Glucose_Regression.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.6"},"colab":{"name":"Glucose_Regression.ipynb","provenance":[{"file_id":"1JUze--w40ksx6UQxZMU5LM_WEa3RiVx6","timestamp":1625233838864}],"toc_visible":true}},"cells":[{"cell_type":"markdown","metadata":{"id":"Fq8SUgQFXG8L"},"source":["# **Glucose Regression**\n","\n"]},{"cell_type":"markdown","metadata":{"id":"MOG6rYfmXckI"},"source":["### Google Colab Functions"]},{"cell_type":"markdown","metadata":{"id":"IYtWMzOvLQ3s"},"source":["#### Prevent random disconnects\n","\n","This cell runs JS code to automatic reconnect to runtime."]},{"cell_type":"markdown","metadata":{"id":"ado2pzmNswm3"},"source":[""]},{"cell_type":"markdown","metadata":{"id":"CD2O1fbeYpRc"},"source":["Plots I can work on :\n","\n","\n","1.   Relationship between features and glyhb - done\n","2.   Distribution of data - done \n","3.   Lasso feature selection -done\n","\n"]},{"cell_type":"code","metadata":{"id":"jtClEMAMLVHw","colab":{"base_uri":"https://localhost:8080/","height":35},"executionInfo":{"status":"ok","timestamp":1625477666568,"user_tz":-330,"elapsed":813,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"289bf48f-8557-4e5c-b956-0722dbe5d1aa"},"source":["import IPython\n","from google.colab import output\n","\n","display(IPython.display.Javascript('''\n"," function ClickConnect(){\n","   btn = document.querySelector(\"colab-connect-button\")\n","   if (btn != null){\n","     console.log(\"Click colab-connect-button\"); \n","     btn.click() \n","     }\n","   \n","   btn = document.getElementById('ok')\n","   if (btn != null){\n","     console.log(\"Click reconnect\"); \n","     btn.click() \n","     }\n","  }\n","  \n","setInterval(ClickConnect,60000)\n","'''))\n","\n","print(\"Done.\")"],"execution_count":1,"outputs":[{"output_type":"display_data","data":{"application/javascript":["\n"," function ClickConnect(){\n","   btn = document.querySelector(\"colab-connect-button\")\n","   if (btn != null){\n","     console.log(\"Click colab-connect-button\"); \n","     btn.click() \n","     }\n","   \n","   btn = document.getElementById('ok')\n","   if (btn != null){\n","     console.log(\"Click reconnect\"); \n","     btn.click() \n","     }\n","  }\n","  \n","setInterval(ClickConnect,60000)\n"],"text/plain":["<IPython.core.display.Javascript object>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Done.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"A-SZElzHXpWi","executionInfo":{"status":"ok","timestamp":1625477689530,"user_tz":-330,"elapsed":22980,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6efbab48-5ea4-44cd-ba93-d42eabe2db81"},"source":["from google.colab import drive\n","drive.mount('/gdrive')"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Mounted at /gdrive\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"JSEdsyEHW-fx"},"source":["# Libraries Used"]},{"cell_type":"code","metadata":{"id":"vev5Bdn3W-f0","executionInfo":{"status":"ok","timestamp":1625477690330,"user_tz":-330,"elapsed":811,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Imports\n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import KFold\n","from sklearn.model_selection import cross_val_score\n","from sklearn.metrics import fbeta_score, make_scorer\n","from scipy.stats import norm\n"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"id":"7awZBWvlW-f1","executionInfo":{"status":"ok","timestamp":1625483267349,"user_tz":-330,"elapsed":787,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Importing Dataset into Notebook\n","dataset =  pd.read_csv(\"/gdrive/MyDrive/Diabetes.csv\")"],"execution_count":113,"outputs":[]},{"cell_type":"code","metadata":{"id":"q65TLvdgOvQe","executionInfo":{"status":"ok","timestamp":1625477691936,"user_tz":-330,"elapsed":36,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":[""],"execution_count":4,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"q7rC76V2OTZh"},"source":["\n","# Data Analysis and Data Cleaning\n","\n","After importing the data, a simple analysis of the data is done."]},{"cell_type":"code","metadata":{"id":"YFnZyi2feJ_h","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477691937,"user_tz":-330,"elapsed":36,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"53e38fd2-66f7-4ab4-d556-6debfc0ca065"},"source":["dataset.info()"],"execution_count":5,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 403 entries, 0 to 402\n","Data columns (total 19 columns):\n"," #   Column    Non-Null Count  Dtype  \n","---  ------    --------------  -----  \n"," 0   id        403 non-null    int64  \n"," 1   chol      402 non-null    float64\n"," 2   stab.glu  403 non-null    int64  \n"," 3   hdl       402 non-null    float64\n"," 4   ratio     402 non-null    float64\n"," 5   glyhb     390 non-null    float64\n"," 6   location  403 non-null    object \n"," 7   age       403 non-null    int64  \n"," 8   gender    403 non-null    object \n"," 9   height    398 non-null    float64\n"," 10  weight    402 non-null    float64\n"," 11  frame     391 non-null    object \n"," 12  bp.1s     398 non-null    float64\n"," 13  bp.1d     398 non-null    float64\n"," 14  bp.2s     141 non-null    float64\n"," 15  bp.2d     141 non-null    float64\n"," 16  waist     401 non-null    float64\n"," 17  hip       401 non-null    float64\n"," 18  time.ppn  400 non-null    float64\n","dtypes: float64(13), int64(3), object(3)\n","memory usage: 59.9+ KB\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"KcZxlCghe181"},"source":["Since there are different numbers of data present in each features, We should check for NULL values."]