
+       "   7,\n",
+       "   8,\n",
+       "   9,\n",
+       "   10,\n",
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+       "   12,\n",
+       "   13,\n",
+       "   14,\n",
+       "   15,\n",
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+       "   17,\n",
+       "   18,\n",
+       "   20),\n",
+       "  'cv_scores': array([ -20.01483529,  -19.49721765,  -19.22183529,  -74.59283333,\n",
+       "          -44.45047059,  -53.63635098,  -15.796332  , -106.83866   ,\n",
+       "          -20.92415   ,  -13.922834  ]),\n",
+       "  'avg_score': -38.8895519137255,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'CHAS',\n",
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+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   1.0,\n",
+       "   2.0,\n",
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+       "   4.0,\n",
+       "   5.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 19: {'feature_idx': (0,\n",
+       "   1,\n",
+       "   2,\n",
+       "   4,\n",
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+       "   6,\n",
+       "   7,\n",
+       "   8,\n",
+       "   9,\n",
+       "   10,\n",
+       "   11,\n",
+       "   12,\n",
+       "   13,\n",
+       "   14,\n",
+       "   15,\n",
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+       "   18,\n",
+       "   20),\n",
+       "  'cv_scores': array([ -20.02093922,  -20.02723725,  -17.22919608,  -57.94924706,\n",
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+       "          -21.41984   ,  -16.222326  ]),\n",
+       "  'avg_score': -35.95862490196079,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
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+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   1.0,\n",
+       "   2.0,\n",
+       "   3.0,\n",
+       "   4.0,\n",
+       "   5.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 18: {'feature_idx': (0,\n",
+       "   1,\n",
+       "   2,\n",
+       "   4,\n",
+       "   5,\n",
+       "   6,\n",
+       "   7,\n",
+       "   8,\n",
+       "   9,\n",
+       "   10,\n",
+       "   11,\n",
+       "   12,\n",
+       "   13,\n",
+       "   15,\n",
+       "   16,\n",
+       "   17,\n",
+       "   18,\n",
+       "   20),\n",
+       "  'cv_scores': array([ -18.72982353,  -18.21386078,  -17.22919608,  -41.13467647,\n",
+       "          -29.52654902,  -47.90213922,  -15.468938  , -110.244478  ,\n",
+       "          -21.41984   ,  -16.222326  ]),\n",
+       "  'avg_score': -33.609182709803925,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   1.0,\n",
+       "   2.0,\n",
+       "   4.0,\n",
+       "   5.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 17: {'feature_idx': (0,\n",
+       "   1,\n",
+       "   2,\n",
+       "   4,\n",
+       "   5,\n",
+       "   6,\n",
+       "   7,\n",
+       "   8,\n",
+       "   9,\n",
+       "   10,\n",
+       "   11,\n",
+       "   12,\n",
+       "   13,\n",
+       "   15,\n",
+       "   17,\n",
+       "   18,\n",
+       "   20),\n",
+       "  'cv_scores': array([ -21.03076863,  -17.61220392,  -16.9243    ,  -41.07060588,\n",
+       "          -21.27527059,  -39.4243902 ,  -16.38433   , -110.244478  ,\n",
+       "          -21.61098   ,  -16.222326  ]),\n",
+       "  'avg_score': -32.17996532156862,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   1.0,\n",
+       "   2.0,\n",
+       "   4.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 16: {'feature_idx': (0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 17, 18, 20),\n",
+       "  'cv_scores': array([ -20.7128549 ,  -16.68289608,  -15.94327451,  -39.08645882,\n",
+       "          -21.16402353,  -33.9949    ,  -12.76474   , -110.244478  ,\n",
+       "          -21.61098   ,  -14.631844  ]),\n",
