Housing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "generic-shipping",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "import tarfile\n",
    "import urllib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "continued-cuisine",
   "metadata": {},
   "outputs": [],
   "source": [
    "DOWNLOAD_ROOT = \"https://raw.githubusercontent.com/ageron/handson-ml2/master/\"\n",
    "HOUSING_PATH = os.path.join(\"datasets\", \"housing\")\n",
    "HOUSING_URL = DOWNLOAD_ROOT + \"datasets/housing/housing.tgz\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "prerequisite-brunei",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_housing_data(housing_url=HOUSING_URL, housing_path=HOUSING_PATH):\n",
    "    os.makedirs(housing_path, exist_ok=True)\n",
    "    tgz_path = os.path.join(housing_path, \"housing.tgz\")\n",
    "    urllib.request.urlretrieve(housing_url, tgz_path)\n",
    "    housing_tgz = tarfile.open(tgz_path)\n",
    "    housing_tgz.extractall(path=housing_path)\n",
    "    housing_tgz.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "earned-myanmar",
   "metadata": {},
   "outputs": [],
   "source": [
    "fetch_housing_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "round-quantity",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "straight-encyclopedia",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_housing_data(housing_path=HOUSING_PATH):\n",
    "    csv_path = os.path.join(housing_path, \"housing.csv\")\n",
    "    return pd.read_csv(csv_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "greek-family",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY  \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY  \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY  \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing = load_housing_data()\n",
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "distinguished-rebel",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   longitude           20640 non-null  float64\n",
      " 1   latitude            20640 non-null  float64\n",
      " 2   housing_median_age  20640 non-null  float64\n",
      " 3   total_rooms         20640 non-null  float64\n",
      " 4   total_bedrooms      20433 non-null  float64\n",
      " 5   population          20640 non-null  float64\n",
      " 6   households          20640 non-null  float64\n",
      " 7   median_income       20640 non-null  float64\n",
      " 8   median_house_value  20640 non-null  float64\n",
      " 9   ocean_proximity     20640 non-null  object \n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "housing.info()\n",
    "#데이터에 대한 간력한 설명과 전체 행 수, 각 특성의 데이터 타입과 널이 아닌 값의 개수를 체크"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "registered-boston",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     9136\n",
       "INLAND        6551\n",
       "NEAR OCEAN    2658\n",
       "NEAR BAY      2290\n",
       "ISLAND           5\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing[\"ocean_proximity\"].value_counts()\n",
    "#어떤 카테고리가 있고, 각 카테고리마다 얼마나 많은 구역이 있는지 체크"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "configured-moisture",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20433.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>537.870553</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>421.385070</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>647.000000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20433.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       537.870553   1425.476744    499.539680       3.870671   \n",
       "std        421.385070   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        296.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        647.000000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()\n",
    "#숫자형 특성의 요약 정보"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "talented-recall",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "modified-session",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "housing.hist(bins=50, figsize=(20, 15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "every-partnership",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "impossible-romania",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "surprised-herald",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_train_test(data, test_ratio):\n",
    "    shuffled_indices = np.random.permutation(len(data))\n",
    "    test_set_size = int(len(data) * test_ratio)\n",
    "    test_indices = shuffled_indices[:test_set_size]\n",
    "    train_indices = shuffled_indices[test_set_size:]\n",
    "    return data.iloc[train_indices], data.iloc[test_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "north-medicine",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_set, test_set = split_train_test(housing, 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "jewish-huntington",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16512"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fifty-sunday",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4128"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(test_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "charged-addiction",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "lonely-divide",
   "metadata": {},
   "outputs": [],
   "source": [
    "from zlib import crc32\n",
    "#python2 와의 호환성을 유지하기 위해 crc32 사용"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "square-shade",
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_set_check(identifier, test_ratio):\n",
    "    return crc32(np.int64(identifier)) & 0xffffffff <test_ratio * 2**32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "competent-exhibit",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_train_test_by_id(data, test_ratio, id_column):\n",
    "    ids = data[id_column]\n",
    "    in_test_set = ids.apply(lambda id_ : test_set_check(id_, test_ratio))\n",
    "    return data.loc[~in_test_set], data.loc[in_test_set]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "guided-munich",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_with_id = housing.reset_index()\n",
    "train_set, test_set = split_train_test_by_id(housing_with_id, 0.2, \"index\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "convertible-brush",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_with_id[\"id\"] = housing[\"longitude\"] * 1000 + housing[\"latitude\"]\n",
    "train_set, test_set = split_train_test_by_id(housing_with_id, 0.2, \"id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ambient-keyboard",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train_set, test_set = train_test_split(housing, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "republican-tennis",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing[\"income_cat\"] = pd.cut(housing[\"median_income\"],\n",
    "                              bins=[0, 1.5, 3.0, 4.5, 6., np.inf],\n",
    "                              labels=[1, 2, 3, 4, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "egyptian-netscape",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing[\"income_cat\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adopted-software",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "mobile-first",
   "metadata": {},
   "outputs": [],
   "source": [
    "from  sklearn.model_selection import StratifiedShuffleSplit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "dated-interaction",
   "metadata": {},
   "outputs": [],
   "source": [
    "split = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42)\n",
    "for train_index, test_index in split.split(housing, housing[\"income_cat\"]):\n",
    "    strat_train_set = housing.loc[train_index]\n",
    "    strat_test_set = housing.loc[test_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "civilian-beverage",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    0.350533\n",
       "2    0.318798\n",
       "4    0.176357\n",
       "5    0.114583\n",
       "1    0.039729\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_test_set[\"income_cat\"].value_counts() / len(strat_test_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "portable-alcohol",
   "metadata": {},
   "outputs": [],
   "source": [
    "for set_ in (strat_train_set, strat_test_set):\n",
    "    set_.drop(\"income_cat\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "voluntary-bangladesh",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "eastern-intent",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing = strat_test_set.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "hourly-system",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='longitude', ylabel='latitude'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "diverse-masters",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='longitude', ylabel='latitude'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\", alpha=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fifth-pride",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fcc00425a30>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\", alpha=0.4, \n",
    "             s=housing[\"population\"]/100, label=\"%population\", figsize=(10,7),\n",
    "            c=\"median_house_value\", cmap=plt.get_cmap(\"jet\"), colorbar=True,\n",
    "            sharex=False\n",
    ")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "abstract-biodiversity",
   "metadata": {},
   "outputs": [],
   "source": [
    "corr_matrix = housing.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "civilian-photographer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value    1.000000\n",
       "median_income         0.691831\n",
       "total_rooms           0.131435\n",
       "housing_median_age    0.071357\n",
       "households            0.071242\n",
       "total_bedrooms        0.057568\n",
       "population           -0.016033\n",
       "longitude            -0.039987\n",
       "latitude             -0.150124\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "turned-orlando",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.plotting import scatter_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "reflected-classics",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:xlabel='median_house_value', ylabel='median_house_value'>,\n",
       "        <AxesSubplot:xlabel='median_income', ylabel='median_house_value'>,\n",
       "        <AxesSubplot:xlabel='total_rooms', ylabel='median_house_value'>,\n",
       "        <AxesSubplot:xlabel='housing_median_age', ylabel='median_house_value'>],\n",
       "       [<AxesSubplot:xlabel='median_house_value', ylabel='median_income'>,\n",
       "        <AxesSubplot:xlabel='median_income', ylabel='median_income'>,\n",
       "        <AxesSubplot:xlabel='total_rooms', ylabel='median_income'>,\n",
       "        <AxesSubplot:xlabel='housing_median_age', ylabel='median_income'>],\n",
       "       [<AxesSubplot:xlabel='median_house_value', ylabel='total_rooms'>,\n",
       "        <AxesSubplot:xlabel='median_income', ylabel='total_rooms'>,\n",
       "        <AxesSubplot:xlabel='total_rooms', ylabel='total_rooms'>,\n",
       "        <AxesSubplot:xlabel='housing_median_age', ylabel='total_rooms'>],\n",
       "       [<AxesSubplot:xlabel='median_house_value', ylabel='housing_median_age'>,\n",
       "        <AxesSubplot:xlabel='median_income', ylabel='housing_median_age'>,\n",
       "        <AxesSubplot:xlabel='total_rooms', ylabel='housing_median_age'>,\n",
       "        <AxesSubplot:xlabel='housing_median_age', ylabel='housing_median_age'>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attributes = [\"median_house_value\", \"median_income\", \"total_rooms\", \"housing_median_age\"]\n",
    "scatter_matrix(housing[attributes], figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "prime-payday",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='median_income', ylabel='median_house_value'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tJVylOIlylpoen7neJvAdorxiqenzxc0elebCOc7IDI/7TUop2Ow3eHmlyTQt7UbIldxaCjFGPHGcs7+ntNQ0XEWleeQ8z2JteJpxZu/pNxr8oR+7TVxU7I8T4qLip37n68800S+eZ8tkIUQTkMaYSf33LwL/IfC7geNTCfglY8wfF0L8PuCPYllkvxn4vxljfrRO8v8G8OV66K8CP2KMORFC/Brw7/Agyf/njTF/WwjxH593jsfN98033zTPQ4vsk8Iii4qSg2FKK3TnY8RZyWrbJysrdkcJ3cCjMgZjDEmheXm5ieepD8wim+QFx9OcftOfM4airOTmUgNh+EAssiQruXNsSQVIwcE4pagMN/oh17o2+f04FpmrJHdPIrTWICWeECAF1zr2hz5jkTVq1lRlDIGjnppFlpYlWycx7aaLJxWl1mSlZr0d2Ptah0tm516wyBYssse951mwyIQQv2GMefOR48/ZwLyC9VrAMtb+mjHmTwshloGfB24Bd7EU4pOapvyfYplgMfCvGWO+Uo/1rwP/23qsP22M+cv18Td5QFP+O8C/XdOUzz3H4+b7vAzMJwVaG+6dWKKAoyRlZUMYt5YaABc+d/aH/zQ/pMed+4P8ME8zn46mOVlV0fYdrnVDHCkufY7LMJOeJZvwSQym58FaXGCBi/CRGJiPGxYG5sl43AL2vBe9Z714njVacVZw5zjmjfX23AuYeUluneB+0q73ot3s0xjHq57veRnhZ4nn6c0v8NHhIgOzkOtf4EoIXMWtpca5i8R5z52mUTrKkgz2RulTLXqPO/fT4AEDxxqpwHNwZJ3MrxfoWcL0rHFba9vczel5SCmQPDqns+dxlCQrS6qapXceLmNMz57vac7zYWLhXX36sJCKWeDKmMXEz1vgzz73rKnaZ8c/W4l/FZxl4GhtWGv7GMNDCVPgoVqDSmu+em/A3eOIeycxaVFd6TxPYvo8rsbi7LWevv7nyVr8oHieNWELvLhYeDAfQ7wIYYbLzuH0onfWK3jaMWf4oDviGZtmb5SSlSVSCG6vNHGEeIgcUVR67hlobRjEBUoIwvpcT/LIpLQez84wAVHhSPlYps95nsg4ybhzEiHr+3na8J2+/rPX86xYix8UL7p3tcDzwcLAfMzwIoQZrjKH8xbx8xa9q17Xswq9nQ275ZVma5igaw9rte0TOmpuJA2Ql9WcjSWFuFS462CSIbDFWGtt/7HXdtYo52XFcZRze6mBV9cy7Q6TubzH2et/FmHEZ72JucpGY4FPDhYhso8RXoQww9PMYbaI36wXv7OL69OM+UFDb6dDS6dpsLN5KCk4nKR87d6Q+4OYXsOlqAxZXSjaD935gnnZcFcrdAldxcEke+Tazs7ndG1DVmiWWx6e+2D3X1R6vlifvf7HhTAvg7SouHcSc/8kfmII8LIhyudZE7bAi4uFB/MxwosQZrjsHM7ugE8npM8+9zTX9UF2xBd5S7N5SCk5Gqe2Kl9ohIBhXLDZCzECNnohB5OMKHtyGOoy13bRfGaeiDCwNUweulZXWcWBZ+0RXMUzvKrX+axJGgu8+FgYmI8RXoQww2XmcFUqs1cr3l7lui4bejuLxy2gs2vLi8qqUCv72HcUSVFhanVeV0lu1QbpqjmovLT6ZLMC0Cct6DMjdPZaN3ohwFNd/+PmfZUNxNOEKC9i2i3wycTCwHyM8LSL6oc5h8ctPMCFzz3NdZ3d5RvBPMR0ER63gLrKJt93hslcYXmjFz6iIzW7D5dZKE/fr3GScRzlLLc8toYJ17rBXKfqSQv6Rbv/q3gEl/E4LruJeRG86QVefCwMzMcML0KY4XFzeNzCA1z43GzMWZOuWU7kSZDSKhLvnAohXe+FF4ZqnrSABq7ipeUmq22fo0lGpQ3GcGlDfp6HELiKzV7InZPooUT93ihlsxde2ns7z6hd1tBd1uO47CbmeXrTLwJLcoFng4WB+RjiRQgzXDSHJy08j3surxe9qzDkylLz7v6EcWabkhljm029vt6+sE7nSQuolIJ24NL0nA9Emz5djGmEvfbTifqsLDHi0fDXeQv6kzSvnjTHq3gcl9nEXMaTfRoj8SKwJBd4dlgYmAWeKZ608Fz03FVi+rPFqyg1W4OYb++OaQcOa50AJSQHk4yXVpr48vyF6bJe4FUM+dn5T9OCr94bWIVdKVlr+xcaV9eVj53Ps5DguarHcZlrv+g+Po2RmLHRdocJ3jnU64Un8/HEwsAs8MxxVTkZuPwOe7Z4ldouPstNl8BVKCk4nuastLzHzu30zvqyYbjLYM5AE5KsqDiJ8oeKMQ8mGWttn4NJdq7hvWhBv8jwXu8EbA1iXEfg1xTlJy3Gyy2Pw0lGVupnlr87O++nSf7PPtO8rNgfZ9xabuCoRV7nk4CFgfkQ8GFKcl/1XJeVN3+a+V1ESz7vOWEeHz6bvXa2eLlKoYRgklUsNVzGaUleVcS5ZK0TnGs8nqaY87L3Qwkrq38wTjHGsDfOWOv4DxVjus7DngpgG5c9Zvxzq/rTjPeOp9w/Scgq2/sk9JTtO3LOYnz6ugWw0vZpes5z8Qqumvw//Zn6rssgztkdJtxebp5Lrljg44WFgXnO+DCVhK96rtOvn7UndmvK8Nn3PmmxfZowztnneg2XYVxcmIs4vXhpY7tBZkXFRi9EjVOyUrPRDbnRPz+s9qSd9elrfFw+6MJ7YZtyghBIAVVlwECpHxjLmXE9L1+j6rFOF0k+QnMuKo6nOTd6wbwHTlJU+EpwnFe8fqbe8bzrPp7mNJeez0//qqG4swbpWjfk3nHMJC3wHLUoxvyYY2FgniOelZzJZRfHq5zr9OullBxOUoxhvnM8/d4nGa6Lzr3ZC69EWT5dzHieITu7ePVDl528AmMXpsftzJ+0sz59jWA9i5bvPDLviwxPZWxb5VvLTbQ2rHcCtk6ScxfKs/drEuf843cOUUrO8zW3V5oEtRzN6byVNoblpofnKPoNjzivbAdM32G55WHE1a77WeOqVPqzn6kjBTf6ITd64QdSI1jgxcDCwDxHPKsf92XGueq5Tr++rGwveCEedH6cU4v1xbUrT8qf5FpfOCc4n7I8My6zcz+WQislX77Vf0Q2Hx71Mh63sz674Kd5yfY4o7PmPjS3or728+6FMMy7NnqOvaaLFsrT9yvOS97am7AzTNjsB6y2A4ZJjjuUvLTcREpxblW/NobQU/hK0AkdNtoBur5uLR7UAs27bxbVnB79vMNOV6HSn2eQrvdC/AVz7BOBhYF5jnhWtQKXGeeq5zr9eikFxth6DyUe1te6jOG66NyefHyF/nnPFaVme5Jd6C1dZvG6yOO6aGd9Wi0ZmFOJs7Ii9Jz53OB8ozhJCw6nGVlZsTdOWW56hJ4zb5l80b3Pi4r9UUpVVTR9h8B1GKcl7cCe8/Q9Pq+qv+EqjvOK5ZZHWmkwsD1MHlFbLsqaENHyCF3nQwk7XYWB9yLUdi3wfLAwMM8Rz6ry/rK1G1c51+nX61LTCz0QkBTVw+/VT06+X3Rux5FXoiyvND12Rgm+kvOF/bS3dBkG2ONChRctZGcN5Nm+MLN5z/JTM6OcFxVJXvLNQYKU2FBY2wdpr+XgAkM5u19bg5ikqFBK0Qns2ElRUVVWxPOizcHp63i97l+/PUxqZWX5iNpy2PJpBQ5ZodnshTiOnN+rF2VRfxFquxZ49lgYmOeMZ7U7u8w4Vz3X2dfDoyyy08YjKQowcL0XPjL2Rec+G96pjCErKlwlH3quKG01/vYwoek7rNaS9jNvKS8uV4T5JI9rtpDN6i5mcz2vL4yn5CPXc60bcPcomhuPvKpwpWSlGdg8UlrS9R32ximhpy4MKwau4qWlptXvx