},{"cell_type":"markdown","metadata":{"id":"8JvEoJlVW-f1"},"source":["### Check For The Null Values\n"]},{"cell_type":"code","metadata":{"id":"_vG1MiSGW-f2","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477691937,"user_tz":-330,"elapsed":33,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"52ea3baf-fce2-4e07-a178-39d981ab4ec3"},"source":["dataset.isnull().sum()"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["id            0\n","chol          1\n","stab.glu      0\n","hdl           1\n","ratio         1\n","glyhb        13\n","location      0\n","age           0\n","gender        0\n","height        5\n","weight        1\n","frame        12\n","bp.1s         5\n","bp.1d         5\n","bp.2s       262\n","bp.2d       262\n","waist         2\n","hip           2\n","time.ppn      3\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"code","metadata":{"id":"mBSrfYBdW-f3","colab":{"base_uri":"https://localhost:8080/","height":225},"executionInfo":{"status":"ok","timestamp":1625477691938,"user_tz":-330,"elapsed":28,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"e0a53311-92cf-40be-b4b9-df47a98e6675"},"source":["# Lets view the data\n","dataset.head()"],"execution_count":7,"outputs":[{"output_type":"execute_result","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>id</th>\n","      <th>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>glyhb</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>bp.2s</th>\n","      <th>bp.2d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1000</td>\n","      <td>203.0</td>\n","      <td>82</td>\n","      <td>56.0</td>\n","      <td>3.6</td>\n","      <td>4.31</td>\n","      <td>Buckingham</td>\n","      <td>46</td>\n","      <td>female</td>\n","      <td>62.0</td>\n","      <td>121.0</td>\n","      <td>medium</td>\n","      <td>118.0</td>\n","      <td>59.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>29.0</td>\n","      <td>38.0</td>\n","      <td>720.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1001</td>\n","      <td>165.0</td>\n","      <td>97</td>\n","      <td>24.0</td>\n","      <td>6.9</td>\n","      <td>4.44</td>\n","      <td>Buckingham</td>\n","      <td>29</td>\n","      <td>female</td>\n","      <td>64.0</td>\n","      <td>218.0</td>\n","      <td>large</td>\n","      <td>112.0</td>\n","      <td>68.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>46.0</td>\n","      <td>48.0</td>\n","      <td>360.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1002</td>\n","      <td>228.0</td>\n","      <td>92</td>\n","      <td>37.0</td>\n","      <td>6.2</td>\n","      <td>4.64</td>\n","      <td>Buckingham</td>\n","      <td>58</td>\n","      <td>female</td>\n","      <td>61.0</td>\n","      <td>256.0</td>\n","      <td>large</td>\n","      <td>190.0</td>\n","      <td>92.0</td>\n","      <td>185.0</td>\n","      <td>92.0</td>\n","      <td>49.0</td>\n","      <td>57.0</td>\n","      <td>180.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1003</td>\n","      <td>78.0</td>\n","      <td>93</td>\n","      <td>12.0</td>\n","      <td>6.5</td>\n","      <td>4.63</td>\n","      <td>Buckingham</td>\n","      <td>67</td>\n","      <td>male</td>\n","      <td>67.0</td>\n","      <td>119.0</td>\n","      <td>large</td>\n","      <td>110.0</td>\n","      <td>50.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>33.0</td>\n","      <td>38.0</td>\n","      <td>480.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1005</td>\n","      <td>249.0</td>\n","      <td>90</td>\n","      <td>28.0</td>\n","      <td>8.9</td>\n","      <td>7.72</td>\n","      <td>Buckingham</td>\n","      <td>64</td>\n","      <td>male</td>\n","      <td>68.0</td>\n","      <td>183.0</td>\n","      <td>medium</td>\n","      <td>138.0</td>\n","      <td>80.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>44.0</td>\n","      <td>41.0</td>\n","      <td>300.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["     id   chol  stab.glu   hdl  ratio  ...  bp.2s bp.2d  waist   hip  time.ppn\n","0  1000  203.0        82  56.0    3.6  ...    NaN   NaN   29.0  38.0     720.0\n","1  1001  165.0        97  24.0    6.9  ...    NaN   NaN   46.0  48.0     360.0\n","2  1002  228.0        92  37.0    6.2  ...  185.0  92.0   49.0  57.0     180.0\n","3  1003   78.0        93  12.0    6.5  ...    NaN   NaN   33.0  38.0     480.0\n","4  1005  249.0        90  28.0    8.9  ...    NaN   NaN   44.0  41.0     300.0\n","\n","[5 rows x 19 columns]"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"markdown","metadata":{"id":"1UiZ5Uzkfkgo"},"source":["Dropping the column \"id\" since it consists of unique value."]},{"cell_type":"code","metadata":{"id":"0zlRb8z4W-f4","executionInfo":{"status":"ok","timestamp":1625477691938,"user_tz":-330,"elapsed":27,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset.drop(columns = \"id\",inplace=True)"],"execution_count":8,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"kJdcb7O2W-f4"},"source":["### Checking Dustribution"]},{"cell_type":"code","metadata":{"id":"D2enNFEkW-f4","colab":{"base_uri":"https://localhost:8080/","height":483},"executionInfo":{"status":"ok","timestamp":1625477691939,"user_tz":-330,"elapsed":27,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"51e56876-a9f6-480c-e87f-cf9f6a37ad8a"},"source":["plt.figure(figsize=(8,8))\n","plt.plot(dataset[\"time.ppn\"])\n","plt.show()"],"execution_count":9,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x576 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"ls6YqAd1W-f5"},"source":["### Filling NAN Values as median of that columns"]},{"cell_type":"code","metadata":{"id":"iJ28c1w8kuRi","colab":{"base_uri":"https://localhost:8080/","height":612},"executionInfo":{"status":"ok","timestamp":1625477691941,"user_tz":-330,"elapsed":28,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"049c262f-e6ed-4f37-ac5f-f111c4c5dcf1"},"source":["# Lets