+       "  'avg_score': -30.683644984313723,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
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+       "   'TAX',\n",
+       "   'PTRATIO',\n",
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+       "   2.0,\n",
+       "   4.0,\n",
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+       "   24.0)},\n",
+       " 15: {'feature_idx': (0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 18, 20),\n",
+       "  'cv_scores': array([ -17.38447451,  -14.54187059,  -16.36607647,  -40.6064098 ,\n",
+       "          -19.76402549,  -24.36852549,  -11.723442  , -110.244478  ,\n",
+       "          -21.575576  ,  -14.36848   ]),\n",
+       "  'avg_score': -29.094335835294117,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'ZN',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
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+       "   'LSTAT',\n",
+       "   2.0,\n",
+       "   6.0,\n",
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+       "   24.0)},\n",
+       " 14: {'feature_idx': (0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 18, 20),\n",
+       "  'cv_scores': array([ -15.47649412,  -15.62870196,  -16.36607647,  -38.25011961,\n",
+       "          -17.67698039,  -16.34627255,  -11.321552  , -110.244478  ,\n",
+       "          -21.575576  ,  -14.36848   ]),\n",
+       "  'avg_score': -27.72547310980392,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
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+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   2.0,\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 13: {'feature_idx': (0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 17, 18, 20),\n",
+       "  'cv_scores': array([ -14.04488627,   -8.56591373,   -7.5407902 ,  -36.93559608,\n",
+       "          -19.23471569,  -15.82070588,  -10.864592  , -110.244478  ,\n",
+       "          -21.575576  ,  -14.36848   ]),\n",
+       "  'avg_score': -25.919573384313725,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   7.0,\n",
+       "   24.0)},\n",
+       " 12: {'feature_idx': (0, 2, 4, 5, 6, 7, 8, 9, 10, 11, 17, 20),\n",
+       "  'cv_scores': array([ -13.39004706,   -9.16693529,   -7.5407902 ,  -36.16776667,\n",
+       "          -13.44812549,  -13.67466863,  -10.0655    , -110.244478  ,\n",
+       "          -21.575576  ,  -14.36848   ]),\n",
+       "  'avg_score': -24.964236733333333,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'INDUS',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   24.0)},\n",
+       " 11: {'feature_idx': (0, 4, 5, 6, 7, 8, 9, 10, 11, 17, 20),\n",
+       "  'cv_scores': array([ -11.2704549 ,   -9.04511961,   -6.94720588,  -35.48608039,\n",
+       "          -11.30051176,  -11.52504118,   -9.59246   , -110.244478  ,\n",
+       "          -21.575576  ,  -13.7815    ]),\n",
+       "  'avg_score': -24.07684277254902,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'B',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   24.0)},\n",
+       " 10: {'feature_idx': (0, 4, 5, 6, 7, 8, 9, 11, 17, 20),\n",
+       "  'cv_scores': array([ -11.82551765,   -8.96506078,   -7.09830588,  -34.97691765,\n",
+       "          -11.7925549 ,  -11.85132941,   -9.56625   , -106.904468  ,\n",
+       "          -15.1106    ,  -14.6951    ]),\n",
+       "  'avg_score': -23.278610427450978,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'DIS',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   24.0)},\n",
+       " 9: {'feature_idx': (0, 4, 5, 6, 8, 9, 11, 17, 20),\n",
+       "  'cv_scores': array([  -9.32726667,   -7.36407647,   -7.02446078,  -32.77597059,\n",
+       "          -10.87262745,  -13.40577059,   -9.047856  , -103.1104    ,\n",
+       "          -15.27333   ,  -10.161066  ]),\n",
+       "  'avg_score': -21.836282454901962,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'AGE',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   24.0)},\n",