7A/yTgYpVQGXllpnnuPT+P0gmxq9YPTyspRVgLQ9O1P3HMURWXmOZpFQeMCHwYWBuZDwLPanV1mnKue6+zrz3tv4CrbMGuUILA1Hdfq3MBF1OQZThdF3h/EHIwzgIcS2WjYnmT4rqQVOBhtOJxkrLd9BLZaf3ecntv75CwD7DJ05yepFz9kYM/QqR0h8BzJzaUQJQT3TmJO4pxOYHMccZ5T+gpXiIcW/PPyYY4j2VxqsDdKWe8ELDVc+k2Pnu9ZjbIn6KrNcF6I8nFqy8+yjfUCCzwOCwOzwBOhteFgkhG6ar5Y7Y3SeeHgRbvg00WRu8MUg6YT2ELI04nsmdcROg4rLZ+jacY0LZm4EiUl9wfxYwvwZuepKo0RsNTwGKflhRImO8MEJSD01HyxPatefBqnDdKM0r3U8tHGEHiKduWQa02WaLSBm70GR1F+qXzYzLAdRxlv76ZsDxNGScmrq016Df/SnsXZIsrHqS2fzTm9aAWNL1LoboEPhoWBWeCJOC/slOYFO8Pk3DAQ8JDsh6sUAsMgLumFtvgwrxtmzReSegc+85Y6voOQthJeCsFJlLM3SuY04NO78Z1hQlFWDJOCvKzYG6Z86WYP31OPLFJRXrI9SPBdiZKCldpQXKYQ0FGKvDY2rcCxVOHQJckrlhseomZANXwHx5GXzodpbXh7b4LvCOLCXvPWMKHf9J5INY/ykqNJhoFziygvk3N6kbpLLkJ3nywsDMwnHM9iN/gQ40wIsrKyC7J8NAwU5SXH0/wh2Q/Pkfieoprm5FWFY6wo5SyRfS5JoBdyOMnm42/06gK85OG6kklasH0cczBNmWQlS02fqtLcPYn43Eb3Eery0STDVQJv3sEyYbUdXLoQ0HMVyy2PrNAUlTmXKq21QUnx2Jqe08i1ptIG13fQpqDpOwziHGqK8UXV+TvDhO1Bgqusx+LUcjmniyjP88qeFfnkWWMRuvvkYWFgPsF4VrvB2YJ09zia51BWWx7GPBzjF8DhJMN35COyH8sNj2lSMk1t8vlaJ3gokX0e4eBYWEMlha2M3+yHXD9VVzIzGEjDJKtoeA7TrKAbuhxNc4pKPyR4WRmDwRqrw1mSvjSstv1LFwKWlSZ0Ha53AkoMnpRzVtZF99x1H6955knrTRWlbU08SXI7H8G8vuZ0bctsIVYCfFfiKcnhJONGL0QbfalQ14tIDV70mPnk4dmp/S3wQuFp+txfNE5RaZyaGnxrKeSV1SaBZ+VaslLPe6wvNb05hdcuriFFZZikBVJKfuhWj+u90HaxPMfQSfmgl7yUVjrm7nHMOwdT7h7H9Jsefl3dDg8MxrVuSKVtbqSqoNdw53UrpzEzFo4U3OiFrLV9NvshTe/ifdbMuJ7uJd9ruOyMU/ZGKVvDZN6z/mnvueNIvnCjyzSvOJpmbA0TXCEZJQV5qdkeJtw7iefnmS3EXi3yCdSfRXXpUNeLmOc4bcyBFyp0t8DTYeHBfELxLHaDszDM7AdfGUPDc9itd+hZofniZpeG71CUmv1xyv444zjKWGsHeI7kRj9ko2OL/nbHKU3feYgo8Lj8wjAuuL3UQEiBqR93AveRXILrKD6z3uI4yjDYY0u1qvJpJpaUVvNrZ5iAAEdKNnpPDg15SrJRFy4qIawBOCeMc9E9LyqNNOKxi3kncLm51OBWP8RzlS04Haa8tGJlYc5r7ay1YaXlszdKyEtbKHuZ63lR8xwvauhugafHwsB8QvFBE7laG+4eRQyTHCEEldbEWUXDU4SeA9jq/+Mop+k5HEwyPEey3vF5a2fM/ZOEjW7I6+st9ifZlaXY58yymXehbNHj2er22YK03PYxCHoNB0daL+h0VftMePNgkiGw5Sdrda3N7HrP29GfXYyXW96Fhvu8ez6r7zHwxPodKQTNwMrTCCHm5zx7nllr59m8VtsBq5dUSH7WeY5n7Qm9iKG7BZ4eCwPzCcVlCiQftzgUleZgktEOHngc46SsK89tzmAWmpppjkkpmWQlt5YaZGXFWsvnnYMpt5cbtAP3QibYebisgXyoqn3VLtQ786ZVDzyl08KboedS1te3qSRJWc2ZWKeNwHmL8dHE5qBOEx5EPV94mC4MgGA+l7yo2BrEvLTUfChvc971mpooMBPfPK+189MsxM8yz/G8PKFFVf8nB4sczCcYM8ovMC+QnMXx06Li3knM/ZP4ofj+k8a73gtZb/tcr1lLpzXH8qKiqkNSrqNwXWUf1wvgRi8kLw2TpKCorBxLZcy5OYrzch8XhUtmYpazKnXDw1Xt2phTwpsPjid5yXvHU752b8j+OEVJ8VDe5MFi/OA9Blht+0yzkncObE+WvNSM04J7JzGHtYe02vbnQpeOkqRFxf4kY3uQcOc4euR+n73eysAXbnSpNBde/yxnBXZD8LhczyyXdroQFZ4+z/GscnwLfLKx8GA+wbioQPJxMvqzBcxVkrWOzyDKkfXida0bcLPf4GCSkeQPNMtmmmM7w4SssK/d6IV2Z39qF+5IMWeCVfXcHrf7vewuPc7KeV5FCSuYWTqPF97My4rjKOdGN7iQiXWeFyUARwiUFNxasvmSvKz42v0BLy83afrOvOfKZi+cG97DSQbG0AocfFeeG5aaXW9RL/6uknQC96mEPR+5P6MEYUAp+cS+O5fBgvG1wGWwMDCfYDyNjP7p/MbtZavHVdTSIxu90C6Cdf+Ts5pjLy03WW37HE0yKm0wQvCFG12GcTEXjdyod/U7wwghIHTVY9v9PilcEmclX703QAmB59oeMQjISv1Qa+CzwptaG5ZbHoHvoJICOJ+J1W+41rsRgtLYBmL3BzG7o5TNfoguKvZGth7FcyQb3RBPSUptVQVmopZRVtIKrFKB56hH8kkzPK7R2VlcJp8yuz9SUPeQcZ/Yd+cyeJGLNRd4cbAwMJ9gPK2M/gyBq7hdS7mcFcA8b9GXUtAOXJqe89B7zu7CJ2nBVl1NL4Vgtf34avqLoLVhZ5QgBbRDm1cZJLYOZqMTYAQP1amc21flAiZWXumHRC2XGi6OknRCl7zUDKKc42mKRiDQJHnF7iC2umLtwNKn2wG+p7jVa4Cpa1aci3uynGcwdobJhc23nsRaE4ZaFkc8uD9xQT90MYILFakvgwXja4HL4EPJwQghlBDinwoh/lb9+GUhxK8KId4RQvx1IYRXH/frx+/Uz790aow/WR9/Wwjx46eO/9762DtCiJ8+dfzcc3yacFEeY7abv2x+40mdBWfx/Vn8fZYTmeVXTo+hayFLz7HV9I4U7A6tiKYwT84lnMbMUMwWbUdJsrximuTcO4nYGSbzOpXZHMEurKfvQaUtE+tLt3pzr21nmDBMctqBQzd0GWUFB+OUQmuOphkbvQCD4GCcME01n91oM800h+MUMHQCh6/dH3L3OGJnnLLS9h+bT5ldz+mcT6kN24OEu8fRI3kyrQ1laeV28vp4WWmKytbN3D+JuXMckVUVnisfCg3OPJcPipnBvrnUmLdDuArOfm8W+OThw/Jg/hjwHaBTP/6PgD9rjPk5IcR/BvwbwF+s/x8YY14TQvxk/bo/IIT4PPCTwA8A14FfEkK8UY/1F4DfA2wBvy6E+AVjzFuPOcenCpeR0f8gdNDTtTKOklw/JbJ4XpinqDXI1joBJ1FuCyQrm5vYGiZzwcrrXavpBRez3ZQQKCXpN1wGccFJFLMzSEAImp7DWjdgo2MVCNw62T9j0zV858J7MJujOCX9YhWdMyo0k7TiWifgWtcHY/Ad23pguekS55IKw53jmKrSbPQCXCUuFZY62wRub2TrbdqB+1AY8bR3lZcaKW0oLnCU9ZRmrLW6Adq1ts8oK0mSAm3svX1WnsZlGV9nP8MXtRZngWeL5+7BCCE2gd8H/L/qxwL4XcDfqF/ys8C/VP/9E/Vj6ud/d/36nwB+zhiTGWPeB94BfrT+944x5j1jTA78HPATTzjHpw4XeSGX8U4eh1mtzOEk5aSWhXn3YMJuXYh4ll00M0b744yDccpS06sZaQGTtKTSNsR1ME756r0BcVY+lu02K5w0gKcE+5MMIQWltu2ER0nJ4SSzis5lxSgpOJxk87EvghJWYy0rKrYHMVuDiHf2p6w2PJq+i9GwO0zZ6ISstQNKDUWhKbWtXwkdW2EfeIrjKLdFkcbMw1IX3e/THuckKchLS5aYab5pY3f8p72r5ZZnDYoQXOsEuI4df2bwl5seSEE3dFlt+3z5Vn9uuD8snP0M46xcMNA+Jfgwvmn/V+CPA+368TIwNMbMfuFbwI367xvAfQBjTCmEGNWvvwH8yqkxT7/n/pnjv/kJ53gIQog/AvwRgFu3bl396j6huEwB3axWxnMEk7Qkr3u+fG6jw7Wu9WTO9rP3HMmt5Qa7w4Stk4Qb/ZC1TsDBKGWQFDhSEIQek6RgaxDjKlnXkTyaxJ4VThptOJpmLDc9Kg3DuJjnYqZ5QakNg1TiK0U7dBknOTujhOvd8Fwmm5R2sb57FJEWGoOhHbqEgcNmv8Fq02drkFBqw1onYKXto6SgHTrsj3MqAwbDUtNSxK8i4XKaSebWIUR4QCee/S2EeIQ+LaVl0B1OUoSwhbC90OOlpeYHSuh/EFyUVxJA6Lnz+S8YaJ9MPFcDI4T4nwAHxpjfEEL8c8/zXE8LY8zPAD8D8Oabby62UFytgE4bw0lU4DuK0FWkeckgyllqeHiuemhhnCWkHQW3l5tM0mKewDYC8rIiCK2emec+2LHPdtynFyI084VLSoWSMEorPCXpNT0ORilDk+MJSSt02B0k3FxuQqXxHIWpzIXtBmwdj+TWUoNXHVv0uD/NKEtbme8q2yhsNnd4kA9q+DFKwHon4GCckhX60hIuM0gp8KVio6aTn06iz+pqjDHzWhatbXW/ElYg0xgQ9f8z8oQrH3hOH6YO2XlEBER1YTO0BT5ZeN4ezG8D/kUhxL8ABNgczJ8DekIIp/YwNoHt+vXbwE1gSwjhAF3g+NTxGU6/57zjx485xwKPwVWkRFwlWW15vL2f19ImcK0X0gtdskpTaPPQwvhQ33tj8Bw1Dxld79rFdJIUp+jGwna0rHMSs2T2nEBgDKWGg3HKMCnJ8oqwoYjyAs8VLDc8XllpoRzJ1+8NuXccc6Mfstz0mO0kHCXR2opmVtUDJeJZfkdJgeMqWkXJd05istqz+MKNLv4pozvbeV/rBPOanKtIuJyHi3JE13shRWm9R4C1js9Gnd9xlZwz/8pSc3+QoGQ0b3EAF+fHngfOYzI6Us6b1S0YaJ9sPFcDY4z5k8CfBKg9mP+NMeYPCSH+a+BfweZM/jDw39Vv+YX68T+pn/8fjDFGCPELwF8TQvwZbJL/deDXsAXqrwshXsYakJ8E/mD9nn9wwTkWeAwuU0B3egf80kqLk6jAYOpEt4eU8tyE9kW0Vq0NriP50maPvXEKAmS9CFXGsH0SczjNAbuY5pV+qJ+L7yiWGi7fHWcYctY7Aa+vtYjyimYtjvlDN3vcPY5oeWpOIT6KcqZpwSC2jcq0YV6nc5qGm+YFJ1HBD212CT0HbR4V3gQe0Tq71gk+cL7jvCR64CpeX2/z0koT4CGG3izfo4Rga5ziOZaiPGvMJuDCkOPzwEV05ovqqRb4ZOGjqoP5E8DPCSH+FPBPgb9UH/9LwH8phHgHOMEaDIwx3xZC/DzwFlACP2WMqQCEEH8U+HuAAv5zY8y3n3COBR6DJxXQnRc++/Lt/nzXLqWcU6HP4rwd+dnxrvdCXEfOd+il1hxOc9baHp3Qm7OpNnshvYbL1kkMBoZxyQ/e6GCMoN9weP84RtT5mI1eaIU4uw8aix1MM5qe4u39CFdKfNd2pzyYZNyq8zCz+aY1tbddC1HCo8Kbp1sxNwJnnmt4aflR3bFngVkY7eyx2WKel5YOfWu5YaV6lCCqiQ3nhRyfZ+7jIk9soTn2yYcwZpF2mOHNN980X/nKVz7qaXzkuCgHo7Xh3klch89qteDKzNskX3U3etF4m72QewOby5BSsHWS4DqSGzWj6iTKcKUEYdlcS02XSVYSOIpC27xEUWrWOwFH04y8NFxr++Ra0wlcNNbziXMrVHlrqUHoO0hhi0Cv90ICRz2Us7joumeewzDJ+dbWiMBTVvNLQFEabvRDNvuN+f17ljv2s7U9p+c7q4fxT4l+ZqU+5cE8eh0LLPC0EEL8hjHmzbPHF5X8CzyCi3acs/CZFFY+Rgkx1+1ylbzybvRsOE5KQZ6VDJOc7brSXwjQGPK6TXNZWJ2v28sNPEche7AzTG2SHVhp+RyMMzxH0fAcbi07HE1mBZI5UV5RVNo2GTOQVxW7o5SXVpskNX12ptn1EKvsgvBenJVsDWN2TxIGScG68hhEhdVu64X4yuqOzXIOT5v7OK+OZFYLAzZ0eHu5OZ+vL5XNB40SRG4VsE/XKC1yHwt8GFgYmGeEF6FD4LOcw9nwhda2Kj8rK3ZGMaYyCCVYbT3az/68eZx37HQ4bta5saw0+8MUIwyesl/PVFeAIMttqGq5aZtwATQDl2s9WGp6DCLbJrnShrWGOycGjJKSm0shSakpCts1stG3Ss8C2zcmK+05bi83aAXuI/mJ84zuTOdLG80wK2iHim9vTyiNwVGC19ZaeK5imhSPZaw96bNMi+ohscq1ts/eOJ3XwgAMohyvTvCfpnDDo71vzgpqPu5zW2CBD4IrGRghxG8HXjfG/GUhxCrQqgsfP9V4EaqSP+gcLlpctDZEecnRJENrw/f3J+wMYqSUtif8zYfzC+fNA85nLs08g/ePpnx7e4ySguWm1S3zlCSvF0EQ886ZohabTPIS37FCmY6UBI5N3mtt6DddSm1lcLQxLDc9AtdhpWWr46OsZJzmuEoROIrbSw1aoeJonD82P3Ha6D7IuQg6oc8kLdk6SVltu4BACEFUVLTr/M1szIvGvugeZoWtxp+FurqBw9agQhszr4XRxmBqoc6zFO7TvW9muaXzBDUv+owWWOCD4NIGRgjxHwBvAp8B/jLgAn8VS0X+1OJZdwj8KOZwkXGaVd5vD2xlfr/psTfKCDyHa90AbeDuccLnr5V4nkIYHpnHbt3N0b+AueTV9RvXOj6dhq2B2R4mLCmXa52gXjwfJNijwlb3H51ild3sN7h/Es+7bxpj6AQuN5bDeYvjedtnbVhu+hSVIclzWoGHEDBNKg6mGetRRrsmE1wkSDnvYSOw9Tq1YObWSYwOHVZbAUJCnFVkheZ6zxZ0Xqbu4/RnKaVkdxQzjHI2lxocTa0qQSdwLNXaGKKs4CTKSQtNpeHWkgZHXsgEPG18zhY+fpjssgU+HbiKB/P7gR8GvgpgjNkRQrQf/5ZPPl6EvhgfZA4XGadZzxglmPdLORjZhTotLE1YCEFWaO6eRLaosrT5mJV2MK8tmVWxNy/wDIrKtg7wPZsEd5Sk4UqKylCUGqXkXN14d5iwNUjwHMHmUogEKvOgmdrp7ptH05xXVpmLWp5+78srTQ6nKfeOc+K84ka/ge9YFtk3d8astHxcJfnsRpu0rOaKzKf7qggpqLShH7oMkoKyMiy1fD633qbd8EizkqzS3Oo38DzFNSkem/uYGa6y1ORlhe9YarGSEiEFe+OUpuegTYUSAiGg4Sne3puiBHPdtYNJNu9Dc55BO++78lGxyxb45OMqBiav60sMgBCi+Zzm9LHCi9AX44PMoageLGjwaM+Y0FM1I6qiNIaqqiiNrRhPi4ooL5HAKClIcxvO+ayBpNSkZUlZGlbb/rlzS4uK3VqbTGuNBiZJQanh8xtt1rqBTcYD905ixCljdxLlXO+FJHkdFsJWrZe1wTqNWSfOotI0A4e9UUroOqy1PY6jnP1xxnrXpxE4hJ7iRr9BlBb88tuHLDc9HCV5ZaXJe0fRQ31VMFZ7rBu6dAOXz210OJxmfGd3zDAu6IX2nr600qLhOxeKi84MV1ZUnEQFealp+jnr3QABdALHtqvOS/JKI0KX46hgteXx+nqTpYaPVAIMJIW9H6dbNz9k0DSPfFccJecFrYvK+gWeJa5iYH5eCPH/wFbI/5vAvw78P5/PtD4+eFH6Yiy3PI7OW1AegxkDan+YcuLmbJzTBjnJSqZpyTv7Y9JSE3qK1cDFU5KGq1huuRwlOQ3XodvwyMuKt3bGLLVdpmlFJ3DZH2dIYeVXTK3fVZaa+ycRpbZstKMoZ3+S8cZ6i1fX2nhKcjzNaS4581136Kq57EylDXlhvaPAUXQbDu8dRMyqHF9Za1oF5VO5Jc9R5EXFNCmYZOXcO2l6krWWz94ow3OtUOX7JzGuFPQaHkVZ8Y++f8S1XkCn4T/UV+V6TZ0WxnqSh9MU14GNns8oLnl7f8pxVPAjt63I5FmPYEYUEFjJneWWS+BJDIatk4TVlkcndFEyQwpLSggc69U0fYf7g4SmVzGaluSFJikqilLju8qy6s4oCZz3fV2wyxZ4Xri0gTHG/CdCiN8DjLF5mP+9MeYXn9vMPkZ4VtL3T4PT+RPg0tIkpzsdSseKJN47jtnsh9bQOJat9NW7A4ZxwfV+g07ocDTJWW55bPYa5GXF17dH7A9T2qFHN3QIfYdmWTJKSlwpKLTBU4LSaKpccxzZ3vVpXnGc5BSlZqXlc70fUhpD07My+lKIeZhm5qFpY72h3WFi+7gYuF5rfLlSstxy5wZICcvyOopymxAHHCV45yDmW/eHpJXmlbUm2hgOpzk3lmx4b61hQ1N5rmmFbm0YFYUxSPlglx/nOUa4uDUZYXeYMIwzvrs3QQlBXtm8TOgpBJYQ8Mpq65Fala1BjBKC0HNs589c0w4cbtTe2e1layg3+yW7w4TdUYqQgpWWZYX1my47gxTHsQl/txKMkoLbDZtHOp7mhL2HK+Yv+r5+VN/hBT65uBKLrDYoC6NyDj6KquTz8iezXf/Z151eOE4zoGadDvNK0/UdrvfCucaW60hW2h5KWjqwFAKBrYHJK81RVPCF613eO4xI85KsrHh9tcn9I43rSDqhR1ZWjNISow2uK+kEDrvjlL1JAkbUi3XF8SQjdJ05E0zzIMl+etetjWG9VjCeGdJJWnA0zXEdRZZbvbL9UcrxJGdzKUQpyfYgZmeYstxy6Lc8jDYkmWap6dIOFJu9Brf6TauPVVVooGYAU5QVviNZbflMsuqhvioAd48jjqcZB5OMKKvQusJ3XQZxTqfh4nsKBPOcxmxTkJe2BsdRM7kcRZyWNOo20qe12tqBS7hiDe/pzpi+Umx0A8LAwWjD7jgFmNcmjdOMO8eR/X6eYfCd/b4uKusXeNa4CotsAnONQA/LIouMMZ2L37XA88RlkvvnMcSUFHMG1IMdeYly5EN1EUoIfEdZIUttKI1GCFudfr0b4kpJK7QtkvcmKWlegRC8ut5ke5AyTQtcR9H0FBWGsCYGGA2OUrR9h3FakBQVvit5bbXJOC1JigqnlpwBmyfylDx3h326Q6Y2hjvHEXll6IcO/abNsTxgsdnryUrN5lJIWcFKyyMr7WLs1/pYUV6SZCXfP4jYG+estn1+22srpIWmKyUEzHuvZEXFwTgjdCWhq7jRD7l7FJEUJVkB1/sByw2vpnWLhzYFvuNyPM1ICo0jBcJodsYJjiOojg1f3Ow95Ek4jlVx3hulRNmD8NZM/0w5VmXZGPvZ5UX1UFHqgh22wIeNq4TI5oyxU03Afux5TGqBy+FJyf3HMcQcKecMqIs6HUop2OiF5JVm6yRhEOf0Gi7GAAYqDHFaEPgON7qhZU31GuyMUzq+y1Gc1wrFsNL0GCYFRVVhhEFrjedIXl9rszdM6IQOoaO4fcNWo89CT3eOo4e6ZXpKzum2Uj5gRS03Pb65MyYrKuKiohc63D1JuNU3NHwXx1U4SuApRTtwidICqWzoaK3tP2RYj6c5K+2AlU5AmpUYIVhrW2NXGTPXSdNTMy8SbfrWECthFaVfXm4wiAs2uuFcn03KB6w5R1kauDFwNM2ojEuh4XPrbXzXAQz7o/QRQc3zwlszhpouNb3QA2GT/WWl6YbOpetvFljgWeOpKvmNFTD7b+vamJ9+tlP6ZGAWlhKGZ9LsqSw1udZzyiw8mWBw2sPR9d9pYReYGXW36Sk6vsONfuNc5d/AVby60kIAL69YOu80K/jV909sBXtSsNT0uN4N2VxqzGnBe6OU1aY/b3+cV5rd0Ql3JhlGa5YaPo6EcVbQbrj0ApfdSUqJwXesKvPWIGYYFyglMNpwEqW0PJv3mEm5zIyoMYZKWwZVv+Gx0g6QIuM4KlDKJu5fW2mxO0rqRV7Q9xW90OP2SvPcewbQCj2izDZMk1JQFZq7g4iGo2j6Tk00sHTswJEcTjO6gUMn9Hh9vYPryLnBLyqNMJbFlRdV7XlJXl5t0vEVX98ac63Tmrc7PhilvLTSPFfU8rSBOGt0AKK8tG0M4pI4j7jWfUDgWLDDFviwcJUQ2b986qHEFl2mz3xGnwDMwlJJXnIc2aR46DpPXR09jHO+tT2i0gYlBV+40aXX8IDHEwxmHk6UFuxNUg5GGYWeNcAKbRdEYfuePM74GWF3v0oKdkYJ28OEo3HC5250WWn5DOKMo3GG68h5aOvsgnd/EBN6ittLoQ0fldb4Hk0yrvcDcm1ouIqTKEcC39sbcecwZrVje9rHecU7BxNeW2ux2W+w0QvnRZwbXau5dTjJOJxkbPYVozjH9xRvLDe40WuwP045GGccTnOudXw2+w3cOmTnnQkLnvYK86IiyUu2TmKmecnbexPyQtNtuHxmo0039LjWC6xByDJ6DZdr7YD1Wqp/poRwWMu2SCHoNVyOphlRVtIKHFZbPrPbnxYl00hTlNYTS4sK/xJCmWdVBo6nuf1u1N1DZ71wZqy3BRb4MHAVD+Z/eurvEriDDZMtcAqzHbWSEBd2VxtlFS3Pear4d1lqvrU9InAkgeeQ5iXf2h7xYy8vP+TJnBfymPWs/8rdE46nGb7rsNEMGMY5R9Ocl1YaNH3vibF5JWzjr91hgqPsAuw4imlW0fRdppmmG9j2vkowH2sWdsrqepfAlfiuwzApuHs8ZaPbINeGu8cJrcDh9fU2O6OUax2faVZSaMuyMhj2hwm51kSFz7uHEWApuLImKgSO4gev93hbjOmGDkIKXltt4khFy3UYOoprXZ/SVMS54e39KWsdn2atfnzaS5hRvsdpweEkIy8qXFdwOM5peIq81EgBb+9O+OKNLsLAKC4JHYXvKUJPcTDJWAP2x+m8wHPmRQzjglu9BhjmCfu8rFhuehxMcpvYV5JrgctxZB9fRSjztBd2tnuo/wLLvyy00D55uEoO5l97nhP5pGD243aFpNKGhucQ5yVCCnSprxz/zrUVbwzqgsPAc4jyjFxrHJ7cZ8R1JOstH1dKmn7Nukpy8qqaU3ovis2f/sGvtG0ferD95nuhS5ZrkrQgyW0l+N44xZGSpq/mY2ltOJqmfHtnhOtIfGVzIZOk4mbPVqNnecnxNGOt7WIwFEXFyTQnykqmWYkrBO+fJISOZG+Qs9oRbA9ilpoenmdrWwzQClw+s9FBScE4LTkY5ax2fe4NY6ZpQVZo3juI8ZQgcB12BhFFBYFS3Kybd80IEbqWg1lteXzvYEqZVbx7GPHDN/t0Q7e+jwXTokQYS4HuhB5pUbI7Tug3PXZGNnk/Kw49mmZc74XoUiOUeCRh/8WbPd7aHlkJHUdyrWuLQ3dGCaF7eaHMs17YaUbai4oXQc9vgWePJxoYIcSf5wF77BEYY/6dZzqjjzlO12woKUhzu3gYfb621ZPgSTkfZ+bBKGkLIS8DU9XaWdjksq7sR+nVeRng3Mrt2Q++1BqMZU3d6IcoAb2myzfujTiKYia5i6k0N+oeKkVZcTyteH3VjrF9EvNP3jtiFOU4rkKSM0qt0RimFXlp1Y09pdge2hDT/VFCqQ2m3snuDCJavuRGveC+tTvklZUWn8ew1PQ4iXKyQqO14eZyE4yhOI65vdQg8B3ipOD7e1M2+j79hsu9Qcz+aMxKy2Oj22R/mlIag++quWZampfsTHM8t/bMlIM0cP8kYrPfpNuwVf8v9ZvsjVM8RzOMMu6exEySgk7D4bPXOmx0G+cWh9qWzIKNminnKklaVAgpMFiZnTgrwNgNwFUS9S9K8e9l8SLo+S3wfHAZD2bRgesKOP3jbrhqnoOpDE/1I3cc2//9W9sjojyb52Au0yVxlrtJi5LDSU4vLGkFLmsdn/VOYAv7skcXoNkPvqwqjmsJ/K1BzGeutYmzisNxzs3lkC/f7mGM4e2DKSdxwVGUo6Tg5lJIZewYcV6yPUzxXMXBJGWp4TFNCj5zrUWWFwyTgm5oZVZuLTc4GKW8fxihhCArKlaaLqPYhsBGaYkU0PFcPn+9Sy+wxmWjE7BcG5qqbiuw2vEJfIe0qNif2tqWg3Fu70Pgkeaa9U6IEQbftXUyN7ohTd8u+F5dixLVNOr3DyOisiIaxPSbHk3f4Ys3ejiOzV91fMU37g+QQtAKXDb7Ae8fxSw3/XOLQ08rGoNtQXAc5Wz2QnbHKfeOIk7inFdXmjiO4rYUNOs2ApfZqHyUxb9XxYug57fA88ETDYwx5mc/jIl8knD6x/36M2CR9RoeP/by8iMssschzyu+cW9I6Ek6QUjDU6SF5ss3e7Z7oxR0AvfcBaiqVXrfP44oSsMwtgWEu6OEN9ZbdALFWveBoGKaa270fELPJS8rpmllJVnSgmGUz0UW+w0f17EtjdsNDyUEpTYsNa0isucoRomVS+k2fNa6PnvDFEcKNvshqdYcjXMqYL3j14bPCnB6jmK9rk0RBraGCXlRsT9OqXRFM3BYabpUlcZxBIdTUMqGovZHGdOstLmsOtSla/ryb9wbsDOIrWCl55NpTcNVNH3J/iTFT2yILsoLK5jZ8lht+YSeQ14YkqKaz21WHAq1tpoxFGXF0STn7rE1qjeXGzjKVvbf8B36Ld9qlQ1TrvWYkygu8136uBROvgh6fgs8H1yFRbaK7XP/eSCYHTfG/K7nMK+PPa76435SgtNx5KVyLmBDU+8dTbg/jGkHthWwoyTjpCDTmuYpXarz5igMHE4zitK22Z2kJUWpibKSdw8jDFbavdfwyYqKTuAgpa1bUUriUtmFeZQwSUpW2x53DiOkEigtaIU+Tdfh5lKDu8cRpq6puXM0ZRAXGCO5ezglKa0HsbncxHEEHeniIOg2Pb67N0UKUEKy2Q/RNSHglRUrx7Lc8rhzNOX7+xPSsqThuhyYglwbrjUC2rc8otx6XV5Tst4JkMA3t8estX1WOz7dhouuNBqrNTbJK3xXMM5LosMIJSWfWW9xHOekRYVU0PJtsWqSFQSewyvLLYR6sFjOpP5HSc6do4jDSYqrFJtLIa4S7AwSjDBIAa6j8JSicgxN3+FaJ6BRG6hZR9EX2TO5LD5uIb0FLo+rsMj+K+CvA78P+LeAPwwcPo9JfdrwLBKcp+tu7h5FDKKCOK/YH2estDzWOgG+Y1WIe6H3RFryattnGBcMooxhUpAXGseRdBsuZWn4+taIlaaHELa5VlZWbHRDHCX46t2IW/2Q19fbfPP+kElWcK0f4Du2uDD0FCdxQcu3VfbTtODX3z/hejfkej9kf5wQ5Zpey6EXuggMk7zketsjD1zuHsXEWYmnFK+uN/na1tDWlpSaaVoQ+g4COJxkCAwbnRDPUURZST90WesFlJVhe6BZafr0Wi4CQdt3cV1J05Xsj1K2B9a4ulKQ5zak5TgCV0mudUKM0fzjd45Y6wZU2nCzF/Lt3TGdwNa3/LbXVvA89chnXJWa7+yOCV1F6DkYA3ePY37H6ytsD23eq6gMK22HpCjZHaX0Gi6eI1lp+4yT8hOXDP84hfQWuDyuYmCWjTF/SQjxx4wxvwz8shDi15/XxD4teBYJztOLV1lptoY29v/Z9Ra/dueE3WFCO3D4getdZB2uepx3pYSg6bm8ttJg+yTClQbjCHqhx72ThM+st+mHLoXRCARKSo4mKQfjnNdWG7XopZWq/8GbPd7Zn/LKSoN7Jwm3+g2mRUXbFRxEOYGycjOVtp0pV9seB6OUpi9Zawb0Q49v7owYRwWB46ArQyu02mFgeHd/itaGzeUGrq9453CKI62G2vYwYRBllNru+LNCc2s5JK0l/o2GrUHMNHEJfAfaMIgLDoyhrCwFOyoqRklOXmimeYEq7eL3/uGUpudghGacWh224zjj5ZUmLy3Zws0kr+atprcGMb6ShJ7DROckua1xGUQ5jpIsN21d062lhiU6HEccTDMOJjm9QKGU4Gia8c3tET90o0u7cT69/DJU3xeVDvxxCektcHlcxcAU9f+7QojfB+wAS89+Sp8uPCnB+aTF4HTdjSskxmhOopylhke34fPGepsor/jSrR6eUhSVmWtiXaQ0YBV3Jb/+/pS0rNBG0gokpdaErmKp4SKVRBjB0STnejfglbU2gyidh+NmrDdh4EY/5HMbXfotH0cItocJe6OU7+9O+PyNDreWmhxOMnaGMULaDmISQb9pBSM9R/KFzR6lrtgaJGR5RVJUHE0yvnl/gHQUk6Lihzd77CQl/YbHKCnYHyUcTwtW2wHTtGKSFES5y3f3x1QVtEOX28tNjqY543HKyTTls9c7jOMKJQVbJxFLDY/AkYyigigraAYOcVrhuYKkLMlKaLiajW6D+ycRw7jg2M+pjCErNQ1fMUlKtgYxgae41g7wlSIrK653Q9Y7AfujlFFaYAz0mx7745RBUjJOCvaGMUNP0YwKXl1uAHAU5zRD95FOlWcLOs/zbhZ04AU+TFzFwPwpIUQX+F8Dfx7oAP/uc5nVpwjCWCORl9VckPB0Q64nLQaVMSR5SVxUVNogBLR8RVSUte6Wlb8vKoPASsTMWiFnZcUgLh5RGihLzTsHU24thTR9h0prkkLTbzocTQoMcK0dsDWMraaYq0jyknFaYUxBJ3Rr6Xm7UH9xs0crcHGinPvHEeOsQggzp+/6jjVad46nLLU91jshvcBja5CCtovuUtNjlBaWAhy4TNOC/XFK6CuudZt4Eu4cRxRVxTiFjcDO/b3DiF/+zh5RYVhte1zrhxyMUpK84sZSg+u9kNWmh9P1OZralsuVMfRCh2ngkRQVrivJq4q273KtG9LyFUYIeqFVjPYcW6yppA0V7oxSxnUrgv1Ryg/e6DDJrME4HGe8ttbk1nLD6oUVhn7L4wu9kM1+g71xyiDKafmK949KS20uNUtNybtHEZ2Gi67MQ4rTRanZOqeg8zzvZkEHXuDDxFUMzK8aY0bACPidz2k+nyrMDEihNXvHKctNj7Dudw+P9k4/bzEQBo6jnMCRNOo6Gd9xWG8GpHVYaK1tpfbX2j5aG37j7gBjNMO0ZLnhPaI0MCvu7DV8HEdxPM0ZxAlV5fDyapMkKxmlOd2GS5RVHE0TpqlmueXiO1b6pBu4rHcDAkfNWW9NT/HW7rgWnbQaXMfTnPVOQVZqer41dJ6S3OiHbOSBNa4Gvn8Y2US6tKrIu+MU31G0eg2EMBxMC5Y0vLzSIqsq0qJka5Cw0vToNl3uHkcIYDDNEBLGSYYzhGGcsdQMuL0ccqvXYLnhITQcjDOGSc7LyyHDRFKWtg1zJ3TxXCuRv9bymaRWi0wqwWbX51feP6EoDQ3fYa2tuH+S8L2DKevtgCiviNKS+ycxgXJoe1ZxYK3l47nOXAxTSoGpu2WudQOOpjYHlleG2/0Gcd1YzJG2Z8/BJHuo2+fpgs7T4dAFHXiBDxtXMTD/SAhxB5vo/2+MMYPnM6VPB07vJkPPp+U5ZJW2SseOfEh1Fy5eDIyw0iZRVhHXRZ0bvYDNpQbbw4TeivtAqn2cEmcFB5MUV0qOogwpYEX5DykNODPWVGoLIF1pmKYFq20rQFmVhu1hwlLTA2M4mpagrWLyatvHcxWFtoWLswJBK6ufIoTtQCml7XDZlrYfi44Nm8shYa27tTOM6QQuSgj2pxlRVoCA19dbBI7tr/L9vQlCCNuaWEM/dPmxV5b4J++eEKUlgZJ4noNSkn7Tt57bKEVrw/vHMcOkxHMlndCl0vCFG22+dzhFScnmSoNX15scRTltIxgnBW9ca1OUBkcIfKl4fb0zz6/MWha/vNoiLzXtwDYu08awM07wlMQAvbaLNLbAcppX5IXmYJrzpU0b/pqFL5US8w/4tdUm2mjCStENPT67Ec5FNJ/U7fM01XdBB17gw8ZVpGLeEEL8KPCTwL8vhHgL+DljzF99brP7BOPsbnK2KJv6t37ZxUAJQeg6tOrdsNG2mE9KUUuOPDBQoyTn7lHEOMnxlO17cv+4YqnhzZUGZlL0Qhl++e0jPCWZpAXr3ZDDSc4gsp5LpTU7w5SNbsDrqy3uDy291rtgrkVlu1le7wVM0pKqMhwnGb/l1WVeWW2zP0qpjOHt/QlpXnI4zbi51GC1FdTtjBN2hglGG0ptiHOrE9YNPSayYrnhYTAMk4IfvNFhZ5wwSnOStOKl5ZC2J3lnf4rGyu2/tFz3sq9bByDgJMnpN9255D3GVtjfObakiTjXVFUJjuRLN22vloNJhqskRli1g8oY3t6dEOcVxhgbLkwKjiYZQkmSrGSpFdAJPToNa3hPooytQYzjWHmhpq8YxiVrLZ9hUtD0FZ7j8bmNDstN/+FwluaJ3T5nWNCBF/iwcdWOlr8G/JoQ4v8E/BngZ4GFgXkKPMmAXHYxeKjbY6nnr3OVfGj8KC3YGSXcOYnnxX5NV7E3Tgk9SWU4FW4xjJKSL1zvkmvDwTBmlBQ40ibwh3FB01M4jp2L59pCwqLUTNICz1Gstf158hmsgQHoNzwGUU5SlBSlYbWu7RBSMJhkbLQDdicJG52QyoDRml+9c0Lbk9w9jizl2FOorEQieO1ai5bvEGUVo7TinYMpS00fTyneWO2wNYyJc4PnOtxebTJJS+4dRxihKExF2/cwxkrEuFJwMMrwpWSU2R73WVFZD8F3CX1DVbkEnsR15CkP1FbYH0U5t5eaCGN12bQxeG7AjV6DaVailGWWgaHUuqZOF3xvf8q1TkDgKfqhi+u4vLbaRkrrSZaYCwtsn9Tt8ywWdOAFPkxcpdCyA/x+rAfzKvA3gR99TvP6xOM8A3J6UT6vdzo86Clymvl10aIxGz8pCvZGKTe6oa2PyUrKSrPS9LjW8Xl1pU2rrurXxqCAsrJ9Vcazxly65GSaE+cVoWtzJNPUilxqbXCV4Fq3wc1+g0qbufpvVlRUWtd1Kpb5lZQVk7QicCXf3h7R8ByWmx7bgwRHGowRbC6HbA8Sdicpldb4rstK0yerKoajFIlkpeOhK9gepJSlZq3nc/c4YneYcnOpgTaGm/0GX77VB+CrWwMORxlRUqIxjOISJSRNTyGM4DguSPOS7x9O6AQuvuvQ9iU7WwmvrjfxHQdjDNOsmt8rKWw4UwB5aUkNr6212VxqIAzsjBKOpjnLLZ+8sg3GGp4iKzR5odkZ2dxbO3RtB8o4p9/wcE51F/We8F26qtFY0IEX+LBwFQ/m68B/C/yHxph/8nym8+nC6YVh3iXxDGNsthg8qcfMeYvGbPy0rGyjKyVQUlAZS2l1lWS9G9hqdlfh1V4PwuAoQZRZYU2t7Q76lbUm++OUojJ0ApeO76AcSZRXrLQ81jsBSgh2J3Znn1eGb++MOIkK1js+nhLsTzKanmKtG9ByJd8/mNgixeUGy00XX0kbntKGlqv47kFElFZIY/BcRVmU5KUBKrLKoJQt1FzvBPzgZo+3d8cMo4z1rvVicm04inIAmziXgrVuyMEkodtwaQQOt5cbhJ6i0JpJWpFXmk7goquKtw5j9sYx47zgjdW2Td53fCvsWWkOximlNhxNMlqh7f8ipJh7kP2mx+4oZZLm+K7DUtO1OZ5eSK5tnu1gmrE9iJHCejgNVyHMJ6taf4FPJ65iYF6pO1meCyHEnzfG/NvPYE6fKkgpQMP2JLuQMfZBesxI+SCpvj9KudELcaUkH1QEvuSVtRaekuwME270wnmYbLMX8u5hRNNXdBoub2y0CR3b+dJzBC8tt2i6DkZYNtxJlHM4ySgrTVZWLNV5k2lW0vSt8nBSlJS6IisESVnxbi2GWZTayvIrRdNXGGM9oKzSeFKwutxEKcMgydma2HbMYeihAIw1xr/ppT5lpdkeJDa/M814dbXF0dSG9kLPIXQVvpL86CtLFGVFWRkcJbl7EpMVMSdxzmtrLQ4mOe8ejvn1uyM6gUPbd1n3FDujmC/d7HOzX99vY1sXHE0zDAaJ4TjKUFJye7lJkpd8dy9mqelyMi0IGxJVa4k5jkRq2+xNVwaDDWeCVbe+N4jt53eJWpVFbcsCLyqukuS/0LjU+G0fcC6fWjyJPvpBe8xI+aCfi+9Kltse7dDWx3hKUmrDdi0aqYSg23BZb3f4/LUuuba1HJ4r6x12yd4442SaM1Ila22fQVzgOXac/VHG9jBlvVPU3TNrXS0lSXOBEJKobjlwMM7IjaaVFLy0Jtkfxry+0eblpTauKzgYZlxfbzOKcyZpiRSKl9ZarDR9uyCXhigvuLXc5Nu7Ew4nmZVYafk4UvL27oRXVpuEdT5is9dgtzZqDc9lpe2wP8q4uRRa+XxHMslKKqPZHeYIDR3fw5GGe8cJgSu4P0yQQnCj38B1JKstn/vHCWlZcTBO6Td8rvdDCq0ZJAVSQK/p0214ZMUDluDsc1lt+2wPEpYbLkbAWstne5jSa9jeP7PNxmYvPFc0dVHbssCLjCsl+Rd4PnhSwv9Z9Jhpes68n4ujJPdPYmuSBOyNElxlay++uTMirzTXugFf3OzRa3g4yia0M12xN87Y6Aa0aun4nZFtQuY7DoeTdF7Ho43maJLT8Bx8xzLR0rLk5eUmaVFwf5Dhe5KmdOk1XAbTAoOwagSAQDLOSvxJZtlVxvD5jRb3BglaCxxH0Awly22Xju9yEmXEaclKJ6DhKfoNj6lTstT2ibKC0HVwHckXrndRSqAQGGC57RG4ir1hQqUNWVXRDV16TYdC+4S+ZGeQME0LNroBk6TgO9mE40nOUttjmBQkZYUrJa3AZZLmHIwFN7oBcVYSuMp+fkpSVA9Ygqc/l+vdAIMhdB0Kbb0Yz32w2RinGXeOIxsGPeOhLGpbFniR8Vxb3AkhAiHErwkhvi6E+LYQ4v9YH39ZCPGrQoh3hBB/XQjh1cf9+vE79fMvnRrrT9bH3xZC/Pip47+3PvaOEOKnTx0/9xwvArQ2ts5FW6dwlvAvKkOUlRSVeYgxNnu+0tBwFWmpafqKUhuWW5e7LCkF13shBkFWavpNj17oEaU2p7HW9vne/oSGp+iGLp4UfGt7RFlqPCVZb/ssNz3WWz6tusbDYBuaYSArq3lvk9BTvLra5nMbHV5ba5JXhsE0J80rHCVQUnFrKeSLN7u0Ayv2mBYlLV8haoN5MrXJbt9VpFnBwTgj9FxeXWmjtaaqVY5nUjg3eiGd0EXVIbusqmh5isG04Kv3hvzj9444iTJeXm3x2mqbWytNbvUb1gMYJggh6AYOvdDHlxKB4OXlBieTjGlSgrAJ/e1BwjjNScuKJCuYpAW+spuDlq/oNTx8R/DO0ZSdYUqUFeSVJi+tLpk4FQfQ2hDlJXml2R1lvHcUkeTVvCAWsIn/aY7v2o6krrIV+rPnT29O4PzmcQss8FHhWXow532jM+B3GWOmQggX+IdCiL8D/K+AP2uM+TkhxH8G/BvAX6z/HxhjXhNC/CTwHwF/QAjxeSx77QeA68AvCSHeqM/xF4DfA2wBvy6E+AVjzFv1e887x0eKi+LlT2ICne0xk5QVh5OMw0nGscgvFXe/iJXmKkmlbahNKWENWeAyiHLGma03ORhn8zbC60YT5/WiaeDz1zuMYtuS2BjDWiegrDShpwiU5DPrku8fTCkrw+4wxleC7WHGzX6Dl1cbjJOCslYOaAcOSVHRDiwduNKGcSqotOZgmvLSSosfDLqMkpLr/QBhBDujhDTXTPOSpKjwXUWlDcOsZKMbstYNiNOCk0lOvlTh1AWK9wYRd48j0kKz1rE9XLqhy1LLIy4s5RkEL6/ZLplRVlFllpAxSQq6DQ+tNdO0YrXjIRAsN10KbQgcxUZPMYhy3toe0w4cltseW8NkrtSwO0zm8i6bSyESbGO6TmBzUKVVTV5ueg/VM532UBa1LQu8yLiygRFCNIwx8TlP/bmzB+q8zbR+6Nb/DPC7gD9YH/9Z4P+AXfx/ov4b4G8A/6kQQtTHf84YkwHvCyHe4QFF+h1jzHv13H4O+AkhxHcec46PDE+Klz+JPjp7Xmtjd7WOnIfULhN3PyucqbVBSsF6J6gL9DRxVnG9H84rwY8nGYMopx3Yr8ooyXlrZ8L1boBf122Mk5Kb/YbN85zEbJ3YsFnTl5xMc46inK1BjBJWMLMbumwuN6BePDf7DTb7DRqeQ15pVls+SgocKbhzElFWdS+ag4jjSc4b67ZGpCw1b+1NSLKCojT0Gh6usnTvH7zR4etbE1zHVrgbAd/aHRKVFQ1P4SrB/iiz7ZodSSdw+NxGi7SoOBpnLLU8fijosju05Iq396YcRwVSQj90OI4qq9tWaYaxbY3QbxRIYRunha7CcxUNT/HuwZQ31pq0agXk3WGCAeQpeZeTKOd6LyROSxDMcy6z5mmPK7hd1LYs8KLi0iEyIcRvrav3v1s//iEhxP999rwx5r+44H1KCPE14AD4ReBdYGiMKeuXbAE36r9vAPfr8Uqs7tny6eNn3nPR8eXHnOPs/P6IEOIrQoivHB4+3/Y2D+LlD/qra2MX/ec9TlpU3DuJuX8Sc+8kZhjn88cHk4yNXsg/95k1ug2XaVqSlprPbrTtQlgXWDpKoqSgGSiu9QKu90KagYs2NrfQ9Cxx4OZSyCurTbJSM0hzoiRHSRjFGVlRMU4LQldRYfjefsQwyjmc5iRlxc4wZW+cUlaGSVpw7zjm3tGUvKzIyoqjKGN7FIPWjNKSJC/YG2eUBqZpiULgKcXhJGeS5kzTnLLUfOP+iCTX1hMaJfzSt/fwlKxDWpK7Jwlpbj2DoyjHdxSh6+A7iu/sTMAY3lhrst722B9nJLlVQCiNoBM6vLHe4gubPYQUHEcZ++O09ioqhBC4p3IqRaUpK43vPCzvMo5zdscpO8OErTon5DjyseHTGeSMGv2cjMvZsO4CC1wGV/Fg/izw48AvABhjvi6E+B1PepMxpgK+JIToYYszP/sU83xuMMb8DPAzAG+++eZz/fU8Ky2oq45z1nPKi4pvbY9s/YdjmUoHk4xbSw1+6ysr5FrjYHf946SYqz0necXBJKWsYPsksfUgrrJlK7W6r9YG15FkRWWbeHkub08mJFnF3iim6bt4jiDNC6K0AgHtwGWcjdka2JqUdmhzPIO4Is0KJrWAZ5zbBTYpxoxia6TeO4pxpWW+rbou7x8kbPRDGr7Lj768xHuHMeOs4Gia8ZlrbaLMyvZvD2I+f71DN/Q5iXLSoiSrNDf6De6fJOwMYw4nOZWuWGq6LLd8doYJq92QYWobl01SW7BqjMFxVF2Zn7LW9slKuyDvjwr6DUuIcOuNgFvrkj0k71Jo9ouKzdpon/ZKP2oPZUGDXuBpcVWpmPvi4UWsusJ7h0KIfwD8FqAnhHBqD2MT2K5ftg3cBLaEEA7QBY5PHZ/h9HvOO378mHN8ZPig8fLTIa6rjHOaaTTzdIraKMHDcX3XkZSFsaKQdSV+Xla8sz9mnJSsdgKu9wLe2h7xtS1NP3R5abVJWWpKY7h7FDGtach5aSvXV9s+E6ekqCrePxrjOg6uFEipcF1FWpT4RjLNMt683bdV/9ousEdRxsEoo9cAKcFogyts6CmsJW8cKYizAt8JWG17vLbWYrnh43mKhuPQ9BXHUcEwyUgyiPOcKK/4+v0RLy036DRcXltv2/oWIYjzgncPJuyNExypUAKWWj5FqcmzitW2T+g4bA8ThlFOO3RJ8opJWrDU9Hh5xRaklpUmFoZu6HD3JJ5/TreXmwAPybt0Gy4nUU4zcB/5TGa5lo+CFbagQS/wQXAVA3NfCPFbAVMn7P8Y8J3HvUEIsQoUtXEJscn4/wj4B8C/AvwctvXyf1e/5Rfqx/+kfv5/MMYYIcQvAH9NCPFnsEn+14FfwxILXhdCvIw1ID8J/MH6PRed4yPF0+5Gz9tFXnacmccTpQWDpCBJS47GGTd6Ad2GT1lLnWhtKI2eLyhRXvHN7RHf27fSKXYn7/Ir757QaShMYbhzOOXeScIb19r4ruD+cUrgybrTpdW06QRW1r8duKy0G5i6v70QFa+0mzR9l15D2cp8aenYe6MERwm6gc96V5OVGt9xKErN5nIDKSVpaZlTjmMVkUNXMEkF7x1Oue8kVgIGyUbPxxXwj94f4juCYVLQ9ixVO84rNro+v+XVBl+7N2Q/Svm1944YRgXTvLS9YpTkaJQipQQp8JCstByUhNfWmkipWG27dcMwl51RQlnZAsxJWhAVFb2GN1dK9upQ1lnCxTgpXzil4wUNeoEPgqsYmH8Lm8i/gV3M/3vgp57wng3gZ4UQCpvv+XljzN+aKTELIf4U8E+Bv1S//i8B/2WdxD/BGgyMMd8WQvw88BZQAj9Vh94QQvxR4O8BCvjPjTHfrsf6Exec4yPHVXejZakfarl7ehc506s6i7MJ/bW2z1fvDSh1xSSp6LZcvrk15rX1Jp6yuYDtYWJj7VrjSpfv7k6I85LQkfSbHgeTlMHU5hemmeL+SUTDdeg1PY6mCXePU24uBdxcamEMTLOShmsXZY3mu3FO6Fo9L0daKvI7+1Ou9zRNv83ray0MgklSkBaa9XbAYTenGTjsj1NaoaKbOTRq1t0gymi6kkleUZSa7Sih3/ZoeC5VpfnOzoTVjofvCQ6nGaEnaTiKo0nGVMMry01uLzfZGcS8czCh4Tv807tD7hxO8ZTiei8gykpybRgnBV96qY9GsDuIkUry+rU2K62AYZShpGCSlnxnd4ySgji3NOlpVqGkJMoSlls+Wal5ZbWFLx+V9zntlYL1/D5qLCT+F/gguEol/xHwh64yuDHmG8APn3P8Pc4RyjTGpMD//IKx/jTwp885/reBv33Zc3zckBYVWycx28OEpu+w2rZ5j8ftIs/zdlxHst7yOY5zun0PDUzigoNRhutKbvUbNH2HvKzYO05R2GZc904iJqntNZNVmlGcM04rug0PR0p2JxlSST4buhTllFFUUGqNrxzyUuMogS4qvrM95rhu2LU/SokLq4V2rdlio+ez3vFoei63+g2ivORgnHEc5TjCkgpe81v02y5Zrgk8xcE4Y5pVpKXhh2/1WO8GHE9yjqOCbsPleJoxzUrCRFAUVoSyrAyVtNL8lRaAYJSWbI0zThLbWtlRgk4jYG8U40wt663pKraHCavDAE9J2qHHWtsqVkdpziAuuNaxxqPtuSglCB0HKSHOYlZaPlbizXAS5w8lyk9vBGbebZSXHF2Rgv68sKBBP4ontTFf4AGuoqb8fwH+FJAAfxf4IvDvLvrBPD/M4t++K2kFDkYbDicZ623/wl3kRTHzzV6IUDM1AMnuMKHhOzR8h8pou5g7EldKlpseeVFx5zhGa7jeDfnu7qjON1iKb5oVJKVGGoPvSO4dxcSFJiwq3juI6AQOe6PMCjc6hrLSeK5gmhaMC03LsaKRDVexN8zoBj5lFdt8TVpyvRcwSAqWmnA4zXhtvUVQ17f4jmQYFVzvh8S5xpWSKNN4jsRozfEkw6m9g0lW8r2DCVuDBEcKGqGHN8kYxjlJllNogzKGrNQcTDOkASE1vYZLXmlCRyEELIUuWaEJXRddaeK8QgnNSZRTlhVR6NAJHdJCk1eVbSOdFrQDG9YTUqARLDW9+aJ03kbAU5LjaY53RQr688RHTTJ4kbAgPFwNVwmR/Y+MMX9cCPH7gTvAvwz8/1j0gwEut6t50mvOPj/vVug4rLR8jqYZ07QkCRw2euG55zgbM7cy+SVFpekHLu/vT4jzgqLQXOsFSCHISsO944i0KBFC0PBsYnu97TOKcw4miZW+X27QDh22BwmBZ0NIB5OMoqowlctvfW2FvDQELiR5iZTQDBRgiAuNp8D3FSvaxWhDURneP07Y6PiURnPnKAIBrlLcXmqw2vZZaXr0GoqVtkfP89idptwbRigp8FwXJQ3f35/Sabi8vNxgc6nJNClwXYnvC8oShlGJ1IY4K1jvhHz2epeTiZXRd3JNJ/QQEo7HNozW8T3anibLNK9stImzki/c6Fo6tC6Jc81y2+fl1SYvrzT52taQvWFCUlQ0XYe41NzoKbQQ3FxukBdWOSF0rYSN1oYkK+u2z/KhjcBGN3ghcx4Lif8F4eFpcBUDM3vt7wP+a2PMSCzisMDldjVPes1Fu9lZ/DtwbROvoK5FuSh8cjpmXmrD7jAhykreOZhyNEk5jnIw0Gu5LDU9NpcavHM4YRBlZGXFNMlBSLqhS6kN3aaLo+RcwsUm1ysGUUlRGDq+IvQdhBBkhWa1HWB0xZ3DiHf2IzJj6AcOJ1GOwdALHLQWCAx5pYmygqpyuX8S8/JKi8BTFIXmq/cG9Bsu7x1NuH+c0G26tD2Hl5abHE0LprkNxS23Ao6jjEprlJT8lpeXbR1NqckKzTjOGcQlvqPwXUUzVASOpOM7vLxmOBoXtBoOk7hANA2FNnxuo821bogwhmbo8PbelEFUkBQaTzqstz3avsM4tQv/esvnrb0xHd8jygs2lxr4juKffa1vWXCTDIDQV+SV5it3B5S1VP9ra20c9cCQAIucxwuKBeHh6riKFtnfEkJ8F/gR4O/XDLH0+Uzr44PTu5rztKIu85qLngceKbJzHEngqodeV5Z6XgQ3i5nnpebecYzB4LqC3WHMSVyw1vZZallDVRhNkpccjnP6LZ8orxhmmu/uTazsvdYMpgXvHk4oC5v7uHsYo7Vho2/7uyRFRa/ps9L18BwBQvOt7TFZXpIUJVGcc/c44mCcIoGXVlssNX2OopwoK/ClwHcVcW47Ps7aDx9NEr6xNeQff/+YcVKydZLwD9854r/56n3SqmS9EzCKSzC2N81nr7dxayOy0vLZGsa8fzDmm9tDqwWmDb7rEAjJcsurmWs+YLh3FJNVms9sdPiRl/u8stpmkpacxAXf2Z3S9m2YK3DsorLS8fEcSzK4exjx/YOI4bQAYWgGDo2aPn0UZXQbHp+51uHWUoNxXBLlJe3AoRe6TJKSnUGMNmZuSFx1ucLKBT58LHTfro6rJPl/us7DjIwxlRAiwkq4fKpxmV3NZeX4z3v+dPxba8P2MHmogn+cZNw5iZDiYaXd672QotL4rrQGotKM0wJfSSoMy02ftZbPeifAUWN8V5GVmtARjOKcbuiQx5ZSixFsLAUkmQZhmKYVN3oOQkAndKi0oarg/VGMEBClOb6ydSqOkkzTnGagWG0H3FpqkpcTHEeyFHoM05K3dodURrLRCXh9rcXuIGWt2+Du0QQpBDvjmIbrgBQoaenFSVYyiKxH1g89vn5vzCsrLeKs5Ov3h+xPUu6cxOS1NlngWlmbMHRoeS47gwk/sNQhcBTf2xsjlWKl4xO6Dm/tjFht+/SaAdc6cDDN+WffWGV7nNByHQpjmGQF7+xPGScFS20PxxW8tT2iG7rc6AYgYHec0g09pBJ4rm1o5hg1//xWWh5prWvmOWpuSAL5aM5jkVj+6LEgPFwdV0ny/y9O/X36qb/yLCf0ccNlaJyXleO/6Pm5BpkwD70uLyuOo5zbSw3b7fEMfdkY2BkmDKOCe3WSWylBWRimaY7vKhqew1JrpqqskVjDNYxzDqY5vdClKEp85dDtQJwFYKDTcDFGM4lLJsIqIbc8h42Ox/tHgDEErqTp277zZaE5nKZooxknBQo4mKQ0A4ew5bPWDsm04f3jiElesNkPKDQoCVVlcHzJKM0JhaDpOnSbHtnhlIYr6ISKqKi4czzllUGDoyijKC3NeZgWVNogBGRFxf4o5WCSUJSGw0lOr+Gx1A4IHEuk2D1JOZ7mCCHw0pJpUhDntl10t+GSFCUNV/HySovPXu9wPEm5d5LQ9BVHNVnga/dHrHd8igp8R3JzqYkEPGUJA7MdsKMkG12fzfrzOr1Qnc55LBLLLw4WhIer4So5mN906u8A+N3AV/mUG5jL7Gqe9JrHPV+WmlxrPCnnulSz1+larv9075CZ56OEAAECwVLTZ60TMIpzBnFGr+Gx2W9xrRviu4qb/QZHk5SsCDmOUpq+3W2HjiRUgnGpuXM8Za0TstRxqYxhGFl9sbTStH0XR0o8t2JnkrPW9dkbZ0gB7x/FhK6gGXpg4Be+vkPXc+g3ffaGCbmuuNlz2eiGlFXF4ShFCMHOSYanbIuBYVwyzQoCV7FetxzQlaHre+RlZTtvelbb7P5xxMk0Z5qXlAa6oYsQEq0r9sYpcVHhOAKtBS0/xVGSH7nZ4zjKKSuD51lDg4aDUUaclxxMUlZbFVHusdRwKCq4udTg3iBmkBScTDO08ahKjQggLTXTrKJR56buHEVsdAN+4HrHKlPXOZm1js+NpQb+Y4zFIrH84mFBeLg8rhIie6gdcq0t9nPPekIfR1xmV3MVOf7Z88M451vbIyptK9y/cKNLr+Fxa6kxz7ns1ZIkjpLkRWWT+6VG1+KHt5ebVpLfEURJzo2lBoHrIISkWXd6vL3cxBGC0Ff0xy4SuDdI6Dd88lKz2XeoDDYH4Xp8biPg3klE1/dQDqx3Q4wxjE6s0XOVz4++1OTdAyt74juSXujTCAS/+v6QbsOl3fBI84rDaUZe2WT8SVJwa7nBWifgZJLS8hTXe12+eLPHuwcRGI3vu7yy0iT0FDujlHGa0w09JklBkhf80nf2ubXcQGEVBHbHMTe7IYNUs94LcYQiKyuUgjgvGUYpb5eaV9cb7I9zWqFtzHY4ydgZRpbAgCZ0FUlW0F4J2RtmjJK8Dg1qpBJoQEiBwhIzAlfhSMFq02O79j7GacnNpQYvrVipmMuIUy4Sywt8nPFB+sFEwMvPaiIfd1xmV3NZOX6w1fvf2h4ROJLAc0jzkm9tj/ixl5cpjZmHTIpSk1eWkbQ3TNEG9scZK20PKQS+Y1lfW4OEg3HGSVLx+Y0Ob1xrPrS4CSloeS6tVZdO6GCERAm4dxIjjCBU0G9aIkCUVfSbPqFnQ2zXeyHf3h7jKYmWhtBTpJXmR273GaUlUVoipGR7kFGVFcYIug2P11YgLzXtwGWaV2itSQpNWRmW2zYM9PJyE0dJPrfRpRu6uFJyHOdsDxNuLTV4Z2/MMCmIs5LPb3SJsoJppgkcSUnFjU7IzZWQdlwSZxV5Zb2uaZaTlRVprmn5BUlRsD/KbDuBpkcndGj6Dg1PsTs0DKKMUVZyVHtuv/htTSd0cR3FP/OZVeKs4rs7hl7LZbXl0/Bd0qJif5IRuopu6KGNmYuKXtb7WFTSL/BxxlVyMP8fbC8XsLIsnwN+/nlMagHItabShqBmJAWeQ5RnpGXF0TR/EDJxNElRQWUIPEnoOmhjOJ5mLDU84rTk1++ckOYlm70GQsDBOOX1tfacxbY3svUYTd/K0FShz2urLY6iDN9VSASrba8WlSz5sVeXGcaWUjtKCtK8ss3FPInvSgJHUpQa33N4bbXFL3/vkHSU2p7znYBpXvDdnRGelCy1XFY6PspA5ikajlUcnqZWv+t6L6TUtiPmOLXV/0tNj3cPp/NWzxhoBw6VsPfLkTBJC5YbLsqxGmeTrKThKPKqYpJm7I0yXlpuEjjCCmGmmjfWWhxMM4q6A+cb19q8dxDTDR3unSRURrMUury60aHXcKk09FsuWW6ZXmmhcZVgpRUwiHNCV2EMbPTC+ebhqt7HIrG8wMcZV/Fg/pNTf5fAXWPM1jOez6cS5zGEPGnrXdK8nHswStqd69mQic7KOowmKbTmcGLl58vKcGs5ZBDndBsepdH4SvD9gynXugGtwKPfcMnLCt95oOLrKcmXbvXZHcRkRUVaVJTGMIwLxmlp62MaLt/bmzBKcqSyRYyjpGAUl6z3A1ypWG/bSvZ/5rUV3jmckhUaIQxCCLaOY+IyZ6UbkKY2X5IUlummjSH0FUle8rX7Q3aGCUpK1jo+UtjOkidRzklU0G2E7I0jtIbhJGOpbfXDBrE1RqGRNLVgEpUQQttXdDyFafl89nqbYVyiqXCEwWBYbrgM05yu57HaD9kfZfSbLVwpKSuD7ymudUManqUuFxXsjyLivOLV1SatwEUJwfV+yGrLtgJw6s/0ab2PRWJ5gY8rrpKD+WUhxDoPkv3ffz5T+nRhxhCqKo0RVpal4Ts4juQLN7p8a3tElGfzHIzvqkdDJlKgjCDKbIMuKSz1uR+6vH8Y4SobKhMG3juMCVxB6CmKquIbW7YO4yTK2eiFlJVme5RQaI1yJK3A5WCcYpBIYWh6ir1hCkJQVZqmr/ja+wMkgv1pwXLLYfs45kY/5NfvDBACvrjZxfUk+8OUUWz1yKK84qRme317b0zo2CZmSkreP5wihETcEHRDh3GSM4xz7h4rOoFiaxDx6lqHpaaHrxS9lmKalowSS8O+3g0QRJxEKV1tSIvSap95gtf6LYwxhH6JEpJXVpucTDPi1PaMyWtl6bDr0vYk3YZL6FljPkkKmoGDI2XdnMyqKd9earDW9hFCcL0bPtT8y3fVh+J9LGjMC7yIuEqI7F8F/mPg/4uVyf/zQoh/zxjzN57T3D7xmDGEKq0ZJIUVmhylfPlWn4bv0Gt4/NjLyw+xyOBh1d2itOKNpTFsDxImSUm36bEUuvO+Kq+utNgapVRVxSjOWVlrsV+LSXZ8l82lkKNpxt2jiKIyeEowTkuysuKd/QmDuAAERVHSbji4jmCclPSbHnvjBCElaVHSDCRGQ1pWTLIK15E0lORX3jnmWi/g/aOYsqootSFKc0LP5inySlNWUA4SrnUCVjshoSfYPkmI0oy3dqaM0oLlhk/Dl9w9TjiZ5nWxqcJzJd3Ao+U5hL5CY+t3BpMSgWSpZfM5S02ftKrYXG3RTwvitGRvWPDqapNKW2WBrBS8vNKkGzgcx9Zby4qKN661mcQ5g7REAJ6j6IYOnmtlfADuHcdU2sxrWgKpnon38TQqEAsa8wIvAq4SIvv3gd9kjDmAea+XXwIWBuYpURnLQhokBY4UBDUbameY8Mpqy7YqdiTOGcGF2aJVVJqdYYJXG56Xlpsc+hnXOwFKSe4eR5Qa1js+N5dC9kYJSgp8R6GkwGjDJC8IvBa3lpscjhP2xhnNwFaql2VFlJV4jsBXLl7LIysq0DbMFWUF949jJlnFIM7Y6Ia246XWSAmbS002l5uMkgHTtOI3vdznJCqIspLSCLqqFt10Hbtg+5KjOKMTKg6OKnZHMUoKqgpKXTFIcjItUY6g1HB/kJDkJa5S/K7PrdBrNimqilFSWLKBL4mLijUFUWbq3FTOasMaSAQErssXb3TwXEXDUeyM7f3cHiT0mi6fvdZhkhXEuebGcot//lqbVuDiINgaJfiuFaW8d2w9xXbdQvo0lfiD0FqfRFNe0JgXeJFxFQMjZ8alxjFXk5pZ4AyUsG2J87IiCL1acVhaOfnHJIJn4RCwrAunbsXre4p24FBqw87YVvz/wI02gyjnzklkvYN2QKUNu6MUJQRN17ZQTvKS/XHK0dTSb9c6AapeHJcaHkrZsFulBQaoKispsz+2zCtPSKappSn3Gi4t12GtHTCY5iy1fPpNn1dX22x0S765PWSl6aEUbHQ8OqGHMZqDSc4kLtlzCgptyQy+ErbKvulijMGTClwwlaHhKtK8IK9KvrM94os3Hd45nJCXBl8pPn+9zTDVlJVmcylkueHz/vEUR0jWOwFKQIWg1/LYGWQ4LYEQgu/uTvj2zphb/QBHKT57rY3nKja6AWlpWKvp3ddFyE6t9ZaXhlvLjadO5l+ED6IC8aLQmBfhu08vrmJg/q4Q4u8B/+/68R/gnD4sC1weUtqY/d4otXIhrqQfukgpL0wEnw6HABSVngtbpnnFICqoAk3oCj6z0aXhOSgpuHMc4zqSaVyw0rJFj74j+O7elDsnETsDS/t1HckkKchKS/VteYr7x1ara7nlsdlv2F4ruSYtKwJXcv84ZbnlM05ybvQbLDU8snonrbXhM9dalAZybZUHVtoe3dDlre0Rh5OMaVpxfanB9W5A03e4fxKRlVZ9ebXjU2pYarjsTzLysgIpcV1IUitimZSG/ajgvcMpRVmRlZrNfshxrGm4MEoq2r5hb5LW6tEV24OE0LW5qbtHEWluuD+IkAiivOTWUkhRauK84DfuDfmR2/168dZUxpBmFTujBKNtWGq56VJpTW6jic+MSvxBVSA+aizCd59uXCXJ/+8JIf5nwG+rD/2MMeZvPp9pfXrQ8B2+fKvPzjCxC5OUFyaCzwuHFKUmLSp2hikGw0Y3oKq9garSlFqzP0wRAqZpidGGb9wf0QochDEM4hyEIHQUWVExTQu0NjQCB1c6fPn2Eu8dRewNbb+Xymi+uTXCl8LqlElFO1CEjuTWUoDWgmFS8YObLRqeyzQvGCclndDlH3//mJOpJSxM0wLXkXx+owdSM0wqllsun+t7dk5ZQZ5btWNtDArDjX6TpZZHXhS8tTulqAzUi2uclHxvf0jgOXjSYWeU0nYV48qggGlaEBcVUV6x2rKU6+/txDQDl+/ujNlcbbLaCjAaxlFOp+ExSgsw4v/f3p9HaZbmd33g51nu+q6x515rd3VXN61Wq5DEaMZGFiMLDUbMYsbGA2IZNMaYZQ7MIGDOYMMA8ngZY3uObB2skXSQwWw2Gg4g6zAIYSMJtVq9qru6q6sqq3KL/d3v9izzx3MjKyorsyqzK6OzKut+zokTb9y473ufiDfi+d3f9v2xqGpe7S9Cnw8wTiO+sjtHipCLydvxy9PyjUmU33pl7aHcrZ9MI70xLRC1RSl53yoQj5oufNfxQI2W3vu/A/ydM1rLB5Y80Ty91X/HMMLdwiGRlmwPEhrrmJWGWIWcgPeCVw6WyFbaXwDGeOJIIYRgoxc28tp4lnWDB752sCCWgjTWbPQi1nqeYT7g3DgoKR8vahZlw+6sYLpsiCNFaSwamJeGQaaQQmK95+W9JZc38yCQCcRKtlMfLRKYFA3SCbzyjNIY6xpiIXn9uKGpDXuzmkgLBIJRIshSzb/83CalCUKT1sHnX5+yqBusBSU9qxXsaM1oELTVrh2u2BjEbOURx6uaZePY6MUUleWVwwUeAUqB97x0a865ZzJ0LJlVhmvHJRuDmDSCo1bN+cmNPpfGGb9+Y4ZSgmEW0xjL1/YWWOt4ciNHSUFhLHuzkn6sbxdmfKOUjb0tLeMhjGy4wwN4r5Yxvx/Cdx1ny4NUkf1vgP8A2CZUkQnAe++HZ7S2x5o749L3kwi+Vzgk1er213kcmiWzWGFKx/lhQqQER4uaJFYME0UzSunHmtePVyRasmygqS27k4InN3pkWuGc46s3ZwxjTRyHaY5F1XBtWhDrCK1Cb4yzll6eIfHcmFakSpLECuc88VSx3otJtWLeGoKmVQ/emxWkWtG4mKgN6SSxpJg2RElEokMuqGwaFBGzleFXX51wcb2H855ntge8tLdAKMIoZAeOkAuZFDWbvZhVI2kay0Hh2RlkSGXRSuBlqBjbGqQMEhX6ewpDL9fcmJRs5Ak3j8OogyRRPLc9IIkVsQyqyBZP0v6+hRCUjSVRijTWNNZxtGiomvDeXFrPv+GQ0GkPIIsjjHVBCSBSbzEi70V9rPd6+K7j7HkQD+b/Cfxr3vsvn9ViPih8o3Hpe4VDtJYhlzMpOV5WCCFojGV3VrGqHXmsOFrVZLUlizNGmUYAuVbslpZlaZiuKmIVZGmEhNJAohV7ywo3D4n80jhq4xlnirqJWJQNeRyx1osoG0fjHAWO2CtK41iWDcvS8ORWj6N5xY1pRW0M88qglaK0lvnhMvTNrGes9eMgaJnD9UOB944sjulnilVjmawqtBIhNKUUG/2ESIWKL+8s3gmGqUbg0VIyziJiLSgax2tHK7YHCVVtuTVdcbRscE7QSyIiLWhc6OsZZZpe3CNJJWXpENKzajznRjFChs0yUmGs9LQ0VLVFCsFarzUAsxIBDNOIJJLvKiT0fvcA3svhu45vDg9iYHY74/Luebdx6XuFQ6QMm9y1ScHxsmZnEN8WXHQerqxnfHV3yZYJ4bS6cewvaprGcH4UKqqOlxXOWhbWUjeWnUHGdzyxwXFl2D1e8aXrU3ZnJVXjGPdihr2ItVQz7if0EsXepEYA40FMWRqOi4bLo5SqCRvvwbQg78VECFCepgmb9cW1jJ1xxqoylHWDkpI0Ehin0FqSxxGr2jIvGxa14/kLA/CwOcjYn69YNQ3LyiLwTEuDQIAouDDMmNeOcR6jRTCYVw/mDPOE8w6KyvDS3pwPb/f5jR9Z5/wwZX9ZMy8tn7y4xou3ZlTW0jhPVRuuTQrGeczz54ccLWsGqWaURnzkwpD9WcXNacG8NFxcy9gepsRasay+cYPwOHgA79XwXcc3h3c0MG1oDODTQoj/Fvjvgerk+977v3s2S3s8ebu7Uhxv+Uc8HUqDtmrMhK7/WEqEEnjr+drejOmqoRcrFkUYbbzRiykay6yokVLw7HaPjTzi89cnzAuLkp6yzRcsigbvJQeLCoGgMo7Nfsqrx6H58pWDUOY8ziNe3lsyK2q2einDPMZZiKRmYwhN45mtGnaGCT3raDy8erAkUgqlJcJ5DBA5UEoSR4ppaSj2VxhrWFaGC+OM9V5G7WqEV4xTCRJ6iaK2gq/fWhBHimd3eryy74i1ZrIyjFKNEnB5I+bl/YKicTy53mMtT6hqg7GOUS8hjRW1CSOWtRI8sd3n3CCoTG/0oDYl+/OKREtuTErGuSbPYp7eyIGgvyYIlWInygvjLKhcXztekcYq9BG1qgDO+TDL5wE318fFA3gvhu86vjncjwfzr516vAK+99TXHugMzANwr7vSxjiuz6s3hc2AN1STraNqLDcmBa8eLkkjSRppntrMmS4NL+7OGGQR670YrSQ3JiviSOEsHK8qIqW4frziF5cNB4uSYRqxM0y4MV2xNw0KwbVxSAVPb/VZlg2FcXz5+oxlbTheVaFbPtVs9GPWnObZnQGekIPw3jFMI3RfMls2jLII4wA83ntuTQukEBwua6rasKgM416MKQyXxymlCaXRznsGacTz52NeOViwLC3XJhXeC8ZxhJSeONYhbFZb5kWYlrnZi6hNGPh147hGAt7C0bLiYBlyMo217M9qolal+WBZoqVklGi2Bgnz2lIay/GqYWeQ4HyoytsaZlxcSymtZ7qquLyZ08/emhPJEs3ljR63pmU77tiBh+uT4hsu0e08gI73M+9oYLz3v+9+XkgI8ae993/53S/p8eZud6Xbg4S9efWmsNmNSdFKkkikkNyaFtyalEzLhmEScbiscc7zxesTxllMbT2ZVixKSyRgb1bxoa0eN5cVwyzitcMCYyzOGbQQHC9Kmqbh6t4KrSWjPEULuDEt2J+VbA0S0kjwld051oQG0OWsojm0FE2N9xLn53zs8jhMo2xqrJBs9mOEEBSNYZwn3DpecVzU7C5qpPPszysa46mtIUvC8K4v3JgSK8Ew0QzylGvTkvU8xnpHkiiQDqUi1nLNvLYcrSqkEGz2YorasihLaitRCpwPXf+bg5y1Xsy1wwWTosFu9Hl6u49A8tL+AlNbxoOYb7uyxsYgYVkZ0kjRjyMyrYhjyXacBENiHFpKJmWFcZ5IvjGy+s6cyGmVheuTgkTL2zcS32g+pvMAOt6vvJt5MHfyrwOdgbkPTt+VCt9K81tHFr+haLysQk9FnoTKJAEY7/BAEiv8yiOEZFk2rPck40yxqBoO5jXLxoD3bAwSBknE+bWUojK8fFBxc1qyqhxKglaCNJZoGXS1qtqRRmHTzxPN60crbhyuiLWgn0csV0HmZWOQtJ3wkv1pBU5wY1aynsZcHKXYxrEoLJlsMB68C+G8aVGgEMSRA6FoaoMVAmctXkYMsmAwKus4nlc4PBv9iFgKjgvDS/srhllELBWjNOJzV4+JtWBSCBprwEqGWUTVWAaJojoxGj7I6Xs8ZWPZHqQMUsWljR6V9RjreO14xTgLc2C0lljriJUiiwQTE+bBHCxr1rKI149XnB9naBm8UeFD6PJNFYFe3H4vTz6/nxL0HR0Pg4dpYLr/mgdASkHdhLta4xy3ZiXnBfTT6Hb4TBAk3pUI8ixaSASWRVkzXTZUtQPhKJoGh+BoWTEpa4ZpxPYwwzmY1obD1yfszmu+enNBFknyVpRyWTRcGKccL2sOFw2Jgp1+jI4EL96c8drBit15g5SgjiukhixWbA9SBILDoqFogix+LIMBvDFZsb+oubSWsqocB/MSj2CYKCYriVQO4yRKegrnwVmUUGEMc9FQG0esFUrCWh4zK4NCspQCJTxJLBklEYNcc1xaRlkoWjhcOApbszOMGWYpk6Khahq00uz0EiKlWBYhbLXWi1jPU84NUpa1QUrJoqyYF4ZBqlnLY25MKqxzKCHZGsY0zvPJy2Nirbg1LXjtcMWFUcowDwbHw5vCYI9Dgr6j493yMA2Mf+dTOk64s8dBAjemJed9SH5fGGfASQ7GsdFP6Ceaa8crPvv6hH4WkceS88OsvfuO6MeaPNbkkeLSes6tacmqrjle1eSxZn0QUzfBsAwShZUyjCdeWpTwlA7GPc1rB0sWZcXevMF7KC1EgLHQi+GoqFAovDcUhA02ixXPDGKWlcVYz9Gy4XjZcHV/SZoKtFAo4WmMpW5CaNB7j44UWkrSSJFIxcpZhpFCi6BSsL8oGeYpOMfGIEYJwW96ZoNpacgihXUWAySRwgmwDmxl6aUKrSIGieLiOGNZNZTGst5PWO8nDBLNq4dLitqwOUj4yLkBh4ua14+XrPcj0kghWqm9nUHKbGXop0Gh+spGj4N5SeMcX7k5J1LitkdzOgz2OCToOzreDZ0H84i4s5osSzSb/ZidUUreiikCb0rwQkjAX9nIybRCyDDNMZJhg410CK01xlEbF0p9bZgVYx1s9RKsh36ac/1wiRUC7yWfvDJgXji884x7MdeOCxpnsT7cNXjAi/AgUopl6dDSM0wjPvHEGvvTipuzFS/vLcljRWM9s7LGe4/SgsOVIxYO5wVSghNhsmRRgW4sw0zSS6B0jn4sibVkWhga27CqDUpUDNOYpzZ7HM4bvn6w4tww5flzA375lX2sCbL6m/2YonGM84hEK7aHEQfzitI6Iim4tNMDJMbBqnYIBJFUxFKxrB2bg5jjom69R0NpwiA1IZYMEk3dWNJYY4xjWhgujlOSKAxo259XXBxnOO9uh8HuN0HfiUF2PK48TAPztx7iaz32nA6hGBeqrGrjSbTi/FiSymB4ThK8J5tQqhWRUuwvQunxoqz5+uGKS2sZ/VhTG8u1ozBauTaW+crQSyJq59BacjwrECKmcTDqRRyuKtJas6obtJS4VY2xjtoKHGF0KQAeYsB7xyCNWJaWWAte2V3QS3QYEAbMVg29VDEvDAeLEhDEIkyonC0NaSRYlpZICVzskYDE01jPuCdJVIS1nkGimSxPvi8YZqHL/smNHrEWrIzh5mxFbQSrBprGsiwMSPBEFI1hf7/m8nrGei/BWouQiq1+TFF7dqcFO+M0dOQ7z7yqma3CtW4eF9yclERaomUIbwE0zmOrttw5020ory0n9z7I4NwRBnunBH0nBtnxOPMgUjFbwB8Enjz9PO/9728//6WHvbjHmZMQyo1JwfXjMFv+ykb+ljALvHkTEkDVWIQIm9pkZRhnEZnW1NZSG89vfGqNzV7ML339AJOETbAsDfvzGussaRSaEr3zLIqGUlpK6yhrAx5WZc2ssOQRlE2rCQT0U0FjPdOlp5dFCCmoGsOituRJuPt23nN9VoOzlA68tURKghPkaURZeXpJRNUYhAAlBVmsOT/M8AIujlK+ur9ikEiUkuyMUpyX9JOTkc+61VFrOF409BJFFAkO547DVUU/FswLhRBQNg5rUtJIsnAwTmPmhQEZ1AAujTLyNMI5x3JiuNgao3/64h5lY0ljRRJJ5pXho+eHXF7Lqa1jd1YyWRmWlWX9lKab93B+fP9hsE4MsuNx50E8mL8H/DPCkDF7Nsv5YJFGIT9gbPAKTjaV09VGd25CRW2YFoant3uYtm/kYF6z1ouQImZWhmbFo0VNYTxxpNEINts5MNujAcvSMC8NNyYFwzwoCyfW0080ZWOZrBq0DvPrpVB4YdnMIvpZgtYKb6GfaPaXwWBNCsOWSNgrT7rbNY0RQSNMQRxpEiVJpaCuPbHyOCRChWbHxnqyVPPEWsa8alpNtZhhX+Aah1KC88OYw2WN9xYvBVXj0FoRC4l0llGeUBhIIkE/iVlVNUqFoWjLxmKtQwh47vyA/UVFLBUHq5pPrOdEUjLOEzb7CdZ7PnpuyItizlY/JokjUi1II40SgsNFTRYprmzk3JoW7M4qLoxTtocpvVOhzfvh/S4F09HxTjyIgcm993/qQV5cCHEZ+Clgh3AT/GPe+78ihFgH/luCN/Qq8Du998dCCAH8FeD7CU2dv9d7/5n2tX4Q+L+1L/3/8N7/ZHv824CfADLCfJo/5r3397rGg6z/m0GkJLFWIUSCeEu10elNyLVxeuc9xjjitlppnEVt74llf14RScGqccwLg5I+CGB6TxJJNnoJh/OaLAqewChPcd5SNJZES25NVlRDTRIFteBBorh6sEBGEUXj+ehmj6NlTdmEiqxIBEOpgFwHOXtrLImSXFrv45wDIUgiwXYvodjs8WuvTVg2Jd6H6ZqxUiyKhq/WlsI4pIB5aUmlJMoj8lgxyBOe2BqyrGq+dnNB2RikAONDUUGkJU9sZNSNw3tDL4u5mOpQwWUcm4MEPLx+WHBjUrDRT7Am6JXtDDKuTYrbv98kUnxkZ4COJN55PIIL4+BhnbwXWsGVjR7zouHSWk7yDYS1ukqzjsedBzEwf18I8f3e+wcZMmaAP+G9/4wQYgD8qhDi54DfC/xj7/2PCCF+GPhh4E8BvxX4UPvxHcCPAt/RGos/B7xAMFS/KoT4mdZg/CghdPfLBAPzfcA/bF/zbtd4T/F21UbOeZwLxXnLsuG4aKib4LWs6pCEH2cxLguhs1QHYyMFIAx4xd6iYpTHpEoySBTeC9byiEVp2J1XDDJNojWxUszKGofAegWE3pz9hWF9kPHhrQGTquH6bMWyMFw7WgCK9X7E01sDbh4tSWJFFkmsEzTGcy6PGKShSuzp7R5l4/kXLx+ghSORkvVewqgf450LP4/zjDLNzHvyWGGd50PbPdZ6Cc9fHKKl5NZM4pzA+IiiCp6YMZY8jehnEdJ5amuRQmE9DBLNMIs4N85YSyK+vDcH4LWjFXkk+adf3ee3f+Li7ffAecdaLwxk0zJMHD2Rg3HtcLETQ1CZEP6L1Dcmyd9VmnU87jyIgfljwJ8RQlRAO7fv7eX6vfc3gZvt47kQ4svAReAHgN/cnvaTwM8TNv8fAH7Ke++BXxJCjIUQ59tzf857fwTQGqnvE0L8PDD03v9Se/yngN9BMDD3usZ7jrtVG53Ou1TGcmtShoolrdgeJmEzGqbU1nEwr0LTphBESrI9Sti0nq/vzhlnjucvDImk4tXDBVXTsGocF8YpadJjvZegBHzy0oh/8MWbHCwbdgYpapQxWVVMioZPXB5jvMAsKj776iFKKvCWPJFcO1qxv6iwxrHZz4gjyflhQpYqzo0TQJLFiktrOf/kK7toIXh6e8RrR0uK2nE51gglaWxB2XbMD3ox1nmGmWZrlLHZT/jM1Skv3pqhpQgNpKnmmZ0B26OEqnYU1rA1yME7Xrw5wzvHs+dGbPcTauupGkdvTfPa4eq2gXhio8e8bLh6vOSj50Zvan49GUkdtT048IZBuHq4ZG8W5Pi2Bwm1dbeLMh7Ge9/R8bjwIBMtB+/mQkKIJ4FvJXgaO63xAbhFCKFBMD6vn3ratfbY2x2/dpfjvM013pOcrhY70RwLMiMK1SbDL63ltze8o2XF68crdmfV7T6MREmUEhSVDcnzSLEzGvHhc0NWleHmrGRzqFg1Dodnd1ZhrEcI2F2kxFrz9FaOc5LaNBS14fxIYi2UxnBtskIL0AoWFZRFQ1WBc4ZYwrI2ocJtWbHRi3jx1oIn1nJSrbg5Kfj0K8fMy4YkkuSxpmzzSVoKpqVhVhhuHK/Y7KfkkWRnOORoWXHruOSL1yekWmG8JxKC2bLm/FqGRNDPIm7cKuhHDaM85mMXxrx6uKSqDfsLyc4wppcojpc14yyispZUa1a1IdYK2YqMRkrebn59U1XXKeMRtx7LlfUsaL21ObJ3k5jvpGA6HlceqExZCLFGCF+lJ8e8979wH8/rEyZh/nHv/UycijG3+ZIzbdJ8u2sIIX4I+CGAK1eunOUy3pETr6VuZ7lc2cjRittTKJ33rQKA5XBR37UP46PnhxwuKxrn6SWac4OYX3vtmL1ZSdk49qa+NTYFT6znHM5KBrnmV1454uI45+asAhxSSJ7a6OEl3DoumJQNB4saoRWVhzRWzCqLVqA1KCk5XlY0VrfTLyuSKKIyjmec5398cZfJsqIylsZoDhYVsZQs6oZBFuE8OO9YNhY3XaKUQkear96aUzaGReH4xKURh6uGr+zOiLVkVhie3hkwKxqs9bx+VLA5SNgtTJgsaT3SGK4eGQZpxKJq2B7FvLy3IlEhzPjsVp8kCQl853zQgPMerSXC8xbjceLZpHH415FKUJmQj5JedF5IR8cpHqRM+f9ICJNdAj4LfCfwi8C/8g7PiwjG5adPSfvvCiHOe+9vtiGwvfb4deDyqadfao9d541w18nxn2+PX7rL+W93jTfhvf8x4McAXnjhhUemRnC6WizREUfLmlvTgisbPZzzbA8SvIdlZXDes9GLSWONkk14fhtKG2UxT230+Pr+nMWq5u9/4Waobmprjee1YRgr9uY1X99boaTnic0eo0zz5GaPjVzz+nFQ/x2kIcn/2t6cwoTu/0EW8frhito5hIVEQ1lCKR1VQyg/xqAVXFhXSDz/4tVDrh+F6ZkG8KbBI3hmKyeNE3ZnK1IFKyGIlWRaOLLI8sXrx+wMY2ZlyDH9ytVDtgYxwsN6FjMpaw7nBcbCzjDl2iQY0WuHC0Z5TFEahIM4kmgBO8OYqtGkWrO/KJEilEFfGGdIKZiXDa8cLFhUYabMRj9mvRe/qarrbon5xgRx0jvlYh7W30UXPut4v/KgOZjfCPyS9/67hRAfAd6296WtCvuvgS977/+TU9/6GeAHgR9pP/+9U8f/XSHE3yAk+aetgfhZ4C+1HhSEkQF/2nt/JISYCSG+kxB6+z3Af/4O13jkOBfk9+GNGP+bqsWcZ6Mf89rRitmyJok1T2z2iFWYd28bx6vHS+rGstlPuHG8YtVYhonm3CDl6/tzvra/4GheoYSgtJa94xInQ++Ly2KWtSXRnrLxvHqwxDgPQrDRS1BCMMw1ozzii9cmFNajPAyzCOtCYUHZOIa5YbIMM19ssHPY8DI4A4fzgrIxeBsaNLVWpFKxrC2jRDPup6z3Ym5OC6alYVo0GOeRAlY1GA/S1fTyINEyKw23piUb/YRRqphXDV/dm6GEJtYSgefq4RKAVCuGw5hFZTlcVHzmtWM2BglJpPjQ9oAnNnusZRFxpImVxDnP3rRkXhjyWCEk7M9KrPV8aOuN6PCdiXkARFC9freqyXfSNWF2vN95EANTeu9LIQRCiMR7/xUhxHPv8JzvAn438AUhxGfbY3+GsOn/TSHEHwCuAr+z/d4/IJQov0QoU/59AK0h+QvAr7Tn/fmThD/w7/BGmfI/bD94m2s8UsrGviVJfGI8pBAsyobdacnuvKKxju1BwuVBcntjma0avnh9GvIXpeHyesaqCaW6X99f8ssvH3BjWjIvGwapZlo0VHVozDxe1iwry6K04AxL44mUImrvyq8drlhVhs1+xs1pyev7Cz53Y0YeScpWFjmNPNs9ycpIemmK8Eu8EEwWJkiwGJAeJFDUUDQNo1TQz2KK2mCdCSOFRymDJGZWGCIJQjic89QNSAVKgPcwq0GqhlhCP9YYY8AJvnBrQaoESkqEcAgPUaSYFw1SCY6Litppbh4VjHsJkVYsyoabk5J/+UNb9LMYKcTtiZMQwl+b/ZhJ0XA0r6kaRxZrCmMZ6DcqxU4n5p3zXJ8UD101uWvC7HgceBADc00IMSZMtPw5IcQxYeO+J977/5F7a5R9z13O98Afvsdr/Tjw43c5/mng43c5fni3azxKnPPcbEcaD9Lwqz9aVggJT2/02R4k/OrVY/bnBZFSnBtlLCvL7qzkiY0edW35zKtH9FLFcJSRRCVfvTXjwlrGIFV8/vUJ06Lh5mSFVqEvZpgqvjJdksWaXqwYphGLoqYyIayGtaxqi3OC2hm8d0RSheqqgwWH8xKGKWVtmBeGysJGTxFJzapxGCsQMmiMCQcOiAUoGQxF04Tmx41+zLSA44VhY6AZ9yOOVxVfujGjFwuEVyRxQ+2CtpqTkBioPTQOIilIlA76azJIulhPMDxZTGUddWNYWjg3SrkwzLg1C5I5g0xTGceqbjhe1Hx1b8HHL45vy+2f9J1ESqKkQACbvQRPqGTbn1dvaaK8XZQh/Jn0snRNmB2PAw9SRfa/bh/+e0KIfwKMgH90Jqt6TLHtZEopRbthWPYWFavGIhHsjFKGmeJgEUb5zkvbikc6DpcVn3v9mC9enzJslZNXjeXre3N2ZzV5JHlxd04vCdL3yguOlzVruWYjT9gepqxqGyq9Is12LLl2WHFYViRKkCaa2sCNScXNSRjoVdkg2PDaYUmsgpqy87A/t2TakkQSBDS1pzagFERhFA1SQT+WlMpTG8etoxVSSSINs9Lw+den5JFk2VhwMcM8QmtFJFfMSk8sQeaKNS2orWerH1Maz1AH5eks1uh2SFlpHLmWDPspk6KmsZ4oUjxzLsd7zziLMc4H7TAhWJSG1/aXXNzIb+dfAM6PM4ra8PpxQRopNgcxF8Y5ts2D3G1jP6telq4Js+Nx4B0NjBBi2FZ+rZ86/IX2cx84usvTOu7gpGnypFqpaSvFgpBjRBJJdmcls5VpE/0K40KPy9Yg5guvT1mWBufh6sECBDy92cd7OFqU+F6C8JabxzVCQNpX9FLNE9s9iqLhcNnggfUsYZhoDpY1z24pXj32VBYqY0k1qEixKiyRCJIsjYHCho+I0OWqgaIBpEPLoLQsJcRS0EhPHdJLWMLI4KIRjHOJEoKitiwbGESSg6Yh05KlsZyPU5SEJ9fX2Z0WGEBLRd0EdeJLGz3KOuieOecYZEHVOIoESkc01jHsRVggiyT9NOIj5/skKow4mK4MkRY8udlnZ5SyPoi5OM7e1IGfRooP7wyDFyOgl4QBcN7zthv7WfSydE2YHY8D9+PB/DfAbwN+lbC/nP4L98DTZ7Cux4rTyVrjPL1EcbCoWZQNl9YztgcpsVYUtWXci1FScLCsAehnoRP9c8spG/2YZ7f7fPrVhr3pigujjGe2+7y0t+DmtODWrGZvUbGWxURKsjPMmCyacJeuNMvK8OrenL1VgzGO9V5CpiUKgRGe0njmZRUGnUkPUlC7N8QuT7prHUFZWRHCWTiIVJBtaFzIv0RAWREGhGUxUlluHddoBdbCCkdtQHuH8rB7vKLXyxhlMTujjCe2e7xya8nBsuJoWSNR9DPJvCyoraeoDVuDhOcvjbh+sGJRW3qRYrwZU1QN40wjvOBTT67RTzTHy6DyPE5j9hclF0fZXTvwjfc4DzcmBVBwYZzx1Gb/HTf2s+hl6ZowO97vvKOB8d7/tvbzU2e/nMePtyRrtaMykqc3+lyfFmSxItbqdigkUkEf69J6jrEOIQTDOEIIsNaTRIpxqliVEWtZxHERqsesc2z2YioThobFkWRrmLC/qJgVhkVpWFYNR2VDpgSlh+NlwbJyGGdY1ZBHglEWY1zDsvSY2mMcJAR107ZQDAUgoDRBbbmxMMqDGVLteab1eqRwLGRDZSxFHYxPA+CDZ7BqIBOOlfOMZDDAi8azqhzn1jI2hylfvj4B4ahqi1KSj272eWq7x+Gi5p9+5YAr6xmR0uzOayIluLyeURnPrVnFs2mPj14YcbCoeGl3zu5sTqolz2z039KB75zn6sGSg0UVJGhs8MCeWO+dyd/F/RiOrgmz4/3M/YTIPvV23z8Ro+y4O3dP1jriWHFlo8etacmyMrelX6z3HMyr0FMhJedGKVoIntnq8+rBksNlTZ7EfPKJlNrBzemKXqQ4nlfkScQT6ym9NGJa1DTOsygN24MMD3zp5ozdSckwDTpf08oQySBqGWmH8ME/adpkPQTPRIqQwBcu/MGkMcSxAAdF7VESitJTtc9LNSQJlEuClyKCcdEilB4LoGjny4xS2BwknBvlrOcJz50f8PpxiTWOg2WDIkjg9CKFj2TwBuclz57vkUca8Gz1U7b6KSvTsCgNz2wNGGQa73xbwACpllxcy3hCSjxQ2dC78uRG7/YG39gwunpVh9HJAsG0aLh2vOLZ7cF9eRD3Yzi68uOODwr3EyL7j9vPKUFs8nOEPeITwKeB33Q2S3s8OJ2sPenCPzkeRfJ2CKQxjr15FSq7gK1BQi/W1NZxrZWN6cUSSczOMGVnlHJ9skJK2MjDTJJ5aUi0QuCpjKeqa1ItuTVZUNUObIPDsaoFjXdUNRB5Ii1IdUzdNKyMo6gc1rYGoR3MoCSs5aHHZRBrlo0gSQRR7LGm4XARvBwtg5EpQhU2URSMChJSRTBCPnhF/TRI6yMkVeO5Nq3QUrBsLKNcUzeG0noOVw2NI/z8QnK4rPns1RlJJFFCcvVgxbyyVNYivGBRN9xoN3DnPc9u96gbj/OhrHmcR3jAWPeW5L1rS4+1lFjnUe2Mm/up3rofw9GVH3d8kHhHGVjv/Xd777+bIFr5Ke/9C977byPoil1/+2d3nCRrF6Xhpd0Frx0VNNZRt42WUobKoL150BTrJZpESw4X9e3NyDnHcVEzKQxXj5fM64ZVYzlYNERS8vrRip1RDgK0lm1YJ8M5z+6s4MXdJVeP5ywbGCUaoQTWhvCXFFAbAcpTutAomcWKPBWsToyLAO9gVoFHMB4mDLJQNhtLQS+JkDLkXdIIEhE8l0SFTn8lQzmx88EASRE8o5Mxz1mkuTUrsc5ybVJw7WjFV2/M2FtWaBGmWjZNw6uHK6z1rOcxxlqqxnBxmLCoG45XFVoIBqnkl79+zGRRURvbNlDWXFzPGKZt4cSiZndaBgNyKnkfqeAxNtazqAxlYxnnmqStPns7ThuOXqKJlGjfuzeLQ7zh0b7RN3NiwDo6HjcepA/mOe/9SfUY3vsvCiE+egZrel9yZ2jEGEftHLEMWmGxllxez4ikpHGOm5OCJ9rwzL16HmrnqK3l+vGKr+/N8QiKyvDlmzNevDVnsxdzaSMnixWLqgEGrOcRq9pwMC+5elygpGQQw/HKgoA8iWjKGu8gS8A6WJUV1mnO9SWzSqGEZ9VYJksTkvseMg1CwriXYhpHrjVTU1EJw6p2aB0MS5JIVpUjioJhma9CruXEg6ldyOGM84hISyIBcay4ECk2BgmvHy6pnGNaWZz3vH60IpIC7xylFYzTiIvrGZFSLOqGvXlFaR1RCZ+4NAIBq3qJE7CqLeMsZpRrtvopt6YVdWNQSrKWx6HE2joigpqClIKnNvt457k+LYhkKJQ4P86AcO69Ql/327fSlR93fJB4EAPzeSHEXwX+Wvv1vwV8/uEv6f3HnaGRNJK8tLe4HWJ57tzgtk7VzVkrwd+EIViDNHrLplM3YXM1jePVvSW/+PI+k6JBSUk/0fSSEMrxQrA7qygry/XJihuTFZ8pKo4WhqZVQF7PYpQWbA4itkTCorIcrWqsB1zwMKra4zDcsAItNfOqoWo8dfvzxYQqMmeDJ3HUCNJIUTiQpUPwRuK/dcyQHrwJHkvtwbjwvSyCJAZ8qATLcs1s2SCFozSO2aqm8YJ+1FA5wXRZoqVmkMjgzUgQHmZlTW0dwzyComFSGl7ZWzDuxySRYpRExLEiUYJYK3qx5vJ6zrNbfXxbMHHtuECJJbFWbwpnpbHm8lqOFEHB2jnPy8cLhAchxe3w5WlDc7+Goys/7vgg8SAG5vcBf4igSQbwC4RhXx9o7oypl5Xhf3rpgMtrGXkeU9bB4zg/SNlb1e0mJvDev6lD/GTTmZUVh4uatTzis9cnNM7RtDmBonGMMrg1q7g4zlkWhplwvLK74JWDBUp4dhcNTV2zqIOa8v68IFYKZyOurOccL2rOD1OkKCkrS2MhVmCNJ9GCxjSk0rMwIeTVADVtsh64OTXECpANUVtJJoGlhWECtnF4gkFa2PCcSIdrlE1b4+7A48BLsiTGWM9kadmbNsQ6GKLjJRwsa0ZZRBZHKOEoG+jFiiRWNN4zWdScW+uxrC1KeV4+WPCMGPDEVh+tJEVlWOL57o/skERh8NmJp3JzsiRSgkEa4Xx4Dy+NM25Ny5DvSjTGOq4eLTmY1yh5YmQ9148LLq0Fz+bEKD2I4ejKjzs+KDxIJ38phPgvgX/gvX/xDNf0vuLO0Ihvwy6xfuNueF4Z8lRxYxaaSgSwPUzx7WArSfAILo0zXj1c8sRGuHs+WtasGsvltZxlY7l5WLCqbLgjTxS7k4LKWl7am3O4aHDeoSQsmrAZIgSr2rCoDMerUK5cG0tjHWVjqdsmyliEcFllgvhl2laOKUKC/iQ7YAieSKygasLP6lw4xxJyNImEOAqeS6LeyLk0Jjy/aKC0oYqrl0oyrSiEx7jQ2KmUwEmB9RaBp59qRnnMbFljfMOqtsHAec9xYciyito4NvoxidY8uzOgahyX1lN0m9Af5fGbDEBdGarGcXEthL5OhyRPv5dShDxKJAX9NOb68QqPYCMPZeN3JucfxHB05ccdHwTue9arEOK3E2T6/1H79SeFED9zRut633A6NAIhfBMpSd2WX01XNUfLmkUR+iqKyuKBvVlJY9ybQiihIz6EdKQMluhwUWKcQzjPubWMJJI453j1YMG8MdyaVyRaUBvDqmqYFg2N9ZQVzBYNdeNDc6OHRdUghac0ltqGHEnaFjkZB43xNA2UrZJxc8q43Emiw/crz+1QmiTkWCoLaSQY9zTeB2O0aENndXvOooZIOA6KhmVR4YBRKsnTiEEiiaRmnMc01lPUFq8E3oF1jllpSeNgZJeFYbKq2ZtW9KKgv1aYoFxgvGNWWRoTLn5iAHaGKUIIdmcl1ycFi7JBCkEs5Zvey8pYpBAksaJuwmPvHF5AotVdk/NSijdNwezo+CDzIMPE/xzw7cAEwHv/WeAD33x5cmfcWM+yMngh+K5nN6mtZ39ecmtW8tHzA4Z5TKRDXwW0ie879qA3GStPKC1u+0aqJngez271+I5nN4ik4qXdWTtnJQIpqV2rF2aDt7C0wXsYJEGNubKWRAucDbphGz1NP5UoDXkU+kN8m4h3hNe4G1UDUgNtwh7eyNNIQr9M4+DiKOfyRsIgF7e7+2nP0YDWEbNVQ20cWRzTSxKEF6RRzCCL+OiFIVqECrRhonliM0cqhTGOovG88OQ6eazYHiSkWoYCBuPRUqGVYNU4zg2TUP59qprreNW0w9oUjXHcnJZsDxK0lm9+Lz2cG6Zs5DFeQFFbGus5N0hv59u65HxHx715kBxM472fijf/Q3W1ldw9NLLZS1g2hr1JybAX01hHGmnOjRTb/QStJI15cx/G6TBO2TRMioZvubJGohWTVcXnXp/iheDl/QV5ImgaT1EZGmtwzpFp2v4NR9MEY5FphVKADyEx6yFLwmjgLFYkWuNdCYQRy1JYohQmizYkdsfPGgNpAsrBKAthMePaHhgBkQhhsX4k6WeaJ7dT9mc1n311Qm2Ch3eiCGCdYZjGbA9i8jgijzWzyrCqLeeGKeM8ZquXUFpYlmFWzDDXDNJw3qI2PLs9pJ9F3DpeUhlLP1WMspjtYYIQgiwOSsonv+eTkGYvjcgSjXOeorFErRz/ne9l3faprOUxeaSQQuAgGJouOd/R8bY8iIH5khDidwFKCPEh4I8C//xslvX+486YutaSgYw4jhpMW94aRC4dB8saYx3OBwXf05pYJxvcomy4PilItEIrSdk40khS1hZj4LhoyDNFEmsOZiWxUDTKs5nHzA30h0Gp2Dv/pmR+1XgyLTANzCtLnigurGVUBuarGiEFjfWIVoBMEYwHhObIYSYZZpJZDTuDCDspsYUPUjI+9MykiaSfapZlhTMNUkWMehFHy4a6Ofk5oTYem8AgS7i81uO4aHiin6IlfOzimHllKGrLomy4MRE4Z9mb1UwKS904ch2hEpgWNeNhynzV0Es0RWP50rUpO+OsNeZv9LHcWe3lCAUUpz2R0+9lKt9scIAuOd/RcZ88iIH5I8CfBSqCAObPAn/hLBb1uHDaI3HeMcoibk5LdKspNkgUrx0ueXqzTxyr2700jXEcLms88NrhinEeUdSWp7f6XD9e8drRkv15Rd04jPOsDWLOjyWrqmGyqvHWIpOU84OMq0cLLLCRRySxomqCmrHUEqkkG1nKqjHUTYPUsK4jbk3q25IuJx5MCgyyYDyU1PRjT54m5IlFqAZjPE0bnkOAkpLduWGzF5HHjlhLIgmqjaVFGhIlSbUkksHbef7igIvDHBVLlIdJZbDGszev6CeKf/HKEc/t9MiTGCXBWMuTGz0aD/uzAoHglYMlkVJ4D/004vWjgt/45HrIlbhvrExYyiCLc2JY7iaS2dHR8VYexMA8337o9uMHgN9OkIzpuAd3Tj8MnethoNdX9xYsSsPevOLD5waUjcO4EJI5N0h4aqPHrWnBvJXplwKOloZntnp44GhRsDc3jFNFYz21cywri7WWRb1knMVsDlNGseTq8YrjaYkjdOXLtjDg2qxAeE/jLNY6vIWqtSrNqZ9DySDJv6wMtjFcWB+icdTWU1ceIYOHtGwA71nUwegcLT1Kg9aQJiExPswiZitHFKlQWOAcL91aEEnBM5sDrk1LDhc1tXGs5zEfOtfnaBbx0t6SOIoQUnB+lPPy4YLjoqYfRzgveG6nz8tHKzZ6GrzgqY2cZW25MQ0TJ0/LtzxImfC71Q67X2HLjo7HjQcxMD8N/Engi7yhhdjxACgh0FJinOOl/QUSwXovIVLwz17c54Un18iioE/16zdmDHsRsQgJ8t9wccjBqiZSYZNPpacfayayprCWm5NQbWaBXpYwLytWtUWKCmMjVrXF+tCLogDRbnhVE7r6tRIkKkJLg1ahQOCkDwagdCDLENqKtMQ6y42pQXmDI/whGRcM0aL2WGdIIoXxnoN5QyIFWihGPcWy9qTao4Ug04q9WU0vkby8L7h6uOKjFwacG+UcL2tmZU1ZRRS1oZdoEDDOIl4+XNCLFc9uDHDSh3JqAUXZMJHQiyP2lzWLyvDMdp+87Ws5XVp8P2XCp/ucpAhD4k6rMLwTnbBlxweZBzEw+977/++ZreQx5c4NZphqbhyvmBWGzX7CIFFMioZb84LrszDqd3dWcvVgxeYwCV6Pgo9dHqOVxHrP1/YXHExLkJKtQYrynquNwRH6NZx3OC+pjWPqLHbZMClCRYYlvOmxBGxoXjQWIu0xKjTQWB9CYqcT/I5gdEJ1mcO6Ctf2jcQaEi2ZV45BLilrFyRoakemfRCwrC1KKcrGo6UniiLW8hgpJIWxgMI6uHq4oGoscbTg8kZOZSy1dawqw2+4PObFmzNePVjhvOO7P7zFxiBlb1ZSmwKvoJ9H2LZ6zjmHQNzuSfpGxg6fFAUYB/vzt6owvB2dsGXHB50HMTB/rpWK+ceEPAwA3vu/+9BX9Zhw5wazKBt+/eaMjTxqZ8x7JkUoAuglmkgIbk4L9ucVSSRJI4U1luOiZraqOFoZlqVBeUiTiKNFSdMYJI7K+BAmsyVZFCGFR+KRXuBbwUgISfjagzNBVl/5UG0WB4EBbCvpYsKXt4eNnZQgWxcGhk2NIY/CRt5PY2IJRR2UCkKpcBDG7CWa0sB6L0YAtXOsak8eecrGobWjMR7jHQfzgqNVg/OezV5C3Ti0FKg1z41Jhcfz1GaP6bImiiRl29+y3U+YDGsiLRBCsqgMvVixM85YlY7mDgke8QC1j0oIBHBzUtxTheFe3K8+WUfH48qDSsV8hBA5OQmReaAzMPfg9AbjnOd41aCEYJjHPLvd45+/fIixnn6i+NiFIVJJZssC4zzPbPfIY03ZWA6XNS/emnO0avBC8PylMTeOVzhnOF42TFZVMAo2dMwvyoZBColSpGnEfFniCaGxXiopytAsKFwbAnOgtQjy/NJTNW9Uj53OwziCIrJth4XFWtC4oAa8qh2DLEICW6OEVdmwrC3WGfIkZVU7auPJE8n2ICHTGoGnsB6E5da0QgrHRi/He8vuogJf8tz5AdcmJR7B9UmJsZDHik89sc68NLx2uGJnmHBpLWeYRqRREMesjOPcIKXOfBgrvQwSPBu9mGuT4r5DVVIKNgcJ144LpHQoKTg3yrDunSX8O2HLjg86D2JgfqP3/rkzW8ljyOkNxgO1sWEGvACH4OMXhlQmdPfvLWqGiUYIyUYvYW9aMs5jbkwKFlWQ519WBuuCbc8ihURR1qGHBelvy9BkEWgFUnqqpqI2wVDEMjRvesJcFx3BQIekfmM8caSIlGVjKKlNsCT71Rs/j6Ydm2zaEcpWYK2l9A4hPF54pqWDZYME8ljjXPiscRyuahLpUUrxkfN9DhYNaSzZnVXsTlbcmJRUJngkz2722F9U7E8rKutY6yVIEYz25c2cLFKM8phlabi8lrM7r0DA+VHGzUmBNZ7GeS6v58RK3pbgOZke+iChql6subiWoQTEUbhZ8J53NBSdsGXHB50Hqbf850KI589sJY8hp7v8q9riPKxlEXjaRseIPIqIIo2xnoNlTS/WfOLyCOPh1cMVrxzMWctjvBekWqJlKEe+NlmxakJC3rclxXEUQl39RNFPElKlqWofpE1k0A1b2eCBDDLBII3RKsjSlDXMa0tZQywVozQiSxUJkAE9FYxLK8JMogE8Tgm0EggEZRWMX6RFELtsDNPKMCsKDlcNUgqEjNACXj0oEAK8F/QjgfGSNNEkStA4z+GiIosVUkmiVnttLY+ZrhpevrXgc9cnvLy7wPswV+bk92ydZ5RFrA9iZDtnpzD2tgQPPPgMFikFF8ZZGJdw0s1/n4bipGLt8nrOlfW8S/B3fKB4EA/mO4HPCiFeIeRgBOC9912Z8ttwuiT2/DgLG15jsc4zTMPd8PlhwrIOzYBChE3sU0+MuXG0ZH9WcLSoccBkVVPWhhee2uDJjR5fujnls68dUxuYrIK0iZKhe78yBt8aE+shj0IILZGADx7LXhWq0oaJZhiH3hQtBY0FgcB5yGMQKjzH2eAZ9RLY7MeUFsrakGhNZWuKOkjEeDypFqxqTy8TjLIEYx3HhWGQOA4Wln7ikMJzbVWw2U/IU4WSCd5DFgmUUjx/YcTrR0ErbFEaShmEPtcHKVE72XJzkNz+PV8aZ5TGcmtWkkXqdlhqf16Fnp53Eap6NwrInbBlxweVBzEw33dmq3jMOdlgIiW5EimWtbk9Inl/XrE9jLmy1uPWrMQ4j3OO3aOKr+7OuT4tiSXsmAzTTsL8+t6CRWWojWfcy6idx3tL4zxSSGa1QXqPI8jsWwdeC2Ll0aHSl7rtd2ksCGUZpTFKhebH2lmyVKNM2EyPFobahT6YJII0jTBOYoxhZRxHyxrX6pfFOhiyEk8cwUY/JY8ls5UjjxVRrBAiVJZt9RNWjaVxBmeDwrRWkvODlBvTFXVjsXgurvew7XUyLeglis1+EpQG2oFtdRPCXrUJVXuX1jKkFG1iPVR9HS7qdxWq6gxFR8eD8SBy/VfPciEfBJzzNNZxMK8YZhHjXsz5YcLuvMY6z1ovxlrHF65Pef1oxcVxj6Kx3Dpa8er+kq1hjBCCg1nFsm7YHuWYxlI1Gm9DxZVDUDUNSuq2e76haCymHSAmDHgJvQi2+ppYC2Zlg3SWg2XoXZF4jBKUxrKoLFoFQxSmVCqMsTQKGmNZFkEh+UTM0tmQ20m1YNxLWe8lfOzSGl++MeVoWbNcNSAlxlpen5Ss6mB4Rr1Q0DDSkigSPHduxIcvjIgPlsxWDR54ZicHIXEeDhYVa3lMpCTCc7taDy85WgYF64vrGRt5jJSSXqzpreuu4bGj45vIg3gwHd8gznnmZcPerMR6z/685spGTqoko16CVDIMr9KKxjqWleF4VaOUoBcrhBbsHxcUTUMvjRhlMYvSsTUKd/U3jpY01rPVTzk3TJmVkvmqxhgonUMC/VQg8SwaiJWgn0QkieJoVrAoYVGZ0DuCpTHQmIq6nUpZWsgTUEqQJbCqHMvaoXyYI+OrUHGWp9BPIiIl2Oin/KZn1jgughCnx/PcuQEv7i05XJQIB5sDT9TmRS4MEyKt2BqkCAFrvZSicaz3EgapZmuQEivBV27NuXG0xHi48EzK+XEW5tL44L0dLGvOj1NuzUqK2nCjcXzqytptg9J5IB0d3zw6A/MQeDspkLKxvLK/4Es3ZigBW8MU8NycFFxezzE2jBwW/o2Z771EI0QQn7wxKZkuSkpjEcCyNgjn6cWK43nN7mJFFmtiL5lWhsnunGEvxnhYVg3iRCOMoER8IVMsG09hLI1pWDUhb+NbFeTahFLkeRWKB7IklCw3PowZvhhHOC+pFg2rtppM8EYJs5QwzmOe2e7x/MU11vKI0jj6ieIzV6fUddMOWIOV8az3Yp7d6jNZGjZ6iv15zeWNnEvDlDiWLFYGoWMkgv1ZxfYgQwhHY8NMlrjVBZNCUJnQ55JoxYVRxs4opWncbaXkjo6Oby6dgXmXvJ0UiHOeG5Mi5A5iRRYpZqVhmGjmpeFru3OM91jjePVghVaC9V5E0Rh6ieLXbh5z9XDB8bLBOziuahCCwjjWsojquOB4adu8h6U2DuMAUVE1DtO0nftt4ZKWYIUgjzz7S8thEY5vDATz0uNsmHCpCBVjKbAs25HKDUQxzGpHJCGKJXPjbjdEaYJU/yhL2Ogn1MZz9WjF7lRSNpZrRxU7owTjPWKxwlgQzmGd42AekvVPbfXxbsGtSfA+itqx1Y/5tifXWc9jduclmZLEkWaUag6XDY11t6vIbk4KqsbhvefcKAsK1kp2fScdHY+IzsC8C95JCsR6H6T6lSDWJ3faYL1DK8Hlccb+quagrihNg1aCW7MVR4uG58/1We40HC4qllWDd5JFbUgjQT9SCB90wXqxCA2W1rGqg5DlRi8M5Zq1Ev1agzVwODdoYTBtrbES4fupVEydobTBI4lF6PCvw2nINv/SSwRKeWKtUBKmq+B9JRIyHRLug1QxyjRaCl7dX5FqQd0KWh4tKhZlg7WCXqRBKzSCVV0zyPph3DTBo+rHEf3Y4zz0Y828Nmz0YkZpRBKHOS6VeUPMJo0Ul9dyRnnE0TLktLyn6zvp6HiEdLGDd8Ebnfrh13hnf8VJyMy6ECKqjKWowy6+PUxIEo13HikFs6JBSUGsFMYaDpY1Umm2hylSSmobRi0jJEJAGmmGcYSWkrI2lJXHtWKTy1XQHmsIDZXeBiFKKcDJMBgsTRXjfphieXMeSpo10NOACs9z4SFKwVpfMUhTYqlDLMxLsghSCcNcsDFKiSON8IKqge1xTtUYisYyKUqs88RCoWUYbLYxiPnYzoDz45xLG32e2cg5N0iJhGBVO/bnJavGkcWS2jr2J0Gt4Ma0ZFY0VMay2Y+BYOjLxnJtUjBp1RK2BknXd9LR8YjpPJh3wTtJgdTWYZ2nqB2TVcMoi3huJ+fKeo+DZY13HtVOtiyNDTpks5JVaanNkn6sWFUNa70I01h6MURKkkSKWVmzqA1NHcJUSRQS8s6GKZO3JzI7MDKUDmeJIJaKVWOojCWSAimDCEAah0qxJIIyNMWjgX4MQkJROhpbs9nTVFaS6iBx01iLEILpqiRWijQOTZZ7k4JFaUgShRCKVAlmzhFLGA1TdvoJeRKz0dc8u9WncYJp2bCsGz6800OI8HuZl2EqaBQrntvIuTEtqIxjLU+QUnB9UoSya+Pop/q2J3m4qOmtd3/eHR2PkjP1YIQQPy6E2BNCfPHUsXUhxM8JIb7Wfl5rjwshxH8mhHhJCPF5IcSnTj3nB9vzvyaE+MFTx79NCPGF9jn/mWjnOd/rGg+b0536y8q8qcP7JHzWTzQfuzDiU1fGPLGR8+GdMOL33CjFeuglilgLlpXl9f2CaWFY1A1fvD7lK7emxIlinEakkUKI0DU/KyzzssaaMD+mbGBVgXShMVKJ8MbmIhgHa0J/yqVxAkoiPUSynSjpYKMnef7SiEEvwprgsXgfxDA1UNcwqzx1bZFSk2rF9nqPZ7b7xLHGGE+sFJuDlHnjSHRQBbgwTNFCcH6U4aXk0lrGhy6M+diFYaieEx4lFaM84cIw5amNHh+7OKKynoNFxc3JCjzcmJes92OyRPPUZp/zo5RISfqJvl0QsTevbofCHrRTv6Oj42w46xDZT/DWBs0fBv6x9/5DBGXmH26P/1bgQ+3HDwE/CsFYAH8O+A7g2wmqzicG40eBP3jqed/3Dtd46NxLCuR0+ExKQS+N0ErixRvP2x4kJFpxZZxzZS3FC0uiJVkcsTWIeW1SMl00HC6KMEc+1nx4p0+sBdZ4lBIoJXAu5EsqD6sa0CEcliWCYQLjXNGLBS/vlRzNalZN+D4eBqniysYQJSWJ8gz7EVfWUzZHMXkMiwZaBRhGWYJvJ3NeGWfsDDMujRLW84ReEuG9YBApYilZyzRP7fS5spEzzmO2BwnWeqraUdaOtV7EKNd825Ux/TRif1nxa69OMA6e2szpxZr1fsJ6P2FnkAQ1A9f+TtsRx1pJnAvqyFVjmBfhnE5UsqPjvcGZxhC8978ghHjyjsM/APzm9vFPAj8P/Kn2+E957z3wS0KIsRDifHvuz3nvjwCEED8HfJ8Q4ueBoff+l9rjPwX8DuAfvs01zoS7dXjfGT6rjcVYhzHu9sa310qYLI2jso55YdgYJAgpOFr6kKgvQtPksi5QQvL13QWruuFw5Ukji7WhhBhaMUsHppVArk2YY6KVxdgwK6U2DUUr9DPKFZHWTMqaprJUtWd7HIcNvK5wHnpxaMzMY4FSMCkslSnw3jErKybzBiMFiRQsqoajZYPddjy1PWS9l5BGmmnRUFtJngYvbJRrlqUN2mKl4WjZEGuJjiRbecSv784RQB5HnB+ngKBpHPOyIdaKC63kzqJs2J2WvH68YndWcWtecn6Yc2k9u++BYB0dHWfHowhS73jvb7aPbwE77eOLwOunzrvWHnu749fucvztrvEWhBA/RPCYuHLlyoP+LPfktJLurKi4NS2xeHZnFduDhAtrGdY6jouGWEm2hhnLsuHWrCTWEiFC8n9ZW1INq9q0kydBqjCvZda8+Zp1K9fS5umZm/A41SE3M3UNa7mg8kGSP1KwrBtWVU1lPbkWrCpHWTfM64ZIBW0xPEyWnrmq0AJ6ccrhssE0lkVtcUApQw5nmAnWezGjXHNtUrDejxnlikXVcH6th5YC6yBShl6qaazlaGm4ME7RShBFivVejJKCSEoGacyibNhZS7k8DtV5kQqS/7969Zj9eUFpHE9v9hBSkCjRFkt09SsdHY+aR5oF9d57IR5k/NPDv4b3/seAHwN44YUXHupa0khxYZjy0v6cOBL04lD1NClqtBJYPGVjSCPFS3tzzo1zBlXNrHa8vDvHemicY1pY8kiyrB1SwHIFMVDecb2GEPOUgjBCuD3WmHBcGzhaeiobKsuqxqJU6I9pmjBGubYVtg07CSSK0FujZZv4F7AoHd41eOExnJQ7SzIt6UcRQiq0kMRasDspQXi+fjDnXGHI04hxHiGVZqMXEylF2YS+nQ9vDzhchGqxtUwTx5plaXAeNnsJu/Pqdr/RRj9maxADnjQ29GJN0VhUGzbrhnp1dDx6HsVt3m4b+qL9vNcevw5cPnXepfbY2x2/dJfjb3eNbwonmmOrynD1aMnrR6sgxNhYICTQrfOM0ojdWcVnrx7xyy8fUhtPlkSMkog8UWjhqWvDdBXUl8sa6gZK9zbXBkr/5kFhJ8drgly/JxiKlYN5A8uqzckIMN4jBQgduuN9q64cRYpUS7yULKoaJ0JJdRopFGG+jVahqGBZGV7eW/DrN+bEWnK0NGgheX26YlZWvHhrjhaeS+s5W4OEj54bsDMKQpfjXhjGppTCWs8w1Xzy0phpEYYFZJEiUoKDeYUQYJ0LPTFNGIcAIe91r/zLyXvjXFcA0NFx1jwKA/MzwEkl2A8Cf+/U8d/TVpN9JzBtw1w/C3yvEGKtTe5/L/Cz7fdmQojvbKvHfs8dr3W3a5w5ZWN57WjF1cMlv/zyIa8cLrh6tOTLN6b8kxf3eGlvxvXJispYlrXlY+cHVNbR12E2fVFZfu3aMcvShk09VlgP06UP1V288XE3Yu7tlsZAItqZLqdeoAYqC4sSpgVMCsikwPjg1UQatnsapCSNgl8gJFhk0EqTEussqzps9Putp5FqSZ5ERDLkk7yDsrasZRpjHS/vL7l+XIa8yijj4jgj0YqdYcaHdwY8sZGTJ0Gg8tpxwd684trxirKxTFY1rx2uuD4peWV/ya1ZSaIF672EC+PsrvmXk/fm9aMVrx2F1+no6Dg7zjREJoT464Rk+6YQ4hqhGuxHgL8phPgDwFXgd7an/wPg+4GXgBVhRDPe+yMhxF8AfqU978+fJPyBf4dQqZYRkvv/sD1+r2ucKac7+5WUHC4rDhcVsZZU1nN9uqS2lg/tDLg1Lbk4FuSJZrPdFL9wY4YxjkVhiJSgKgxlZRA+SL4IFzyLXhSGhzn7Zk8lpj3vHuvzQHEPy9QQ9NB0+/xF5emnInhLDm7OK4aJJo0jRmlMEitiKZgUDb1YUTaeUU/TiyK2hgkIwcYgIZKO3XnNwbIm1mFGi9KKpPXQntzKkYTBYOdHKcDtxtUs1szLht15SawF3nsOFjVXD5fsLyo+fnHIb7g0ZlnWFI3jO57cIEv0XY3LO6kudHR0PHzOuors37zHt77nLud64A/f43V+HPjxuxz/NPDxuxw/vNs1zpo3SpMVs6Jmf1Hy2sGK8+OMzTxGeNjsp3xoZ0DRWA4WNTvA8bLBes8g1RSNweMwTlLUlroJhiFPIE8iEi1ZlFVIlnvBvHCsXHBFhYRMhnDXnQUAAP0IygYKgiE6QRJCaBmQxZBnkqJypIkC78h6Md47kkgzzjRppDEWFrUhiyVrWUIShU3b+DAiuWwsxli+enPO3jRoj/WTkOBfVobpoibVmhvHBedGGa7tWbmzcRUPCsH2IOWLN6a3Xe5hqilqzyiFQZZQ2wqh7i3Df/q9Ado5MabL1XR0nCFdq/ND5KQ0uW6nKnrnWdWW41WNsY5BEpG3UyxTrTE4PvP6hINlxUt7C8Y9jfOKpzcH3Jys8HHwKoQK3gvOcbRosB6GcVBd7keG49JRlEEOJlIgNWzI0NGvCAbnRDG5vsu6NSFR309BR4qmtlgPRWGJooherIm0xHofChdGGZGWjHNF0Qict3zlxozDRY1q8x8X1zJ2xhk3DxekUcTTWwmz0rKoQtJ+nCdtPkVya1qwNUhRbfL+YF5RmdDLclKSDJ6tQYIWgsY79udhuqfzoQFUSUEs7x3xfSfVhY6OjodPV8v5EDkpTS5ry81JyflxzscvDOjFmlhKskSRKoVHMEwUrx4tSSLJej9hECskkvVUg/BIKbm8PmB7lIYhYEqidAipXd7IWOunCATL2iEExHE7TdKHCrEkDh36eRo68xsLyzoYnDvJQjEWiwqaxlI56CcS7yx4x7wybGQRa3nC1iAjiRTPnR8wSDM+tNOjbIJcjHFBPmZaNjTWEymJR/DkZo88jlnLY4x1PL2VcWkjZ5hFGOepTfDerk0K9ucVHm5rieWJ5twoxbdjnq33XBjlfGizR+N8GCNtHB+/OEK/jSz/26kudHR0nA2dB/OQSSPFpbWc65OCYRZxaT3n5qRgXhqePz8g0YpEB+FL6zzDfsKkaIiTiN1ZyaCt1kq1RAmJdTBMI7wTpFqyqEI/jPWeZVWH4WA+NELiYVV6ag+yhn6uWM4dzry5pLm1JxjeyLnkKaQK0iQO6stWYKXFOlBYjsuGNFbsjBLGWczRqqGoLIiEcS9hf17z7U9tkGrFq0cLJquGnX7MdJkyrwzrPY118PRWzicvr7ExSNFSht+D9cxLQ6LlXbXE0kjxxEaPzUHC/jyUUWdJxL/6/DmkCp7L2xmX0+/NlfW8m2rZ0fFNojMwZ0CkJFuDhFnZoGR4/Mxmn+fODZFS0FhHURt+/frstsLy+XHOZFmzOYx5+WDFziDipf0FANIotkaK+cJSNQ2FVUTCU7Wd+isDVRPKiyvfji+WMFs11ObN+RZ4c5hM84bS8vqwxzBRzGvHQVmhhARp0ZGiF0me2erjERyuGhIpWB+k1I1hWTQY44gjhRCSjUGK90Euf7MfM8g0l9YyhBBsDULD5K1ZSSUcWkq2R8FwnFalvjM/IqVgkIZw3bsxEHdTXejo6DgbOgPzkDkZQBYMiacfS3ppqBLTWrKqDDcmBQ5PP4s4XJQcrSrmK8OoF5NoTVkb5s7RuDDfxVKx3K+QQhAphbOWvSKMQrZtVVgF0BqXPA5zXhbtQLE7DYxqjylCwj9qGzG9N+zPDYIwryZVgkUlWAnPS/tLGgeXxxkbo5wsjchiyScurfG5q5LSeA6XFb1Ygxd8eGdAGmvWpeB4aRjnCcM0Yq0Xc7CsaaXQ2B4kpJFin4qyNsRRyFHdKz/SGYiOjvcPnYF5CJx0jgvP7VLYLE7ox5rKOq6shVLY6armc69PAE+kJdvDiL15gXSe146WWA/XCBL1pQkTKhWeVRUkW5TyXBhBtXI4Gyq/LBDxRiWYBPqRZFU5lu362h5KPNATkEVQmDCwrLZh9kusgxfkPcSR5lIeMylqfGlQQrHei6iNYVEbNrwjjxXL0vC13QXDPOZf/fh5Xrw5pbKOLFGhak4IRnnClfUeILg4yrgxK1ECdKzwzrM3D9I5jXVcn1VAMDpPbHZaYh0d73c6A/MuOT0y2XlPYxxZPwEgjhSN8xQmNB++tDvjpb2Q2HfeY5xjmEZc3urx8uGKxjgO5xVFY5ivDHEMZR069wUheb87Nczv0h9oCJMonYfjpaM49T3JG/0xvh30ohxUNVjVTrBsJVZGvYTLaxmR0hyvarQUoXdESxrnqYyjcUFTLVJBF+zCeswgjXjh6U12p2E+i1YSJYMuWR5rlpXB4Ckaw7KytyVfskhywzr6iWa4HVEZG4xcpyXW0fG+p/svfhecbt7rJZpESQ6XNbUJFsDYMFJ4f14hCCXLRd1wa1JSNZZX91fcnBZESrLRi1gYi1AQKUUvlZjmDa9EyeBp3M24BBGVkH9p4C3GJZbByxnEMErD40iD0pCpkIPRHrI44rue2eLcuEeiwXrL5iDh0lrOWh6xqgy1cRS1pZ8EUcoraznnRxnGeRZlw6KyPLnRY5jFKCE4an8fUgg0gsNFDd6Txxq853Be40+NNchijYdulktHx2NA58G8C+5s3osjxUY/pmocjfUIuD0jPmn7SJASIRyVcSyKiqI2HM9LXrw153hVAwJrLVJKegksKocRYN1b9cXuB0eQ8NfAOJE8vT2g8TBZ1hytDArPWixZ68VcHPc4N87QUnL1SPCRc2PKyrI0juNVzWY/4ZNX1kiiCAFs9hOevzhiWVnWMkGTKNbymFEvIYmD17YoDaM0VNMJKdjoxaway6o2KCnYGMQI2fWndHQ8jnQG5l1wt+a9LNJcGme3w2LHi5pbs5Jzw4SNQcLLewt6iaQyjjyNmK0aXj9aMCsa6saSRRF5pikaT9MYbKuMfC/jImg9HEIY7G7qWhLY6Ame2RkCYXbLhXHKlU1NWVlULLg8yvjwuQHHRc3xogk5okFGui7pxZrSmNtyLHGimRcNF8YZG72EjR63c1DXJgXGOtJIsTNIqPKIJ9d7aB1CcFms6acaKUSYOulCzmVvXlEZgxSi60/p6HhM6AzMu+Ckee/GpGBZGbSSt4UWDxd129ch2cFzbVIwyjTnRhnGe64drdBSsNaLaZoGYyGVnlrAqqipHCRRROoMxT2lLVsJfUKILJZQ3EVpuR/DzjgjiTXOgfWOUZ4wrQy9XPPs5oAnNnq8tD9nUTRYF+TxV9pyvGhYVmGkwPPnR6AlZSuLf3HtDR2vk8qukxk4J8bi0lp+u0fl9IycxrvbxiSNFFci1fWndHQ8ZnQG5iEg7vh8EjqTUrIsGyZFQ1lb6sbykXMDbs4K9iYwMY79ecXhqgm5m9qgtcAYj9YKIT1JrMldw6p+wzs5bUNOpGCQoQhAExL+J2ymkGUR67005HEIc2WySJMnmo+eG7IzSoOcv3EMspiysaway+6kZNzTbAxShmlEaRxraYTSkgujjDx565/POzUz3uv7XflxR8fjR2dg3gUnSf5YS/JE31bovTTOaIxjd1awPw9J7uNlxc4g4+pqRWHNbeNzc1biraUxDk8Yc9yPYNVYaiUpK0dRvzFM7LQvc6KeHCvoJVCaUHWmfGimzBQMU0UWaYraIIm4tJGwYWNcq40W1Icl+9OCNI44P0o4WtZcP15SWMeTeY9zwxzdToq8uJ6Tx3dXLD7hnYxFZ0w6Oj4YdAbmXfB2Cr2IMFTMONcOyxJoLfjyrTCpUgFrWYQUHicdsRCsjRLKRrDRV1w9XFKVjrIJBsTa4CGdNEjmbRWYApRSDPOI1axkexQ2/7Lx5LHi0jhncxBRWXh6a4CWgsY5PIIPbw/YHMS3p0ZeWUsxDkZZjHeWPImCxpeUQeq/dkRttVdHR0fHO9EZmHfBvRR6IcjFPLXZBxGUig/mJV+8MaVoLM5BFiviJGJrkOG8w7iKwjis9ywqgZaKuCdhFdL7jYVeGt4wqcA5QaQlJwLCFod1YSLlWpqQxQ6J5NwoJo8jelnEpXHGII/YnVYYa9keJpwbpVSN4/w443BZcbRsMNZx7vyYYa65NQnikwJ4arNH1PWndHR03CedgXkXnE5an66AUkLgXPBuLo5zDmYVq8ohEQzyBG+CiKSzLhgpB71EsywrYhWaMNfyCCkVznhiJein4L3AYUm1IlaK2lmMFeSpQHlJHhtiFbGoDJGQrPUUF9Z6nB/3eGYr58XdJbNlQ6QE50a9IKLpBVc2ejgX1I83e0koVhhlXJ8W2FNlaUl0Ny3mjo6OjrvTGZh3yZ1J69o6rk0KGue4dViy0Yt5ZqdPGklWxoEDrSWzZc1L+5aPnOuzt6iJk5q5Flzc6IWS4MpSNJ7aGIwXxM7hpaIXa7aGCXkcIXAcLCqEEExLx9YwI5Kw0U/IteT8ep9vubzGExt9skTTz2K2+gmpDnNYvOD2mvfmFVIKYqG4MA7zXk68sJOfrWjsbQHKE3mcruqro6PjXnQG5iFwkrQ+3dl/WovsmXGfXhxhjGVaGerG0Y8VT25n/OLXjri4llM3CcuhJYsU670+rxwssS7kX9JIh1yNDTmYb3lizDCNGSaa/UXJV27NGfegMoZ50ZBqyeYw5aPnhzy50SdtCxBipRhl8ZsMwpvXHGFaY3NpnN3uVYnuaIA8LY9zutS4o6Oj4zSdgXmI3K2zv3EeocJkxlvTkjUlwcO5Ycq14xWX13Och715SRppkkjyzEbOMI0Y9xJWjeH1wxXOe7zzfOzSmJ1hytXDJeN+zCiPsQiuHixxhSGPFKnWjPspF9ZSLGFE8b0aGO9VqODFW3tazo1SgG62fUdHx33RGZiHyNuN5Y0i+Zb+j0vkfOnmDCXg6Y0+tbc4J3hie8B3jXOitkHRNo6XDxdoHSZYrqqTqq8eB8uay2s5g1RzdX+BVprNQcxHzg2oGjg/TNFa3jOU9aBrbqz7hmfbd2G1jo4PFp2BeYjcK+l/r2bCfhbx3c9t88Xr07Bpy4Tnzg/Y6CVv3oAjxbPRkFvTEq0cg0Sz2U9IIsXOMKWsDdOiYZjFQQJmvY9WknlpkFLctfLr9Gb/IGv+Rmfbd2G1jo4PHsJ3qrW3eeGFF/ynP/3pd/06D3qnboyjdu4dR/+eft26DU05H0Q1x1nE9cmKeWluS++v9WI+tD14yxruttnHSt73mh/UWDjnee1o1YbVglFqrO/Cah0djwlCiF/13r9w5/HOgzkDTt/134+x0Vqi72NywunXTeVbJVeyRHNzUtDY0BB5vtVFO83ppP6dOZT77XF50Nn2b9eQ2nX0d3Q8vnQG5gw567DQneGrNFI8sdF7243/9GbvnA+zV6x74M3+QeRevtGwWkdHx/ubzsCcEW/nKZxlWOidNv6TzX5RNhyvGmpjcR7Oj7Mz69J/p9xUR0fH40lnYM6I90pY6M4QnZSC7UHCZ147RglBEinWsoi9ecWVSJ3Zpv+gYbWOjo73P52BOSPeC2Ghe4XoIi05N0rJWoMihWBZnb3xe9DcVEdHx/ubzsCcEY86LPR2ITolBLpVyTwxgt9M49eVLHd0fDDoDMwZ8ijDQm8XoouUfGTG71Hlpjo6Or75dAbmjHlUw7XeKUT3qIzfeyU31dHRcfZ0wz0eU05CdI31LCtDY/1bvJSTLv9vpudw2vABXclyR8djTOfBPMa8Fyu3HnVuqqOj45vHY+3BCCG+TwjxohDiJSHEDz/q9TwKHoWX8k6cGL7L6zlX1vMuwd/R8Zjy2BoYIYQC/t/AbwWeB/5NIcTzj3ZVHSe8Fw1fR0fHw+WxNTDAtwMvee9f9t7XwN8AfuARr6mjo6PjA8PjbGAuAq+f+vpae+xNCCF+SAjxaSHEp/f3979pi+vo6Oh43HmcDcx94b3/Me/9C977F7a2th71cjo6OjoeGx5nA3MduHzq60vtsY6Ojo6ObwKPs4H5FeBDQoinhBAx8G8AP/OI19TR0dHxgeGxnmgphPh+4D8FFPDj3vu/+A7n7wNXTx3aBA7ObIEPj26dD5dunQ+Xbp0Pl/fiOp/w3r8lx/BYG5h3ixDi03cbA/peo1vnw6Vb58OlW+fD5f2yTni8Q2QdHR0dHY+QzsB0dHR0dJwJnYF5e37sUS/gPunW+XDp1vlw6db5cHm/rLPLwXR0dHR0nA2dB9PR0dHRcSZ0Bqajo6Oj40zoDMw9eD9I/QshLgsh/okQ4teFEF8SQvyxR72mt0MIoYQQvyaE+PuPei33QggxFkL8bSHEV4QQXxZC/KZHvaa7IYT4P7fv+ReFEH9dCJE+6jUBCCF+XAixJ4T44qlj60KInxNCfK39vPYo19iu6W7r/A/b9/3zQoj/TggxfoRLPFnTW9Z56nt/QgjhhRCbj2Jt90NnYO7C+0jq3wB/wnv/PPCdwB9+j67zhD8GfPlRL+Id+CvAP/LefwT4Ft6D6xVCXAT+KPCC9/7jhEbif+PRruo2PwF83x3Hfhj4x977DwH/uP36UfMTvHWdPwd83Hv/CeCrwJ/+Zi/qLvwEb10nQojLwPcCr32zF/QgdAbm7rwvpP699ze9959pH88Jm+FbFKPfCwghLgH/K+CvPuq13AshxAj4l4D/GsB7X3vvJ490UfdGA5kQQgM5cOMRrwcA7/0vAEd3HP4B4Cfbxz8J/I5v5pruxt3W6b3/H7z3pv3ylwj6hY+Ue/w+Af5fwP8VeE9XaXUG5u7cl9T/ewkhxJPAtwK//IiXci/+U8I/hHvE63g7ngL2gf9PG8r7q0KI3qNe1J14768D/xHh7vUmMPXe/w+PdlVvy473/mb7+Baw8ygXc5/8fuAfPupF3A0hxA8A1733n3vUa3knOgPzGCCE6AN/B/jj3vvZo17PnQghfhuw573/1Ue9lndAA58CftR7/63AkvdGOOdNtDmMHyAYxAtATwjxf3i0q7o/fOiLeE/fdQsh/iwh/PzTj3otdyKEyIE/A/zfH/Va7ofOwNyd943UvxAiIhiXn/be/91HvZ578F3AbxdCvEoIN/4rQoi/9miXdFeuAde89yde4N8mGJz3Gr8FeMV7v++9b4C/C/zPHvGa3o5dIcR5gPbz3iNezz0RQvxe4LcB/5Z/bzYJPkO4sfhc+/90CfiMEOLcI13VPegMzN15X0j9CyEEIV/wZe/9f/Ko13MvvPd/2nt/yXv/JOF3+f/z3r/n7ri997eA14UQz7WHvgf49Ue4pHvxGvCdQoi8/Rv4Ht6DxQin+BngB9vHPwj8vUe4lnsihPg+Qhj3t3vvV496PXfDe/8F7/229/7J9v/pGvCp9m/3PUdnYO5Cm+j7d4GfJfzj/k3v/Zce7aruyncBv5vgEXy2/fj+R72o9zl/BPhpIcTngU8Cf+nRLuettB7W3wY+A3yB8H/8npAPEUL8deAXgeeEENeEEH8A+BHgfymE+BrB+/qRR7lGuOc6/wtgAPxc+7/0Xz7SRXLPdb5v6KRiOjo6OjrOhM6D6ejo6Og4EzoD09HR0dFxJnQGpqOjo6PjTOgMTEdHR0fHmdAZmI6Ojo6OM6EzMB0dHR0dZ0JnYDo6zgghxM8LIV5oH/+Dhyn/LoT4t4UQv+dhvV5Hx1mgH/UCOjo+CHjvH2oDrPf+kTcBdnS8E50H09FxCiHEk+3QqZ8QQnxVCPHTQojfIoT4n9qBWd8uhOi1g6D+Rau6/APtczMhxN9oB5X9d0B26nVfPRkMJYT474UQv9oODPuhU+cshBB/UQjxOSHELwkh7qk6LIT494QQf7J9/PNCiP+gXc9XhRD/i/a4EkL8R+1Qss8LIf5Ie/x72nV/of05klNr/MttF/unhRCfEkL8rBDi60KIf/vUtf8vQohfaV/z33+ob0DHY0VnYDo63sqzwH8MfKT9+F3A/xz4kwQl2z9L0FP7duC7gf+wlfX/Q8DKe/9R4M8B33aP1//93vtvA14A/qgQYqM93gN+yXv/LcAvAH/wAdas2/X88fbaAD8EPAl8sh2i9dMiTL78CeB/773/DYQoxh869Tqvee8/Cfyz9rz/HWGY3b8PIIT4XuBDhJlJnwS+TQjxLz3AOjs+QHQGpqPjrbzSigo64EuEaYyeoPv1JGGS4A8LIT4L/DyQAlcIw8r+GoD3/vPA5+/x+n9UCPE5wlCry4QNG6AGTsZJ/2p7rfvlREn79PN+C/BfnQzR8t4fAc+1P99X23N+sl33CSeirl8Aftl7P/fe7wNVm0P63vbj1whaaB85tf6OjjfR5WA6Ot5KdeqxO/W1I/zPWOB/671/8fSTgrDx2yOE+M2Ejf83ee9XQoifJxgogOaURLzlwf4/T9b4oM+71+uc/rlPvtaAAP6y9/6/ehfX6PiA0HkwHR0Pzs8Cf6SVykcI8a3t8V8ghNMQQnwc+MRdnjsCjlvj8hFC+Oms+Dng/9SOVUYIsQ68CDwphHi2Ped3A//0AV7zZ4Hf3w65QwhxUQix/RDX3PEY0RmYjo4H5y8AEfB5IcSX2q8BfhToCyG+DPx5QrjqTv4RoNtzfoQQJjsr/iphdszn25Dc7/Lel8DvA/6WEOILBM/kvivS2tHM/w3wi+3z/zZB4r6j4y10cv0dHR0dHWdC58F0dHR0dJwJXZK/o+M9jBDizwL/+h2H/5b3/i8+ivV0dDwIXYiso6Ojo+NM6EJkHR0dHR1nQmdgOjo6OjrOhM7AdHR0dHScCZ2B6ejo6Og4E/7/uW1+Zc4xM/sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind=\"scatter\", x=\"median_income\", y=\"median_house_value\", alpha=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "external-separation",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing[\"rooms_per_household\"] = housing[\"total_rooms\"] / housing[\"households\"]\n",