check the percentage of NaN values in our features\n","percent_missing = dataset.isnull().sum() * 100 / len(dataset)\n","missing_value_df = pd.DataFrame({'column_name': dataset.columns,\n","                                 'percent_missing': percent_missing})\n","missing_value_df"],"execution_count":10,"outputs":[{"output_type":"execute_result","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>column_name</th>\n","      <th>percent_missing</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>chol</th>\n","      <td>chol</td>\n","      <td>0.248139</td>\n","    </tr>\n","    <tr>\n","      <th>stab.glu</th>\n","      <td>stab.glu</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>hdl</th>\n","      <td>hdl</td>\n","      <td>0.248139</td>\n","    </tr>\n","    <tr>\n","      <th>ratio</th>\n","      <td>ratio</td>\n","      <td>0.248139</td>\n","    </tr>\n","    <tr>\n","      <th>glyhb</th>\n","      <td>glyhb</td>\n","      <td>3.225806</td>\n","    </tr>\n","    <tr>\n","      <th>location</th>\n","      <td>location</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>age</th>\n","      <td>age</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>gender</th>\n","      <td>gender</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>height</th>\n","      <td>height</td>\n","      <td>1.240695</td>\n","    </tr>\n","    <tr>\n","      <th>weight</th>\n","      <td>weight</td>\n","      <td>0.248139</td>\n","    </tr>\n","    <tr>\n","      <th>frame</th>\n","      <td>frame</td>\n","      <td>2.977667</td>\n","    </tr>\n","    <tr>\n","      <th>bp.1s</th>\n","      <td>bp.1s</td>\n","      <td>1.240695</td>\n","    </tr>\n","    <tr>\n","      <th>bp.1d</th>\n","      <td>bp.1d</td>\n","      <td>1.240695</td>\n","    </tr>\n","    <tr>\n","      <th>bp.2s</th>\n","      <td>bp.2s</td>\n","      <td>65.012407</td>\n","    </tr>\n","    <tr>\n","      <th>bp.2d</th>\n","      <td>bp.2d</td>\n","      <td>65.012407</td>\n","    </tr>\n","    <tr>\n","      <th>waist</th>\n","      <td>waist</td>\n","      <td>0.496278</td>\n","    </tr>\n","    <tr>\n","      <th>hip</th>\n","      <td>hip</td>\n","      <td>0.496278</td>\n","    </tr>\n","    <tr>\n","      <th>time.ppn</th>\n","      <td>time.ppn</td>\n","      <td>0.744417</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["         column_name  percent_missing\n","chol            chol         0.248139\n","stab.glu    stab.glu         0.000000\n","hdl              hdl         0.248139\n","ratio          ratio         0.248139\n","glyhb          glyhb         3.225806\n","location    location         0.000000\n","age              age         0.000000\n","gender        gender         0.000000\n","height        height         1.240695\n","weight        weight         0.248139\n","frame          frame         2.977667\n","bp.1s          bp.1s         1.240695\n","bp.1d          bp.1d         1.240695\n","bp.2s          bp.2s        65.012407\n","bp.2d          bp.2d        65.012407\n","waist          waist         0.496278\n","hip              hip         0.496278\n","time.ppn    time.ppn         0.744417"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"markdown","metadata":{"id":"PLPI8ySOmuV4"},"source":["We can clearly see that the coulumns **bp.2s** and **bp.2d** have over ***65%*** of NaN values in it,thus rendering the column useless. Therefore we will drop these 2 columns too."]},{"cell_type":"code","metadata":{"id":"qmlXNBG1W-f5","executionInfo":{"status":"ok","timestamp":1625477691942,"user_tz":-330,"elapsed":27,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset[\"weight\"].fillna(dataset[\"weight\"].median(),inplace=True)\n","dataset[\"height\"].fillna(dataset[\"height\"].median(),inplace=True)\n","dataset[\"hdl\"].fillna(dataset[\"hdl\"].median(),inplace=True)\n","dataset[\"ratio\"].fillna(dataset[\"ratio\"].median(),inplace=True)\n","dataset[\"bp.1s\"].fillna(dataset[\"bp.1s\"].median(),inplace=True)\n","dataset[\"bp.1d\"].fillna(dataset[\"bp.1d\"].median(),inplace=True)\n","dataset[\"chol\"].fillna(dataset[\"chol\"].median(),inplace=True)\n","dataset[\"waist\"].fillna(dataset[\"waist\"].median(),inplace=True)\n","dataset[\"hip\"].fillna(dataset[\"hip\"].median(),inplace=True)\n","dataset[\"time.ppn\"].fillna(dataset[\"time.ppn\"].median(),inplace=True)\n","dataset[\"frame\"].fillna(\"medium\",inplace=True)\n","dataset[\"glyhb\"].fillna(dataset[\"glyhb\"].median(),inplace=True)\n"],"execution_count":11,"outputs":[]},{"cell_type":"code","metadata":{"id":"Cl1_5_55ZrOD","executionInfo":{"status":"ok","timestamp":1625477691942,"user_tz":-330,"elapsed":26,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Deleting bp.2s , bp.2d Too many NAN values so dropping values\n","dataset.drop(columns=[\"bp.2s\",\"bp.2d\"],inplace=True)"],"execution_count":12,"outputs":[]},{"cell_type":"code","metadata":{"scrolled":true,"id":"S39mvZEVW-f8","colab":{"base_uri":"https://localhost:8080/","height":442},"executionInfo":{"status":"ok","timestamp":1625477691943,"user_tz":-330,"elapsed":27,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"17691f46-9f5f-4f2d-bbc6-089a758cbb10"},"source":["dataset"],"execution_count":13,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>glyhb</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>203.0</td>\n","      <td>82</td>\n","      <td>56.0</td>\n","      <td>3.6</td>\n","      <td>4.310000</td>\n","      <td>Buckingham</td>\n","      <td>46</td>\n","      <td>female</td>\n","      <td>62.0</td>\n","      <td>121.0</td>\n","      <td>medium</td>\n","      <td>118.0</td>\n","      <td>59.0</td>\n","      <td>29.0</td>\n","      <td>38.0</td>\n","      <td>720.