+       " 8: {'feature_idx': (0, 4, 5, 8, 9, 11, 17, 20),\n",
+       "  'cv_scores': array([-11.5716    ,  -7.55505686,  -7.02216667, -27.58590392,\n",
+       "         -11.27631373, -12.15971373,  -8.573062  , -97.046328  ,\n",
+       "         -15.475302  , -12.494264  ]),\n",
+       "  'avg_score': -21.07597109019608,\n",
+       "  'feature_names': ('CRIM',\n",
+       "   'NOX',\n",
+       "   'RM',\n",
+       "   'TAX',\n",
+       "   'PTRATIO',\n",
+       "   'LSTAT',\n",
+       "   6.0,\n",
+       "   24.0)},\n",
+       " 7: {'feature_idx': (0, 5, 8, 9, 11, 17, 20),\n",
+       "  'cv_scores': array([ -9.21804706,  -6.65025294,  -6.92848627, -28.71330784,\n",
+       "          -9.52150392, -10.69602941,  -7.262248  , -97.060308  ,\n",
+       "         -14.501176  , -15.170368  ]),\n",
+       "  'avg_score': -20.572172745098037,\n",
+       "  'feature_names': ('CRIM', 'RM', 'TAX', 'PTRATIO', 'LSTAT', 6.0, 24.0)},\n",
+       " 6: {'feature_idx': (0, 5, 9, 11, 17, 20),\n",
+       "  'cv_scores': array([  -7.41756863,   -7.58010588,   -6.96252353,  -22.70133725,\n",
+       "          -10.09713922,   -8.54933725,   -8.411888  , -101.324748  ,\n",
+       "          -14.501176  ,  -15.138676  ]),\n",
+       "  'avg_score': -20.268449976470585,\n",
+       "  'feature_names': ('CRIM', 'RM', 'PTRATIO', 'LSTAT', 6.0, 24.0)},\n",
+       " 5: {'feature_idx': (0, 5, 9, 11, 17),\n",
+       "  'cv_scores': array([ -7.46448824,  -7.46147843,  -6.91899216, -22.70133725,\n",
+       "         -11.65047059,  -8.54933725,  -8.52223   , -97.911562  ,\n",
+       "         -14.49901   , -15.074004  ]),\n",
+       "  'avg_score': -20.075290992156862,\n",
+       "  'feature_names': ('CRIM', 'RM', 'PTRATIO', 'LSTAT', 6.0)},\n",
+       " 4: {'feature_idx': (0, 5, 9, 11),\n",
+       "  'cv_scores': array([ -7.12655294,  -6.73561765,  -8.00023333, -24.01952353,\n",
+       "         -10.94252549,  -8.24724118,  -7.19716   , -97.958812  ,\n",
+       "         -14.49901   , -15.093622  ]),\n",
+       "  'avg_score': -19.982029811764704,\n",
+       "  'feature_names': ('CRIM', 'RM', 'PTRATIO', 'LSTAT')},\n",
+       " 3: {'feature_idx': (0, 5, 11),\n",
+       "  'cv_scores': array([ -9.12226667,  -6.7015902 ,  -4.46690784, -24.66997059,\n",
+       "         -15.34621176, -12.83467451,  -7.361062  , -92.118568  ,\n",
+       "         -14.316582  , -15.791666  ]),\n",
+       "  'avg_score': -20.27294995686275,\n",
+       "  'feature_names': ('CRIM', 'RM', 'LSTAT')},\n",
+       " 2: {'feature_idx': (5, 11),\n",
+       "  'cv_scores': array([  -9.47129216,   -8.65154902,   -7.54689216,  -22.24765294,\n",
+       "          -18.09018431,  -16.51726078,  -11.423768  , -103.10757   ,\n",
+       "          -20.573036  ,  -14.295642  ]),\n",
+       "  'avg_score': -23.192484737254905,\n",
+       "  'feature_names': ('RM', 'LSTAT')},\n",
+       " 1: {'feature_idx': (11,),\n",
+       "  'cv_scores': array([-20.51551569, -18.63969412,  -7.87550196, -41.69083922,\n",
+       "         -43.71370588, -76.4581    , -29.269912  , -52.896014  ,\n",
+       "         -21.690854  , -12.23778   ]),\n",
+       "  'avg_score': -32.498791686274515,\n",
+       "  'feature_names': ('LSTAT',)}}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sfs1 = SFS(classifier_pipeline, \n",
+    "           k_features=1, \n",
+    "           forward=False, \n",
+    "           scoring='neg_mean_squared_error',\n",
+    "           cv=cv)\n",
+    "\n",
+    "X = boston.drop(columns='MEDV')\n",
+    "\n",
+    "sfs1.fit(X,y)\n",
+    "\n",
+    "sfs1.subsets_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 4.458\n",
+      "R_squared: 0.765\n"
+     ]
+    }
+   ],
+   "source": [
+    "X = boston.drop(columns='MEDV')[['CRIM','RM','PTRATIO','LSTAT']]\n",