    "housing[\"bedrooms_per_room\"] = housing[\"total_bedrooms\"] / housing[\"total_rooms\"]\n",
    "housing[\"population_per_household\"] = housing[\"population\"] / housing[\"households\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "entire-circle",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value          1.000000\n",
       "median_income               0.691831\n",
       "rooms_per_household         0.192575\n",
       "total_rooms                 0.131435\n",
       "housing_median_age          0.071357\n",
       "households                  0.071242\n",
       "total_bedrooms              0.057568\n",
       "population                 -0.016033\n",
       "longitude                  -0.039987\n",
       "population_per_household   -0.135142\n",
       "latitude                   -0.150124\n",
       "bedrooms_per_room          -0.240362\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix = housing.corr()\n",
    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "useful-script",
   "metadata": {},
   "outputs": [],
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "superior-newark",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing = strat_train_set.drop(\"median_house_value\", axis=1)\n",
    "housing_labels = strat_train_set[\"median_house_value\"].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "noble-management",
   "metadata": {},
   "outputs": [],
   "source": [
    "#데이터 정제"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "married-password",
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>&lt;1H OCEAN</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>6563</th>\n",
       "      <td>-118.13</td>\n",
       "      <td>34.20</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4.9312</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12053</th>\n",
       "      <td>-117.56</td>\n",
       "      <td>33.88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1196.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>2.0682</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13908</th>\n",
       "      <td>-116.40</td>\n",
       "      <td>34.09</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>872.0</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>3.2723</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11159</th>\n",
       "      <td>-118.01</td>\n",
       "      <td>33.82</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>4.0625</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15775</th>\n",
       "      <td>-122.45</td>\n",
       "      <td>37.77</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3095.0</td>\n",
       "      <td>682.0</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>3.5750</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16354 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "6563     -118.13     34.20                46.0       1271.0           236.0   \n",
       "12053    -117.56     33.88                40.0       1196.0           294.0   \n",
       "13908    -116.40     34.09                 9.0       4855.0           872.0   \n",
       "11159    -118.01     33.82                31.0       1960.0           380.0   \n",
       "15775    -122.45     37.77                52.0       3095.0           682.0   \n",
       "\n",
       "       population  households  median_income ocean_proximity  \n",
       "17606       710.0       339.0         2.7042       <1H OCEAN  \n",
       "18632       306.0       113.0         6.4214       <1H OCEAN  \n",
       "14650       936.0       462.0         2.8621      NEAR OCEAN  \n",
       "3230       1460.0       353.0         1.8839          INLAND  \n",
       "3555       4459.0      1463.0         3.0347       <1H OCEAN  \n",
       "...           ...         ...            ...             ...  \n",
       "6563        573.0       210.0         4.9312          INLAND  \n",
       "12053      1052.0       258.0         2.0682          INLAND  \n",
       "13908      2098.0       765.0         3.2723          INLAND  \n",
       "11159      1356.0       356.0         4.0625       <1H OCEAN  \n",
       "15775      1269.0       639.0         3.5750        NEAR BAY  \n",
       "\n",
       "[16354 rows x 9 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.dropna(subset=[\"total_bedrooms\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "imposed-cholesterol",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "imputer = SimpleImputer(strategy=\"median\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "coordinate-musical",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SimpleImputer(strategy='median')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_num = housing.drop(\"ocean_proximity\", axis=1)\n",
    "imputer.fit(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "talented-combat",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-118.51  ,   34.26  ,   29.    , 2119.5   ,  433.    , 1164.    ,\n",
       "        408.    ,    3.5409])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.statistics_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "otherwise-yorkshire",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-118.51  ,   34.26  ,   29.    , 2119.5   ,  433.    , 1164.    ,\n",
       "        408.    ,    3.5409])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_num.median().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "loving-switch",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = imputer.transform(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "automated-current",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_tr = pd.DataFrame(X, columns=housing_num.columns, index=housing_num.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "undefined-missile",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_cat = housing[[\"ocean_proximity\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "concerned-picnic",
   "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>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19480</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8879</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13685</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4937</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4861</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ocean_proximity\n",
       "17606       <1H OCEAN\n",
       "18632       <1H OCEAN\n",
       "14650      NEAR OCEAN\n",
       "3230           INLAND\n",
       "3555        <1H OCEAN\n",
       "19480          INLAND\n",
       "8879        <1H OCEAN\n",
       "13685          INLAND\n",
       "4937        <1H OCEAN\n",
       "4861        <1H OCEAN"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "beneficial-devices",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OrdinalEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "broken-metallic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.],\n",
       "       [0.],\n",
       "       [4.],\n",
       "       [1.],\n",
       "       [0.],\n",
       "       [1.],\n",
       "       [0.],\n",
       "       [1.],\n",
       "       [0.],\n",
       "       [0.]])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ordina_encoder = OrdinalEncoder()\n",
    "housing_cat_encoded = ordina_encoder.fit_transform(housing_cat)\n",
    "housing_cat_encoded[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "floral-flooring",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "       dtype=object)]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ordina_encoder.categories_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "attractive-advantage",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "sorted-owner",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_encoder = OneHotEncoder()\n",
    "housing_cat_1hot = cat_encoder.fit_transform(housing_cat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "sunset-gasoline",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<16512x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 16512 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_1hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "confused-point",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., 0., 0.],\n",
       "       [1., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 1.],\n",
       "       ...,\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [1., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 1., 0.]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_1hot.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "informal-webmaster",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "       dtype=object)]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_encoder.categories_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "expanded-uzbekistan",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, TransformerMixin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "difficult-header",
   "metadata": {},
   "outputs": [],
   "source": [
    "rooms_ix, bedrooms_ix, population_ix, households_ix = 3, 4, 5, 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "egyptian-philadelphia",
   "metadata": {},
   "outputs": [],
   "source": [
    "class CombinedAttributesAdder(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, add_bedrooms_per_room = True): # *args 또는 **kargs 없음\n",
    "        self.add_bedrooms_per_room = add_bedrooms_per_room\n",
    "    def fit(self, X, y=None):\n",
    "        return self  # 아무것도 하지 않습니다\n",
    "    def transform(self, X):\n",
    "        rooms_per_household = X[:, rooms_ix] / X[:, households_ix]\n",
    "        population_per_household = X[:, population_ix] / X[:, households_ix]\n",
    "        if self.add_bedrooms_per_room:\n",
    "            bedrooms_per_room = X[:, bedrooms_ix] / X[:, rooms_ix]\n",
    "            return np.c_[X, rooms_per_household, population_per_household,\n",
    "                         bedrooms_per_room]\n",
    "        else:\n",
    "            return np.c_[X, rooms_per_household, population_per_household]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "fluid-sleep",
   "metadata": {},
   "outputs": [],
   "source": [
    "attr_adder = CombinedAttributesAdder(add_bedrooms_per_room=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "burning-certificate",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_extra_attribs = attr_adder.transform(housing.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "iraqi-minutes",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "complimentary-hampton",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "opened-racing",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "adjusted-chemical",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_pipeline = Pipeline([\n",
    "        ('imputer', SimpleImputer(strategy=\"median\")),\n",
    "        ('attribs_adder', CombinedAttributesAdder()),\n",
    "        ('std_scaler', StandardScaler()),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "paperback-waterproof",
   "metadata": {},
   "outputs": [],
   "source": [
    "houing_num_tr = num_pipeline.fit_transform(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "liberal-puppy",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "passing-piano",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.compose import ColumnTransformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "characteristic-drive",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_attribs = list(housing_num)\n",
    "cat_attribs = [\"ocean_proximity\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "alert-sunset",
   "metadata": {},
   "outputs": [],
   "source": [
    "full_pipeline = ColumnTransformer([\n",
    "    (\"num\", num_pipeline, num_attribs),\n",
    "    (\"cat\", OneHotEncoder(), cat_attribs),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "breeding-elements",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_prepared = full_pipeline.fit_transform(housing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "naughty-sweden",
   "metadata": {},
   "outputs": [],
   "source": [
    "#2.6 모델 선택과 훈련"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "worldwide-funeral",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "polar-noise",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_reg = LinearRegression()\n",
    "lin_reg.fit(housing_prepared, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "developing-share",
   "metadata": {},
   "outputs": [],
   "source": [
    "some_data = housing.iloc[:5]\n",
    "some_labels = housing_labels.iloc[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "aggregate-store",
   "metadata": {},
   "outputs": [],
   "source": [
    "some_data_prepared = full_pipeline.transform(some_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "entitled-people",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "예측 :  [210644.60459286 317768.80697211 210956.43331178  59218.98886849\n",
      " 189747.55849879]\n"
     ]
    }
   ],
   "source": [
    "print(\"예측 : \", lin_reg.predict(some_data_prepared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "expected-cooking",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "레이블 :  [286600.0, 340600.0, 196900.0, 46300.0, 254500.0]\n"
     ]
    }
   ],
   "source": [
    "print(\"레이블 : \", list(some_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "latin-robin",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "global-possession",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "executive-holder",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_predictions = lin_reg.predict(housing_prepared)\n",
    "lin_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "lin_rmse = np.sqrt(lin_mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "alternative-chess",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68628.19819848923"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "vulnerable-stevens",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "rapid-african",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "cardiovascular-tracy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor()"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_reg = DecisionTreeRegressor()\n",
    "tree_reg.fit(housing_prepared, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "proper-cisco",
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_predictions = tree_reg.predict(housing_prepared)\n",
    "tree_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "tree_mse = np.sqrt(tree_mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "canadian-syndicate",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_mse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "legitimate-underground",
   "metadata": {},
   "outputs": [],
   "source": [
    "#교차 검증을 사용한 평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "russian-update",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "developing-tsunami",
   "metadata": {},
   "outputs": [],
   "source": [
    "scores = cross_val_score(tree_reg, housing_prepared, housing_labels, scoring=\"neg_mean_squared_error\", cv=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "athletic-desert",
   "metadata": {},
   "outputs": [],
   "source": [
    "tree_rmse__scores = np.sqrt(-scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "nutritional-supervision",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "점수 :  [69168.06580377 65957.83474559 71026.87436236 70834.37546379\n",
      " 71380.80872216 74036.47856707 71078.05976993 69985.93941365\n",