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>165.0</td>\n","      <td>97</td>\n","      <td>24.0</td>\n","      <td>6.9</td>\n","      <td>4.440000</td>\n","      <td>Buckingham</td>\n","      <td>29</td>\n","      <td>female</td>\n","      <td>64.0</td>\n","      <td>218.0</td>\n","      <td>large</td>\n","      <td>112.0</td>\n","      <td>68.0</td>\n","      <td>46.0</td>\n","      <td>48.0</td>\n","      <td>360.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>228.0</td>\n","      <td>92</td>\n","      <td>37.0</td>\n","      <td>6.2</td>\n","      <td>4.640000</td>\n","      <td>Buckingham</td>\n","      <td>58</td>\n","      <td>female</td>\n","      <td>61.0</td>\n","      <td>256.0</td>\n","      <td>large</td>\n","      <td>190.0</td>\n","      <td>92.0</td>\n","      <td>49.0</td>\n","      <td>57.0</td>\n","      <td>180.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>78.0</td>\n","      <td>93</td>\n","      <td>12.0</td>\n","      <td>6.5</td>\n","      <td>4.630000</td>\n","      <td>Buckingham</td>\n","      <td>67</td>\n","      <td>male</td>\n","      <td>67.0</td>\n","      <td>119.0</td>\n","      <td>large</td>\n","      <td>110.0</td>\n","      <td>50.0</td>\n","      <td>33.0</td>\n","      <td>38.0</td>\n","      <td>480.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>249.0</td>\n","      <td>90</td>\n","      <td>28.0</td>\n","      <td>8.9</td>\n","      <td>7.720000</td>\n","      <td>Buckingham</td>\n","      <td>64</td>\n","      <td>male</td>\n","      <td>68.0</td>\n","      <td>183.0</td>\n","      <td>medium</td>\n","      <td>138.0</td>\n","      <td>80.0</td>\n","      <td>44.0</td>\n","      <td>41.0</td>\n","      <td>300.0</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","      <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>398</th>\n","      <td>296.0</td>\n","      <td>369</td>\n","      <td>46.0</td>\n","      <td>6.4</td>\n","      <td>16.110001</td>\n","      <td>Louisa</td>\n","      <td>53</td>\n","      <td>male</td>\n","      <td>69.0</td>\n","      <td>173.0</td>\n","      <td>medium</td>\n","      <td>138.0</td>\n","      <td>94.0</td>\n","      <td>35.0</td>\n","      <td>39.0</td>\n","      <td>210.0</td>\n","    </tr>\n","    <tr>\n","      <th>399</th>\n","      <td>284.0</td>\n","      <td>89</td>\n","      <td>54.0</td>\n","      <td>5.3</td>\n","      <td>4.390000</td>\n","      <td>Louisa</td>\n","      <td>51</td>\n","      <td>female</td>\n","      <td>63.0</td>\n","      <td>154.0</td>\n","      <td>medium</td>\n","      <td>140.0</td>\n","      <td>100.0</td>\n","      <td>32.0</td>\n","      <td>43.0</td>\n","      <td>180.0</td>\n","    </tr>\n","    <tr>\n","      <th>400</th>\n","      <td>194.0</td>\n","      <td>269</td>\n","      <td>38.0</td>\n","      <td>5.1</td>\n","      <td>13.630000</td>\n","      <td>Louisa</td>\n","      <td>29</td>\n","      <td>female</td>\n","      <td>69.0</td>\n","      <td>167.0</td>\n","      <td>small</td>\n","      <td>120.0</td>\n","      <td>70.0</td>\n","      <td>33.0</td>\n","      <td>40.0</td>\n","      <td>20.0</td>\n","    </tr>\n","    <tr>\n","      <th>401</th>\n","      <td>199.0</td>\n","      <td>76</td>\n","      <td>52.0</td>\n","      <td>3.8</td>\n","      <td>4.490000</td>\n","      <td>Louisa</td>\n","      <td>41</td>\n","      <td>female</td>\n","      <td>63.0</td>\n","      <td>197.0</td>\n","      <td>medium</td>\n","      <td>120.0</td>\n","      <td>78.0</td>\n","      <td>41.0</td>\n","      <td>48.0</td>\n","      <td>255.0</td>\n","    </tr>\n","    <tr>\n","      <th>402</th>\n","      <td>159.0</td>\n","      <td>88</td>\n","      <td>79.0</td>\n","      <td>2.0</td>\n","      <td>4.840000</td>\n","      <td>Louisa</td>\n","      <td>68</td>\n","      <td>female</td>\n","      <td>64.0</td>\n","      <td>220.0</td>\n","      <td>medium</td>\n","      <td>100.0</td>\n","      <td>72.0</td>\n","      <td>49.0</td>\n","      <td>58.0</td>\n","      <td>900.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>403 rows × 16 columns</p>\n","</div>"],"text/plain":["      chol  stab.glu   hdl  ratio  ...  bp.1d waist   hip time.ppn\n","0    203.0        82  56.0    3.6  ...   59.0  29.0  38.0    720.0\n","1    165.0        97  24.0    6.9  ...   68.0  46.0  48.0    360.0\n","2    228.0        92  37.0    6.2  ...   92.0  49.0  57.0    180.0\n","3     78.0        93  12.0    6.5  ...   50.0  33.0  38.0    480.0\n","4    249.0        90  28.0    8.9  ...   80.0  44.0  41.0    300.0\n","..     ...       ...   ...    ...  ...    ...   ...   ...      ...\n","398  296.0       369  46.0    6.4  ...   94.0  35.0  39.0    210.0\n","399  284.0        89  54.0    5.3  ...  100.0  32.0  43.0    180.0\n","400  194.0       269  38.0    5.1  ...   70.0  33.0  40.0     20.0\n","401  199.0        76  52.0    3.8  ...   78.0  41.0  48.0    255.0\n","402  159.0        88  79.0    2.0  ...   72.0  49.0  58.0    900.0\n","\n","[403 rows x 16 columns]"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"id":"LjKz6WIhW-f9","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477691943,"user_tz":-330,"elapsed":26,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"5c2c879b-5609-41d8-a943-17bdb60a9edb"},"source":["dataset.isnull().sum()"],"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/plain":["chol        0\n","stab.glu    0\n","hdl         0\n","ratio       0\n","glyhb       0\n","location    0\n","age         0\n","gender      0\n","height      0\n","weight      0\n","frame       0\n","bp.1s       0\n","bp.1d       0\n","waist       0\n","hip         0\n","time.ppn    0\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":14}]},{"cell_type":"markdown","metadata":{"id":"T9MMKb9AZ1JJ"},"source":["Now We are NULL free!"]