+    "y = boston['MEDV']\n",
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),3)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),3)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "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>CRIM</th>\n",
+       "      <th>RM</th>\n",
+       "      <th>PTRATIO</th>\n",
+       "      <th>LSTAT</th>\n",
+       "      <th>MEDV</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>CRIM</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.219247</td>\n",
+       "      <td>0.289946</td>\n",
+       "      <td>0.455621</td>\n",
+       "      <td>-0.388305</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>RM</th>\n",
+       "      <td>-0.219247</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.355501</td>\n",
+       "      <td>-0.613808</td>\n",
+       "      <td>0.695360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PTRATIO</th>\n",
+       "      <td>0.289946</td>\n",
+       "      <td>-0.355501</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.374044</td>\n",
+       "      <td>-0.507787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>LSTAT</th>\n",
+       "      <td>0.455621</td>\n",
+       "      <td>-0.613808</td>\n",
+       "      <td>0.374044</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.737663</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MEDV</th>\n",
+       "      <td>-0.388305</td>\n",
+       "      <td>0.695360</td>\n",
+       "      <td>-0.507787</td>\n",
+       "      <td>-0.737663</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             CRIM        RM   PTRATIO     LSTAT      MEDV\n",
+       "CRIM     1.000000 -0.219247  0.289946  0.455621 -0.388305\n",
+       "RM      -0.219247  1.000000 -0.355501 -0.613808  0.695360\n",
+       "PTRATIO  0.289946 -0.355501  1.000000  0.374044 -0.507787\n",
+       "LSTAT    0.455621 -0.613808  0.374044  1.000000 -0.737663\n",
+       "MEDV    -0.388305  0.695360 -0.507787 -0.737663  1.000000"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "boston[['CRIM','RM','PTRATIO','LSTAT','MEDV']].corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston['RM*LSTAT']=boston['RM']*boston['LSTAT']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 4.458\n",
+      "R_squared: 0.765\n"
+     ]
+    }
+   ],
+   "source": [
+    "X = boston.drop(columns='MEDV')[['CRIM','RM','PTRATIO','LSTAT']]\n",
+    "y = boston['MEDV']\n",
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),3)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),3)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x1240705f8>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x900 with 30 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sn.pairplot(boston[['CRIM','RM','PTRATIO','LSTAT','MEDV']])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston = boston.drop(boston[boston['MEDV']==boston['MEDV'].max()].index.tolist())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 3.502\n",
+      "R_squared: 0.801\n"
+     ]
+    }
+   ],
+   "source": [
+    "X = boston.drop(columns='MEDV')[['CRIM','RM','PTRATIO','LSTAT','RM*LSTAT']]\n",
+    "y = boston['MEDV']\n",
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),3)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),3)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boston['LSTAT_2']=boston['LSTAT']**2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = boston.drop(columns='MEDV')[['CRIM','RM','RM_2','PTRATIO','LSTAT']]\n",
+    "y_pred = cross_val_predict(classifier_pipeline, X, y, cv=cv)\n",
+    "print(\"RMSE: \" + str(round(sqrt(mean_squared_error(y,y_pred)),3)))\n",
+    "print(\"R_squared: \" + str(round(r2_score(y,y_pred),3)))"
+   ]
+  }
+ ],
+ "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": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}