      " 77188.5572031  70841.67846541]\n",
      "평균 :  71149.86725168291\n",
      "표준편차 :  2780.393869133278\n"
     ]
    }
   ],
   "source": [
    "def display_scores(scores):\n",
    "    print(\"점수 : \", scores)\n",
    "    print(\"평균 : \", scores.mean())\n",
    "    print(\"표준편차 : \", scores.std())\n",
    "    \n",
    "display_scores(tree_rmse__scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "contrary-updating",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "점수 :  [66782.73843989 66960.118071   70347.95244419 74739.57052552\n",
      " 68031.13388938 71193.84183426 64969.63056405 68281.61137997\n",
      " 71552.91566558 67665.10082067]\n",
      "평균 :  69052.46136345083\n",
      "표준편차 :  2731.674001798342\n"
     ]
    }
   ],
   "source": [
    "lin_scores = cross_val_score(lin_reg, housing_prepared, housing_labels, scoring=\"neg_mean_squared_error\", cv=10)\n",
    "lin_rmse_scores = np.sqrt(-lin_scores)\n",
    "display_scores(lin_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "convenient-cincinnati",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "toxic-comment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor()"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "forest_reg = RandomForestRegressor()\n",
    "forest_reg.fit(housing_prepared, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "paperback-student",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18681.559316271425"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_predictions = forest_reg.predict(housing_prepared)\n",
    "forest_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "forest_rmse = np.sqrt(forest_mse)\n",
    "forest_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "dependent-anthony",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "점수 :  [49474.11381632 47710.49195481 50088.7031315  52134.51989346\n",
      " 49855.65075974 53496.64618711 48652.71842474 48286.97391734\n",
      " 52878.08554222 50109.69759691]\n",
      "평균 :  50268.76012241449\n",
      "표준편차 :  1861.5191100109907\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "forest_scores = cross_val_score(forest_reg, housing_prepared, housing_labels,\n",
    "                                scoring=\"neg_mean_squared_error\", cv=10)\n",
    "forest_rmse_scores = np.sqrt(-forest_scores)\n",
    "display_scores(forest_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "sudden-respect",
   "metadata": {},
   "outputs": [],
   "source": [
    "#2.7 모델 세부 튜닝"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "typical-toner",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, estimator=RandomForestRegressor(random_state=42),\n",
       "             param_grid=[{'max_features': [2, 4, 6, 8],\n",
       "                          'n_estimators': [3, 10, 30]},\n",
       "                         {'bootstrap': [False], 'max_features': [2, 3, 4],\n",
       "                          'n_estimators': [3, 10]}],\n",
       "             return_train_score=True, scoring='neg_mean_squared_error')"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "param_grid = [\n",
    "    {'n_estimators': [3, 10, 30], 'max_features': [2, 4, 6, 8]},\n",
    "    {'bootstrap': [False], 'n_estimators': [3, 10], 'max_features': [2, 3, 4]},\n",
    "  ]\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state=42)\n",
    "grid_search = GridSearchCV(forest_reg, param_grid, cv=5,\n",
    "                           scoring='neg_mean_squared_error',\n",
    "                           return_train_score=True)\n",
    "grid_search.fit(housing_prepared, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "geological-north",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_features': 8, 'n_estimators': 30}"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "dedicated-press",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(max_features=8, n_estimators=30, random_state=42)"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "demographic-french",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "63669.11631261028 {'max_features': 2, 'n_estimators': 3}\n",
      "55627.099719926795 {'max_features': 2, 'n_estimators': 10}\n",
      "53384.57275149205 {'max_features': 2, 'n_estimators': 30}\n",
      "60965.950449450494 {'max_features': 4, 'n_estimators': 3}\n",
      "52741.04704299915 {'max_features': 4, 'n_estimators': 10}\n",
      "50377.40461678399 {'max_features': 4, 'n_estimators': 30}\n",
      "58663.93866579625 {'max_features': 6, 'n_estimators': 3}\n",
      "52006.19873526564 {'max_features': 6, 'n_estimators': 10}\n",
      "50146.51167415009 {'max_features': 6, 'n_estimators': 30}\n",
      "57869.25276169646 {'max_features': 8, 'n_estimators': 3}\n",
      "51711.127883959234 {'max_features': 8, 'n_estimators': 10}\n",
      "49682.273345071546 {'max_features': 8, 'n_estimators': 30}\n",
      "62895.06951262424 {'bootstrap': False, 'max_features': 2, 'n_estimators': 3}\n",
      "54658.176157539405 {'bootstrap': False, 'max_features': 2, 'n_estimators': 10}\n",
      "59470.40652318466 {'bootstrap': False, 'max_features': 3, 'n_estimators': 3}\n",
      "52724.9822587892 {'bootstrap': False, 'max_features': 3, 'n_estimators': 10}\n",
      "57490.5691951261 {'bootstrap': False, 'max_features': 4, 'n_estimators': 3}\n",
      "51009.495668875716 {'bootstrap': False, 'max_features': 4, 'n_estimators': 10}\n"
     ]
    }
   ],
   "source": [
    "cvres = grid_search.cv_results_\n",
    "for mean_score, params in zip(cvres[\"mean_test_score\"], cvres[\"params\"]):\n",
    "    print(np.sqrt(-mean_score), params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "increasing-marine",
   "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>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_max_features</th>\n",
       "      <th>param_n_estimators</th>\n",
       "      <th>param_bootstrap</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>...</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "      <th>split0_train_score</th>\n",
       "      <th>split1_train_score</th>\n",
       "      <th>split2_train_score</th>\n",
       "      <th>split3_train_score</th>\n",
       "      <th>split4_train_score</th>\n",
       "      <th>mean_train_score</th>\n",
       "      <th>std_train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.078709</td>\n",
       "      <td>0.001028</td>\n",
       "      <td>0.004277</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 2, 'n_estimators': 3}</td>\n",
       "      <td>-3.837622e+09</td>\n",
       "      <td>-4.147108e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.053756e+09</td>\n",
       "      <td>1.519591e+08</td>\n",
       "      <td>18</td>\n",
       "      <td>-1.064113e+09</td>\n",
       "      <td>-1.105142e+09</td>\n",
       "      <td>-1.116550e+09</td>\n",
       "      <td>-1.112342e+09</td>\n",
       "      <td>-1.129650e+09</td>\n",
       "      <td>-1.105559e+09</td>\n",
       "      <td>2.220402e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.256731</td>\n",
       "      <td>0.002431</td>\n",
       "      <td>0.012004</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 2, 'n_estimators': 10}</td>\n",
       "      <td>-3.047771e+09</td>\n",
       "      <td>-3.254861e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.094374e+09</td>\n",
       "      <td>1.327062e+08</td>\n",
       "      <td>11</td>\n",
       "      <td>-5.927175e+08</td>\n",
       "      <td>-5.870952e+08</td>\n",
       "      <td>-5.776964e+08</td>\n",
       "      <td>-5.716332e+08</td>\n",
       "      <td>-5.802501e+08</td>\n",
       "      <td>-5.818785e+08</td>\n",
       "      <td>7.345821e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.783018</td>\n",
       "      <td>0.006946</td>\n",
       "      <td>0.035246</td>\n",
       "      <td>0.001091</td>\n",
       "      <td>2</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 2, 'n_estimators': 30}</td>\n",
       "      <td>-2.689185e+09</td>\n",
       "      <td>-3.021086e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.849913e+09</td>\n",
       "      <td>1.626875e+08</td>\n",
       "      <td>9</td>\n",
       "      <td>-4.381089e+08</td>\n",
       "      <td>-4.391272e+08</td>\n",
       "      <td>-4.371702e+08</td>\n",
       "      <td>-4.376955e+08</td>\n",
       "      <td>-4.452654e+08</td>\n",
       "      <td>-4.394734e+08</td>\n",
       "      <td>2.966320e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.133935</td>\n",
       "      <td>0.002300</td>\n",
       "      <td>0.004715</td>\n",
       "      <td>0.000464</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 4, 'n_estimators': 3}</td>\n",
       "      <td>-3.730181e+09</td>\n",
       "      <td>-3.786886e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.716847e+09</td>\n",
       "      <td>1.631510e+08</td>\n",
       "      <td>16</td>\n",
       "      <td>-9.865163e+08</td>\n",
       "      <td>-1.012565e+09</td>\n",
       "      <td>-9.169425e+08</td>\n",
       "      <td>-1.037400e+09</td>\n",
       "      <td>-9.707739e+08</td>\n",
       "      <td>-9.848396e+08</td>\n",
       "      <td>4.084607e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.429455</td>\n",
       "      <td>0.003255</td>\n",
       "      <td>0.011897</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 4, 'n_estimators': 10}</td>\n",
       "      <td>-2.666283e+09</td>\n",
       "      <td>-2.784511e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.781618e+09</td>\n",
       "      <td>1.268607e+08</td>\n",
       "      <td>8</td>\n",
       "      <td>-5.097115e+08</td>\n",
       "      <td>-5.162820e+08</td>\n",
       "      <td>-4.962893e+08</td>\n",
       "      <td>-5.436192e+08</td>\n",
       "      <td>-5.160297e+08</td>\n",
       "      <td>-5.163863e+08</td>\n",
       "      <td>1.542862e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.279843</td>\n",
       "      <td>0.010347</td>\n",
       "      <td>0.034287</td>\n",
       "      <td>0.001016</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 4, 'n_estimators': 30}</td>\n",
       "      <td>-2.387153e+09</td>\n",
       "      <td>-2.588448e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.537883e+09</td>\n",
       "      <td>1.214614e+08</td>\n",
       "      <td>3</td>\n",
       "      <td>-3.838835e+08</td>\n",
       "      <td>-3.880268e+08</td>\n",
       "      <td>-3.790867e+08</td>\n",
       "      <td>-4.040957e+08</td>\n",
       "      <td>-3.845520e+08</td>\n",
       "      <td>-3.879289e+08</td>\n",
       "      <td>8.571233e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.179319</td>\n",
       "      <td>0.005302</td>\n",
       "      <td>0.004639</td>\n",
       "      <td>0.000295</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 6, 'n_estimators': 3}</td>\n",
       "      <td>-3.119657e+09</td>\n",
       "      <td>-3.586319e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.441458e+09</td>\n",
       "      <td>1.893056e+08</td>\n",
       "      <td>14</td>\n",
       "      <td>-9.245343e+08</td>\n",
       "      <td>-8.886939e+08</td>\n",
       "      <td>-9.353135e+08</td>\n",
       "      <td>-9.009801e+08</td>\n",
       "      <td>-8.624664e+08</td>\n",
       "      <td>-9.023976e+08</td>\n",
       "      <td>2.591445e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.591407</td>\n",
       "      <td>0.006569</td>\n",
       "      <td>0.012387</td>\n",
       "      <td>0.001073</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 6, 'n_estimators': 10}</td>\n",
       "      <td>-2.549663e+09</td>\n",
       "      <td>-2.782039e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.704645e+09</td>\n",
       "      <td>1.471569e+08</td>\n",
       "      <td>6</td>\n",
       "      <td>-4.980344e+08</td>\n",
       "      <td>-5.045869e+08</td>\n",
       "      <td>-4.994664e+08</td>\n",
       "      <td>-4.990325e+08</td>\n",
       "      <td>-5.055542e+08</td>\n",
       "      <td>-5.013349e+08</td>\n",
       "      <td>3.100456e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.793540</td>\n",
       "      <td>0.005098</td>\n",
       "      <td>0.034146</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>6</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 6, 'n_estimators': 30}</td>\n",
       "      <td>-2.370010e+09</td>\n",
       "      <td>-2.583638e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.514673e+09</td>\n",
       "      <td>1.285080e+08</td>\n",
       "      <td>2</td>\n",
       "      <td>-3.838538e+08</td>\n",
       "      <td>-3.804711e+08</td>\n",
       "      <td>-3.805218e+08</td>\n",
       "      <td>-3.856095e+08</td>\n",
       "      <td>-3.901917e+08</td>\n",
       "      <td>-3.841296e+08</td>\n",
       "      <td>3.617057e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.226917</td>\n",
       "      <td>0.002944</td>\n",
       "      <td>0.004440</td>\n",
       "      <td>0.000235</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 8, 'n_estimators': 3}</td>\n",
       "      <td>-3.353504e+09</td>\n",
       "      <td>-3.348552e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.348850e+09</td>\n",
       "      <td>1.241939e+08</td>\n",
       "      <td>13</td>\n",
       "      <td>-9.228123e+08</td>\n",
       "      <td>-8.553031e+08</td>\n",
       "      <td>-8.603321e+08</td>\n",
       "      <td>-8.881964e+08</td>\n",
       "      <td>-9.151287e+08</td>\n",
       "      <td>-8.883545e+08</td>\n",
       "      <td>2.750227e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.762174</td>\n",
       "      <td>0.007648</td>\n",
       "      <td>0.011892</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 8, 'n_estimators': 10}</td>\n",
       "      <td>-2.571970e+09</td>\n",
       "      <td>-2.718994e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.674041e+09</td>\n",
       "      <td>1.392777e+08</td>\n",
       "      <td>5</td>\n",
       "      <td>-4.932416e+08</td>\n",
       "      <td>-4.815238e+08</td>\n",
       "      <td>-4.730979e+08</td>\n",
       "      <td>-5.155367e+08</td>\n",
       "      <td>-4.985555e+08</td>\n",
       "      <td>-4.923911e+08</td>\n",
       "      <td>1.459294e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.305912</td>\n",
       "      <td>0.019248</td>\n",
       "      <td>0.033935</td>\n",
       "      <td>0.000584</td>\n",
       "      <td>8</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'max_features': 8, 'n_estimators': 30}</td>\n",
       "      <td>-2.357390e+09</td>\n",
       "      <td>-2.546640e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.468328e+09</td>\n",
       "      <td>1.091662e+08</td>\n",
       "      <td>1</td>\n",
       "      <td>-3.841658e+08</td>\n",
       "      <td>-3.744500e+08</td>\n",
       "      <td>-3.773239e+08</td>\n",
       "      <td>-3.882250e+08</td>\n",
       "      <td>-3.810005e+08</td>\n",
       "      <td>-3.810330e+08</td>\n",
       "      <td>4.871017e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.121684</td>\n",
       "      <td>0.001515</td>\n",
       "      <td>0.004759</td>\n",
       "      <td>0.000230</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 2, 'n_est...</td>\n",
       "      <td>-3.785816e+09</td>\n",
       "      <td>-4.166012e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.955790e+09</td>\n",
       "      <td>1.900964e+08</td>\n",
       "      <td>17</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.402926</td>\n",
       "      <td>0.001412</td>\n",
       "      <td>0.013715</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 2, 'n_est...</td>\n",
       "      <td>-2.810721e+09</td>\n",
       "      <td>-3.107789e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.987516e+09</td>\n",