},{"cell_type":"markdown","metadata":{"id":"YSYJMy_dW-f-"},"source":[" Standardisation of all the columns as there must not be much diffrence in column values Very important for distance based values not much of a effect on trees based values"]},{"cell_type":"code","metadata":{"id":"-7amaJFJW-f-","executionInfo":{"status":"ok","timestamp":1625477691943,"user_tz":-330,"elapsed":20,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset[\"bp.1s\"] = np.log(dataset[\"bp.1s\"]) \n","dataset[\"hdl\"] = np.log(dataset[\"hdl\"]) \n","dataset[\"height\"] = np.log(dataset[\"height\"]) \n","dataset[\"age\"] = np.log(dataset[\"age\"]) \n","dataset[\"bp.1d\"] = np.log(dataset[\"bp.1d\"]) \n","dataset[\"ratio\"] = np.log(dataset[\"ratio\"]) \n","dataset[\"stab.glu\"] = np.sqrt(dataset[\"stab.glu\"])"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"id":"bVNczEFxW-f_","executionInfo":{"status":"ok","timestamp":1625477691944,"user_tz":-330,"elapsed":20,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.preprocessing import StandardScaler,MinMaxScaler,RobustScaler\n","sc = StandardScaler()\n","dataset[\"stab.glu\"] =  sc.fit_transform(dataset[\"stab.glu\"].values.reshape(403,1))\n","dataset['hdl'] = sc.fit_transform(dataset[\"hdl\"].values.reshape(403,1))\n","dataset[\"ratio\"] = sc.fit_transform(dataset[\"ratio\"].values.reshape(403,1))\n","dataset['waist'] = sc.fit_transform(dataset[\"waist\"].values.reshape(403,1))\n","dataset[\"weight\"] = sc.fit_transform(dataset[\"weight\"].values.reshape(403,1))\n","dataset[\"chol\"] = sc.fit_transform(dataset[\"chol\"].values.reshape(403,1))\n","dataset[\"bp.1s\"] = sc.fit_transform(dataset[\"bp.1s\"].values.reshape(403,1))\n","dataset[\"bp.1d\"] = sc.fit_transform(dataset[\"bp.1d\"].values.reshape(403,1))\n","dataset[\"time.ppn\"] = sc.fit_transform(dataset[\"time.ppn\"].values.reshape(403,1))\n","dataset[\"hip\"] = sc.fit_transform(dataset[\"hip\"].values.reshape(403,1))\n","dataset[\"age\"] = sc.fit_transform(dataset[\"age\"].values.reshape(403,1))\n","dataset[\"height\"] = sc.fit_transform(dataset[\"height\"].values.reshape(403,1))"],"execution_count":16,"outputs":[]},{"cell_type":"code","metadata":{"id":"hMffn-uvW-gC","colab":{"base_uri":"https://localhost:8080/","height":442},"executionInfo":{"status":"ok","timestamp":1625477692894,"user_tz":-330,"elapsed":21,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"97912fb1-4cec-480e-a07d-f125212de0dd"},"source":["dataset"],"execution_count":17,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>glyhb</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>-0.109082</td>\n","      <td>-0.498023</td>\n","      <td>0.485298</td>\n","      <td>-0.476985</td>\n","      <td>4.310000</td>\n","      <td>Buckingham</td>\n","      <td>0.125395</td>\n","      <td>female</td>\n","      <td>-1.033326</td>\n","      <td>-1.406006</td>\n","      <td>medium</td>\n","      <td>-0.864244</td>\n","      <td>-2.026457</td>\n","      <td>-1.558395</td>\n","      <td>-0.893303</td>\n","      <td>1.231660</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>-0.966182</td>\n","      <td>-0.123024</td>\n","      <td>-2.111356</td>\n","      <td>1.396400</td>\n","      <td>4.440000</td>\n","      <td>Buckingham</td>\n","      <td>-1.129342</td>\n","      <td>female</td>\n","      <td>-0.496206</td>\n","      <td>1.004457</td>\n","      <td>large</td>\n","      <td>-1.196269</td>\n","      <td>-1.159206</td>\n","      <td>1.419726</td>\n","      <td>0.880976</td>\n","      <td>0.063298</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.454799</td>\n","      <td>-0.244575</td>\n","      <td>-0.784788</td>\n","      <td>1.088371</td>\n","      <td>4.640000</td>\n","      <td>Buckingham</td>\n","      <td>0.755834</td>\n","      <td>female</td>\n","      <td>-1.308419</td>\n","      <td>1.948762</td>\n","      <td>large</td>\n","      <td>2.166407</td>\n","      <td>0.687334</td>\n","      <td>1.945276</td>\n","      <td>2.477827</td>\n","      <td>-0.520882</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>4.630000</td>\n","      <td>Buckingham</td>\n","      <td>1.148155</td>\n","      <td>male</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>large</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.928460</td>\n","      <td>-0.294119</td>\n","      <td>-1.638941</td>\n","      <td>2.129326</td>\n","      <td>7.720000</td>\n","      <td>Buckingham</td>\n","      <td>1.023565</td>\n","      <td>male</td>\n","      <td>0.529432</td>\n","      <td>0.134703</td>\n","      <td>medium</td>\n","      <td>0.131908</td>\n","      <td>-0.166428</td>\n","      <td>1.069359</td>\n","      <td>-0.361020</td>\n","      <td>-0.131429</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","      <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>398</th>\n","      <td>1.988557</td>\n","      <td>4.300799</td>\n","      <td>-0.117546</td>\n","      <td>1.179792</td>\n","      <td>16.110001</td>\n","      <td>Louisa</td>\n","      <td>0.510647</td>\n","      <td>male</td>\n","      <td>0.776412</td>\n","      <td>-0.113799</td>\n","      <td>medium</td>\n","      <td>0.131908</td>\n","      <td>0.818708</td>\n","      <td>-0.507293</td>\n","      <td>-0.715875</td>\n","      <td>-0.423519</td>\n","    </tr>\n","    <tr>\n","      <th>399</th>\n","      <td>1.717894</td>\n","      <td>-0.319097</td>\n","      <td>0.373845</td>\n","      <td>0.636739</td>\n","      <td>4.390000</td>\n","      <td>Louisa</td>\n","      <td>0.406029</td>\n","      <td>female</td>\n","      <td>-0.762634</td>\n","      <td>-0.585951</td>\n","      <td>medium</td>\n","      <td>0.223454</td>\n","      <td>1.196686</td>\n","      <td>-1.032844</td>\n","      <td>-0.006164</td>\n","      <td>-0.520882</td>\n","    </tr>\n","    <tr>\n","      <th>400</th>\n","      <td>-0.312080</td>\n","      <td>2.973653</td>\n","      <td>-0.703059</td>\n","      <td>0.525974</td>\n","      <td>13.630000</td>\n","      <td>Louisa</td>\n","      <td>-1.129342</td>\n","      <td>female</td>\n","      <td>0.776412</td>\n","      <td>-0.262900</td>\n","      <td>small</td>\n","      <td>-0.757310</td>\n","      <td>-0.982130</td>\n","      <td>-0.857660</td>\n","      <td>-0.538447</td>\n","      <td>-1.040154</td>\n","    </tr>\n","    <tr>\n","      <th>401</th>\n","      <td>-0.199303</td>\n","      <td>-0.657568</td>\n","      <td>0.258185</td>\n","      <td>-0.321297</td>\n","      <td>4.490000</td>\n","      <td>Louisa</td>\n","      <td>-0.187563</td>\n","      <td>female</td>\n","      <td>-0.762634</td>\n","      <td>0.482604</td>\n","      <td>medium</td>\n","      <td>-0.757310</td>\n","      <td>-0.321087</td>\n","      <td>0.543808</td>\n","      <td>0.880976</td>\n","      <td>-0.277474</td>\n","    </tr>\n","    <tr>\n","      <th>402</th>\n","      <td>-1.101514</td>\n","      <td>-0.344215</td>\n","      <td>1.539825</td>\n","      <td>-2.169534</td>\n","      <td>4.840000</td>\n","      <td>Louisa</td>\n","      <td>1.188448</td>\n","      <td>female</td>\n","      <td>-0.496206</td>\n","      <td>1.054157</td>\n","      <td>medium</td>\n","      <td>-1.917309</td>\n","      <td>-0.810043</td>\n","      <td>1.945276</td>\n","      <td>2.655254</td>\n","      <td>1.815840</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>403 rows × 16 columns</p>\n","</div>"],"text/plain":["         chol  stab.glu       hdl  ...     waist       hip  time.ppn\n","0   -0.109082 -0.498023  0.485298  ... -1.558395 -0.893303  1.231660\n","1   -0.966182 -0.123024 -2.111356  ...  1.419726  0.880976  0.063298\n","2    0.454799 -0.244575 -0.784788  ...  1.945276  2.477827 -0.520882\n","3   -2.928491 -0.220006 -4.235595  ... -0.857660 -0.893303  0.452752\n","4    0.928460 -0.294119 -1.638941  ...  1.069359 -0.361020 -0.131429\n","..        ...       ...       ...  ...       ...       ...       ...\n","398  1.988557  4.300799 -0.117546  ... -0.507293 -0.715875 -0.423519\n","399  1.717894 -0.319097  0.373845  ... -1.032844 -0.006164 -0.520882\n","400 -0.312080  2.973653 -0.703059  ... -0.857660 -0.538447 -1.040154\n","401 -0.199303 -0.657568  0.258185  ...  0.543808  0.880976 -0.277474\n","402 -1.101514 -0.344215  1.539825  ...  1.945276  2.655254  1.815840\n","\n","[403 rows x 16 columns]"]},"metadata":{"tags":[]},"execution_count":17}]},{"cell_type":"markdown","metadata":{"id":"0R0m-JL1W-gD"},"source":["### Checking Distribution"]},{"cell_type":"code","metadata":{"id":"wKlEdhRpW-gD","colab":{"base_uri":"https://localhost:8080/","height":316},"executionInfo":{"status":"ok","timestamp":1625477692895,"user_tz":-330,"elapsed":21,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"24cb5d9e-df0e-490b-ea98-6eabde90e864"},"source":["fig,ax = plt.subplots()\n","dataset[\"bp.1d\"].hist(bins=50,color='#A9C5D3',edgecolor='black',grid=False)\n","ax.set_title('Ratio', fontsize=12)\n","ax.set_xlabel('Ratio Distribution', fontsize=12)\n","ax.set_ylabel('Frequency', fontsize=12)"],"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Frequency')"]},"metadata":{"tags":[]},"execution_count":18},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"iusdOVzCW-gE","colab":{"base_uri":"https://localhost:8080/","height":373},"executionInfo":{"status":"ok","timestamp":1625477692895,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6c62f81d-c5b0-4991-ff1c-07c157b5d00c"},"source":["fig,ax = plt.subplots()\n","np.log(dataset[\"ratio\"]).hist(bins=10,color='#A9C5D3',edgecolor='black',grid=False)\n","ax.set_title('Ratio Log', fontsize=12)\n","ax.set_xlabel('Ratio Distribution', fontsize=12)\n","ax.set_ylabel('Frequency', fontsize=12)"],"execution_count":19,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.7/dist-packages/pandas/core/series.py:726: RuntimeWarning: invalid value encountered in log\n","  result = getattr(ufunc, method)(*inputs, **kwargs)\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Frequency')"]},"metadata":{"tags":[]},"execution_count":19},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"Qqi3CGw7W-gE","colab":{"base_uri":"https://localhost:8080/","height":459},"executionInfo":{"status":"ok","timestamp":1625477693865,"user_tz":-330,"elapsed":981,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"95289018-30da-446e-a30c-fc2b2a906f55"},"source":["plt.figure(figsize=(20,10))\n","sns.jointplot(x=dataset[\"ratio\"],y=dataset[\"glyhb\"],kind=\"reg\")\n","plt.show()"],"execution_count":20,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1440x720 with 0 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"8fLENd3y_cU3","colab":{"base_uri":"https://localhost:8080/","height":459},"executionInfo":{"status":"ok","timestamp":1625477695359,"user_tz":-330,"elapsed":1503,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"66e0be1d-b5b3-4fc4-fab1-bc4dff5a58a2"},"source":["## Plot relation ship between glyhb and stab.glu\n","plt.figure(figsize=(20,10))\n","sns.jointplot(x=dataset[\"stab.glu\"],y=dataset[\"glyhb\"],kind=\"reg\")\n","plt.show()"],"execution_count":21,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1440x720 with 0 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"MTDckfieMMMU","colab":{"base_uri":"https://localhost:8080/","height":297},"executionInfo":{"status":"ok","timestamp":1625477695360,"user_tz":-330,"elapsed":39,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"7deb41ff-b9f1-4e80-a46b-5c82807535b6"},"source":["sns.scatterplot(data=dataset, x=dataset['stab.glu'], y=dataset['glyhb'])"],"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"aeTgArxGATs4","colab":{"base_uri":"https://localhost:8080/","height":337},"executionInfo":{"status":"ok","timestamp":1625477695361,"user_tz":-330,"elapsed":37,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"49490b56-6a9e-4edf-fa81-aaf44856159c"},"source":["# Distrubution of stab.glu\n","sns.distplot(dataset['stab.glu']);"],"execution_count":23,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"IJybk-zJAuCO","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695361,"user_tz":-330,"elapsed":33,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"2336273a-6247-4dce-aff5-614902b57785"},"source":["print(\"Skewness: %f\" % dataset['stab.glu'].skew())\n","print(\"Kurtosis: %f\" % dataset['stab.glu'].kurt())"],"execution_count":24,"outputs":[{"output_type":"stream","text":["Skewness: 2.202467\n","Kurtosis: 5.031123\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"oqTN3cgCAjKV"},"source":[""]},{"cell_type":"code","metadata":{"id":"mJ9GhIXfW-gF","executionInfo":{"status":"ok","timestamp":1625477695362,"user_tz":-330,"elapsed":31,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Creating Y \n","y = dataset[\"glyhb\"]\n","dataset.drop(columns=\"glyhb\",inplace=True)"],"execution_count":25,"outputs":[]},{"cell_type":"code","metadata":{"id":"ev0s7HQEO-st","colab":{"base_uri":"https://localhost:8080/","height":442},"executionInfo":{"status":"ok","timestamp":1625477695362,"user_tz":-330,"elapsed":31,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"4143621d-6915-4291-ebf8-ea3571b9482f"},"source":["dataset"],"execution_count":26,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>-0.109082</td>\n","      <td>-0.498023</td>\n","      <td>0.485298</td>\n","      <td>-0.476985</td>\n","      <td>Buckingham</td>\n","      <td>0.125395</td>\n","      <td>female</td>\n","      <td>-1.033326</td>\n","      <td>-1.406006</td>\n","      <td>medium</td>\n","      <td>-0.864244</td>\n","      <td>-2.026457</td>\n","      <td>-1.558395</td>\n","      <td>-0.893303</td>\n","      <td>1.231660</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>-0.966182</td>\n","      <td>-0.123024</td>\n","      <td>-2.111356</td>\n","      <td>1.396400</td>\n","      <td>Buckingham</td>\n","      <td>-1.129342</td>\n","      <td>female</td>\n","      <td>-0.496206</td>\n","      <td>1.004457</td>\n","      <td>large</td>\n","      <td>-1.196269</td>\n","      <td>-1.159206</td>\n","      <td>1.419726</td>\n","      <td>0.880976</td>\n","      <td>0.063298</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.454799</td>\n","      <td>-0.244575</td>\n","      <td>-0.784788</td>\n","      <td>1.088371</td>\n","      <td>Buckingham</td>\n","      <td>0.755834</td>\n","      <td>female</td>\n","      <td>-1.308419</td>\n","      <td>1.948762</td>\n","      <td>large</td>\n","      <td>2.166407</td>\n","      <td>0.687334</td>\n","      <td>1.945276</td>\n","      <td>2.477827</td>\n","      <td>-0.520882</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>Buckingham</td>\n","      <td>1.148155</td>\n","      <td>male</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>large</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.928460</td>\n","      <td>-0.294119</td>\n","      <td>-1.638941</td>\n","      <td>2.129326</td>\n","      <td>Buckingham</td>\n","      <td>1.023565</td>\n","      <td>male</td>\n","      <td>0.529432</td>\n","      <td>0.134703</td>\n","      <td>medium</td>\n","      <td>0.131908</td>\n","      <td>-0.166428</td>\n","      <td>1.069359</td>\n","      <td>-0.361020</td>\n","      <td>-0.131429</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>398</th>\n","      <td>1.988557</td>\n","      <td>4.300799</td>\n","      <td>-0.117546</td>\n","      <td>1.179792</td>\n","      <td>Louisa</td>\n","      <td>0.510647</td>\n","      <td>male</td>\n","      <td>0.776412</td>\n","      <td>-0.113799</td>\n","      <td>medium</td>\n","      <td>0.131908</td>\n","      <td>0.818708</td>\n","      <td>-0.507293</td>\n","      <td>-0.715875</td>\n","      <td>-0.423519</td>\n","    </tr>\n","    <tr>\n","      <th>399</th>\n","      <td>1.717894</td>\n","      <td>-0.319097</td>\n","      <td>0.373845</td>\n","      <td>0.636739</td>\n","      <td>Louisa</td>\n","      <td>0.406029</td>\n","      <td>female</td>\n","      <td>-0.762634</td>\n","      <td>-0.585951</td>\n","      <td>medium</td>\n","      <td>0.223454</td>\n","      <td>1.196686</td>\n","      <td>-1.032844</td>\n","      <td>-0.006164</td>\n","      <td>-0.520882</td>\n","    </tr>\n","    <tr>\n","      <th>400</th>\n","      <td>-0.312080</td>\n","      <td>2.973653</td>\n","      <td>-0.703059</td>\n","      <td>0.525974</td>\n","      <td>Louisa</td>\n","      <td>-1.129342</td>\n","      <td>female</td>\n","      <td>0.776412</td>\n","      <td>-0.262900</td>\n","      <td>small</td>\n","      <td>-0.757310</td>\n","      <td>-0.982130</td>\n","      <td>-0.857660</td>\n","      <td>-0.538447</td>\n","      <td>-1.040154</td>\n","    </tr>\n","    <tr>\n","      <th>401</th>\n","      <td>-0.199303</td>\n","      <td>-0.657568</td>\n","      <td>0.258185</td>\n","      <td>-0.321297</td>\n","      <td>Louisa</td>\n","      <td>-0.187563</td>\n","      <td>female</td>\n","      <td>-0.762634</td>\n","      <td>0.482604</td>\n","      <td>medium</td>\n","      <td>-0.757310</td>\n","      <td>-0.321087</td>\n","      <td>0.543808</td>\n","      <td>0.880976</td>\n","      <td>-0.277474</td>\n","    </tr>\n","    <tr>\n","      <th>402</th>\n","      <td>-1.101514</td>\n","      <td>-0.344215</td>\n","      <td>1.539825</td>\n","      <td>-2.169534</td>\n","      <td>Louisa</td>\n","      <td>1.188448</td>\n","      <td>female</td>\n","      <td>-0.496206</td>\n","      <td>1.054157</td>\n","      <td>medium</td>\n","      <td>-1.917309</td>\n","      <td>-0.810043</td>\n","      <td>1.945276</td>\n","      <td>2.655254</td>\n","      <td>1.815840</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>403 rows × 15 columns</p>\n","</div>"],"text/plain":["         chol  stab.glu       hdl  ...     