       "      <td>1.539234e+08</td>\n",
       "      <td>10</td>\n",
       "      <td>-6.056477e-02</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-2.967449e+00</td>\n",
       "      <td>-6.056027e-01</td>\n",
       "      <td>1.181156e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.165078</td>\n",
       "      <td>0.003275</td>\n",
       "      <td>0.005299</td>\n",
       "      <td>0.000549</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 3, 'n_est...</td>\n",
       "      <td>-3.618324e+09</td>\n",
       "      <td>-3.441527e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.536729e+09</td>\n",
       "      <td>7.795057e+07</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-6.072840e+01</td>\n",
       "      <td>-1.214568e+01</td>\n",
       "      <td>2.429136e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.541256</td>\n",
       "      <td>0.009998</td>\n",
       "      <td>0.014269</td>\n",
       "      <td>0.000473</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 3, 'n_est...</td>\n",
       "      <td>-2.757999e+09</td>\n",
       "      <td>-2.851737e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.779924e+09</td>\n",
       "      <td>6.286720e+07</td>\n",
       "      <td>7</td>\n",
       "      <td>-2.089484e+01</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-5.465556e+00</td>\n",
       "      <td>-5.272080e+00</td>\n",
       "      <td>8.093117e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.204627</td>\n",
       "      <td>0.003072</td>\n",
       "      <td>0.004897</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 4, 'n_est...</td>\n",
       "      <td>-3.134040e+09</td>\n",
       "      <td>-3.559375e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.305166e+09</td>\n",
       "      <td>1.879165e+08</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.685166</td>\n",
       "      <td>0.005392</td>\n",
       "      <td>0.013930</td>\n",
       "      <td>0.000541</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "      <td>{'bootstrap': False, 'max_features': 4, 'n_est...</td>\n",
       "      <td>-2.525578e+09</td>\n",
       "      <td>-2.710011e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.601969e+09</td>\n",
       "      <td>1.088048e+08</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-1.514119e-02</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-3.028238e-03</td>\n",
       "      <td>6.056477e-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "0        0.078709      0.001028         0.004277        0.000141   \n",
       "1        0.256731      0.002431         0.012004        0.000301   \n",
       "2        0.783018      0.006946         0.035246        0.001091   \n",
       "3        0.133935      0.002300         0.004715        0.000464   \n",
       "4        0.429455      0.003255         0.011897        0.000111   \n",
       "5        1.279843      0.010347         0.034287        0.001016   \n",
       "6        0.179319      0.005302         0.004639        0.000295   \n",
       "7        0.591407      0.006569         0.012387        0.001073   \n",
       "8        1.793540      0.005098         0.034146        0.000800   \n",
       "9        0.226917      0.002944         0.004440        0.000235   \n",
       "10       0.762174      0.007648         0.011892        0.000146   \n",
       "11       2.305912      0.019248         0.033935        0.000584   \n",
       "12       0.121684      0.001515         0.004759        0.000230   \n",
       "13       0.402926      0.001412         0.013715        0.000379   \n",
       "14       0.165078      0.003275         0.005299        0.000549   \n",
       "15       0.541256      0.009998         0.014269        0.000473   \n",
       "16       0.204627      0.003072         0.004897        0.000152   \n",
       "17       0.685166      0.005392         0.013930        0.000541   \n",
       "\n",
       "   param_max_features param_n_estimators param_bootstrap  \\\n",
       "0                   2                  3             NaN   \n",
       "1                   2                 10             NaN   \n",
       "2                   2                 30             NaN   \n",
       "3                   4                  3             NaN   \n",
       "4                   4                 10             NaN   \n",
       "5                   4                 30             NaN   \n",
       "6                   6                  3             NaN   \n",
       "7                   6                 10             NaN   \n",
       "8                   6                 30             NaN   \n",
       "9                   8                  3             NaN   \n",
       "10                  8                 10             NaN   \n",
       "11                  8                 30             NaN   \n",
       "12                  2                  3           False   \n",
       "13                  2                 10           False   \n",
       "14                  3                  3           False   \n",
       "15                  3                 10           False   \n",
       "16                  4                  3           False   \n",
       "17                  4                 10           False   \n",
       "\n",
       "                                               params  split0_test_score  \\\n",
       "0              {'max_features': 2, 'n_estimators': 3}      -3.837622e+09   \n",
       "1             {'max_features': 2, 'n_estimators': 10}      -3.047771e+09   \n",
       "2             {'max_features': 2, 'n_estimators': 30}      -2.689185e+09   \n",
       "3              {'max_features': 4, 'n_estimators': 3}      -3.730181e+09   \n",
       "4             {'max_features': 4, 'n_estimators': 10}      -2.666283e+09   \n",
       "5             {'max_features': 4, 'n_estimators': 30}      -2.387153e+09   \n",
       "6              {'max_features': 6, 'n_estimators': 3}      -3.119657e+09   \n",
       "7             {'max_features': 6, 'n_estimators': 10}      -2.549663e+09   \n",
       "8             {'max_features': 6, 'n_estimators': 30}      -2.370010e+09   \n",
       "9              {'max_features': 8, 'n_estimators': 3}      -3.353504e+09   \n",
       "10            {'max_features': 8, 'n_estimators': 10}      -2.571970e+09   \n",
       "11            {'max_features': 8, 'n_estimators': 30}      -2.357390e+09   \n",
       "12  {'bootstrap': False, 'max_features': 2, 'n_est...      -3.785816e+09   \n",
       "13  {'bootstrap': False, 'max_features': 2, 'n_est...      -2.810721e+09   \n",
       "14  {'bootstrap': False, 'max_features': 3, 'n_est...      -3.618324e+09   \n",
       "15  {'bootstrap': False, 'max_features': 3, 'n_est...      -2.757999e+09   \n",
       "16  {'bootstrap': False, 'max_features': 4, 'n_est...      -3.134040e+09   \n",
       "17  {'bootstrap': False, 'max_features': 4, 'n_est...      -2.525578e+09   \n",
       "\n",
       "    split1_test_score  ...  mean_test_score  std_test_score  rank_test_score  \\\n",
       "0       -4.147108e+09  ...    -4.053756e+09    1.519591e+08               18   \n",
       "1       -3.254861e+09  ...    -3.094374e+09    1.327062e+08               11   \n",
       "2       -3.021086e+09  ...    -2.849913e+09    1.626875e+08                9   \n",
       "3       -3.786886e+09  ...    -3.716847e+09    1.631510e+08               16   \n",
       "4       -2.784511e+09  ...    -2.781618e+09    1.268607e+08                8   \n",
       "5       -2.588448e+09  ...    -2.537883e+09    1.214614e+08                3   \n",
       "6       -3.586319e+09  ...    -3.441458e+09    1.893056e+08               14   \n",
       "7       -2.782039e+09  ...    -2.704645e+09    1.471569e+08                6   \n",
       "8       -2.583638e+09  ...    -2.514673e+09    1.285080e+08                2   \n",
       "9       -3.348552e+09  ...    -3.348850e+09    1.241939e+08               13   \n",
       "10      -2.718994e+09  ...    -2.674041e+09    1.392777e+08                5   \n",
       "11      -2.546640e+09  ...    -2.468328e+09    1.091662e+08                1   \n",
       "12      -4.166012e+09  ...    -3.955790e+09    1.900964e+08               17   \n",
       "13      -3.107789e+09  ...    -2.987516e+09    1.539234e+08               10   \n",
       "14      -3.441527e+09  ...    -3.536729e+09    7.795057e+07               15   \n",
       "15      -2.851737e+09  ...    -2.779924e+09    6.286720e+07                7   \n",
       "16      -3.559375e+09  ...    -3.305166e+09    1.879165e+08               12   \n",
       "17      -2.710011e+09  ...    -2.601969e+09    1.088048e+08                4   \n",
       "\n",
       "    split0_train_score  split1_train_score  split2_train_score  \\\n",
       "0        -1.064113e+09       -1.105142e+09       -1.116550e+09   \n",
       "1        -5.927175e+08       -5.870952e+08       -5.776964e+08   \n",
       "2        -4.381089e+08       -4.391272e+08       -4.371702e+08   \n",
       "3        -9.865163e+08       -1.012565e+09       -9.169425e+08   \n",
       "4        -5.097115e+08       -5.162820e+08       -4.962893e+08   \n",
       "5        -3.838835e+08       -3.880268e+08       -3.790867e+08   \n",
       "6        -9.245343e+08       -8.886939e+08       -9.353135e+08   \n",
       "7        -4.980344e+08       -5.045869e+08       -4.994664e+08   \n",
       "8        -3.838538e+08       -3.804711e+08       -3.805218e+08   \n",
       "9        -9.228123e+08       -8.553031e+08       -8.603321e+08   \n",
       "10       -4.932416e+08       -4.815238e+08       -4.730979e+08   \n",
       "11       -3.841658e+08       -3.744500e+08       -3.773239e+08   \n",
       "12       -0.000000e+00       -0.000000e+00       -0.000000e+00   \n",
       "13       -6.056477e-02       -0.000000e+00       -0.000000e+00   \n",
       "14       -0.000000e+00       -0.000000e+00       -0.000000e+00   \n",
       "15       -2.089484e+01       -0.000000e+00       -0.000000e+00   \n",
       "16       -0.000000e+00       -0.000000e+00       -0.000000e+00   \n",
       "17       -0.000000e+00       -1.514119e-02       -0.000000e+00   \n",
       "\n",
       "    split3_train_score  split4_train_score  mean_train_score  std_train_score  \n",
       "0        -1.112342e+09       -1.129650e+09     -1.105559e+09     2.220402e+07  \n",
       "1        -5.716332e+08       -5.802501e+08     -5.818785e+08     7.345821e+06  \n",
       "2        -4.376955e+08       -4.452654e+08     -4.394734e+08     2.966320e+06  \n",
       "3        -1.037400e+09       -9.707739e+08     -9.848396e+08     4.084607e+07  \n",
       "4        -5.436192e+08       -5.160297e+08     -5.163863e+08     1.542862e+07  \n",
       "5        -4.040957e+08       -3.845520e+08     -3.879289e+08     8.571233e+06  \n",
       "6        -9.009801e+08       -8.624664e+08     -9.023976e+08     2.591445e+07  \n",
       "7        -4.990325e+08       -5.055542e+08     -5.013349e+08     3.100456e+06  \n",
       "8        -3.856095e+08       -3.901917e+08     -3.841296e+08     3.617057e+06  \n",
       "9        -8.881964e+08       -9.151287e+08     -8.883545e+08     2.750227e+07  \n",
       "10       -5.155367e+08       -4.985555e+08     -4.923911e+08     1.459294e+07  \n",
       "11       -3.882250e+08       -3.810005e+08     -3.810330e+08     4.871017e+06  \n",
       "12       -0.000000e+00       -0.000000e+00      0.000000e+00     0.000000e+00  \n",
       "13       -0.000000e+00       -2.967449e+00     -6.056027e-01     1.181156e+00  \n",
       "14       -0.000000e+00       -6.072840e+01     -1.214568e+01     2.429136e+01  \n",
       "15       -0.000000e+00       -5.465556e+00     -5.272080e+00     8.093117e+00  \n",
       "16       -0.000000e+00       -0.000000e+00      0.000000e+00     0.000000e+00  \n",
       "17       -0.000000e+00       -0.000000e+00     -3.028238e-03     6.056477e-03  \n",
       "\n",
       "[18 rows x 23 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cvresDF = pd.DataFrame(grid_search.cv_results_)\n",
    "cvresDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "answering-outdoors",
   "metadata": {},
   "outputs": [],
   "source": [
    "## 최상의 모델과 오차 분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "pediatric-carrier",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7.33442355e-02, 6.29090705e-02, 4.11437985e-02, 1.46726854e-02,\n",
       "       1.41064835e-02, 1.48742809e-02, 1.42575993e-02, 3.66158981e-01,\n",
       "       5.64191792e-02, 1.08792957e-01, 5.33510773e-02, 1.03114883e-02,\n",
       "       1.64780994e-01, 6.02803867e-05, 1.96041560e-03, 2.85647464e-03])"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importances = grid_search.best_estimator_.feature_importances_\n",
    "feature_importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "caroline-fifty",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.36615898061813423, 'median_income'),\n",
       " (0.16478099356159054, 'INLAND'),\n",
       " (0.10879295677551575, 'pop_per_hhold'),\n",
       " (0.07334423551601243, 'longitude'),\n",
       " (0.06290907048262032, 'latitude'),\n",
       " (0.056419179181954014, 'rooms_per_hhold'),\n",
       " (0.053351077347675815, 'bedrooms_per_room'),\n",
       " (0.04114379847872964, 'housing_median_age'),\n",
       " (0.014874280890402769, 'population'),\n",
       " (0.014672685420543239, 'total_rooms'),\n",
       " (0.014257599323407808, 'households'),\n",
       " (0.014106483453584104, 'total_bedrooms'),\n",
       " (0.010311488326303788, '<1H OCEAN'),\n",
       " (0.0028564746373201584, 'NEAR OCEAN'),\n",
       " (0.0019604155994780706, 'NEAR BAY'),\n",
       " (6.0280386727366e-05, 'ISLAND')]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extra_attribs = [\"rooms_per_hhold\", \"pop_per_hhold\", \"bedrooms_per_room\"]\n",
    "#cat_encoder = cat_pipeline.named_steps[\"cat_encoder\"] # 예전 방식\n",
    "cat_encoder = full_pipeline.named_transformers_[\"cat\"]\n",
    "cat_one_hot_attribs = list(cat_encoder.categories_[0])\n",
    "attributes = num_attribs + extra_attribs + cat_one_hot_attribs\n",
    "sorted(zip(feature_importances, attributes), reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "bright-anthropology",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_model = grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "lovely-substance",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = strat_test_set.drop(\"median_house_value\", axis=1)\n",
    "y_test = strat_test_set[\"median_house_value\"].copy()\n",
    "\n",
    "X_test_prepared = full_pipeline.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "elder-wilderness",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_predictions = final_model.predict(X_test_prepared)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "small-antique",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47730.22690385927"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_mse = mean_squared_error(y_test, final_predictions)\n",
    "final_rmse = np.sqrt(final_mse)\n",
    "\n",
    "final_rmse\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "insured-pillow",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([45685.10470776, 49691.25001878])"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy import stats\n",
    "\n",
    "confidence = 0.95\n",
    "squared_errors = (final_predictions - y_test) ** 2\n",
    "np.sqrt(stats.t.interval(confidence, len(squared_errors) - 1,\n",
    "                         loc=squared_errors.mean(),\n",
    "                         scale=stats.sem(squared_errors)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "operating-piano",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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