waist       hip  time.ppn\n","0   -0.109082 -0.498023  0.485298  ... -1.558395 -0.893303  1.231660\n","1   -0.966182 -0.123024 -2.111356  ...  1.419726  0.880976  0.063298\n","2    0.454799 -0.244575 -0.784788  ...  1.945276  2.477827 -0.520882\n","3   -2.928491 -0.220006 -4.235595  ... -0.857660 -0.893303  0.452752\n","4    0.928460 -0.294119 -1.638941  ...  1.069359 -0.361020 -0.131429\n","..        ...       ...       ...  ...       ...       ...       ...\n","398  1.988557  4.300799 -0.117546  ... -0.507293 -0.715875 -0.423519\n","399  1.717894 -0.319097  0.373845  ... -1.032844 -0.006164 -0.520882\n","400 -0.312080  2.973653 -0.703059  ... -0.857660 -0.538447 -1.040154\n","401 -0.199303 -0.657568  0.258185  ...  0.543808  0.880976 -0.277474\n","402 -1.101514 -0.344215  1.539825  ...  1.945276  2.655254  1.815840\n","\n","[403 rows x 15 columns]"]},"metadata":{"tags":[]},"execution_count":26}]},{"cell_type":"markdown","metadata":{"id":"J8VFwWEWW-gF"},"source":["### Splitting train and test values"]},{"cell_type":"code","metadata":{"id":"yDuzbhnmW-gG","executionInfo":{"status":"ok","timestamp":1625477695363,"user_tz":-330,"elapsed":30,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.model_selection import train_test_split\n","x_train,x_test,y_train,y_test = train_test_split(dataset,y,test_size=0.2,random_state=42)"],"execution_count":27,"outputs":[]},{"cell_type":"code","metadata":{"id":"zo1fnudxW-gG","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695363,"user_tz":-330,"elapsed":30,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"81bb40cf-2ef1-41c5-e049-29314dd3eca9"},"source":["x_train.shape,y_train.shape,x_test.shape,y_test.shape"],"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((322, 15), (322,), (81, 15), (81,))"]},"metadata":{"tags":[]},"execution_count":28}]},{"cell_type":"code","metadata":{"id":"VV7LoxvZOt7l","colab":{"base_uri":"https://localhost:8080/","height":442},"executionInfo":{"status":"ok","timestamp":1625477695364,"user_tz":-330,"elapsed":26,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"ce7c4d90-56d8-4b82-ebaa-1c9c6c69d7ff"},"source":["x_train"],"execution_count":29,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>353</th>\n","      <td>-0.041417</td>\n","      <td>-0.472007</td>\n","      <td>1.080314</td>\n","      <td>-1.001985</td>\n","      <td>Louisa</td>\n","      <td>0.458841</td>\n","      <td>male</td>\n","      <td>0.776412</td>\n","      <td>-0.610801</td>\n","      <td>small</td>\n","      <td>0.223454</td>\n","      <td>1.073274</td>\n","      <td>-0.332110</td>\n","      <td>-0.538447</td>\n","      <td>-0.472201</td>\n","    </tr>\n","    <tr>\n","      <th>233</th>\n","      <td>-0.266969</td>\n","      <td>0.290480</td>\n","      <td>0.797224</td>\n","      <td>-0.816145</td>\n","      <td>Louisa</td>\n","      <td>0.352171</td>\n","      <td>male</td>\n","      <td>0.278792</td>\n","      <td>-0.933853</td>\n","      <td>medium</td>\n","      <td>1.679430</td>\n","      <td>1.778906</td>\n","      <td>-0.507293</td>\n","      <td>-1.070731</td>\n","      <td>-0.910336</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>Buckingham</td>\n","      <td>1.148155</td>\n","      <td>male</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>large</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>-0.312080</td>\n","      <td>-0.524198</td>\n","      <td>-0.868755</td>\n","      <td>0.690563</td>\n","      <td>Louisa</td>\n","      <td>-0.541273</td>\n","      <td>male</td>\n","      <td>-0.496206</td>\n","      <td>-1.281755</td>\n","      <td>medium</td>\n","      <td>-1.310909</td>\n","      <td>-0.479763</td>\n","      <td>-1.383211</td>\n","      <td>-1.603015</td>\n","      <td>-0.715609</td>\n","    </tr>\n","    <tr>\n","      <th>131</th>\n","      <td>-0.447411</td>\n","      <td>-0.630551</td>\n","      <td>-0.184903</td>\n","      <td>-0.033104</td>\n","      <td>Louisa</td>\n","      <td>-0.947960</td>\n","      <td>female</td>\n","      <td>0.278792</td>\n","      <td>1.228108</td>\n","      <td>medium</td>\n","      <td>-0.652145</td>\n","      <td>-0.982130</td>\n","      <td>1.594909</td>\n","      <td>1.768115</td>\n","      <td>-0.650700</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>71</th>\n","      <td>-0.988738</td>\n","      <td>-0.394885</td>\n","      <td>-0.545865</td>\n","      <td>-0.102494</td>\n","      <td>Buckingham</td>\n","      <td>-1.759782</td>\n","      <td>female</td>\n","      <td>0.776412</td>\n","      <td>1.675411</td>\n","      <td>large</td>\n","      <td>-0.446889</td>\n","      <td>-0.560674</td>\n","      <td>1.069359</td>\n","      <td>0.703548</td>\n","      <td>0.258025</td>\n","    </tr>\n","    <tr>\n","      <th>106</th>\n","      <td>1.920891</td>\n","      <td>-0.420440</td>\n","      <td>2.072602</td>\n","      <td>-0.907566</td>\n","      <td>Louisa</td>\n","      <td>-0.947960</td>\n","      <td>female</td>\n","      <td>0.278792</td>\n","      <td>0.557155</td>\n","      <td>medium</td>\n","      <td>-1.310909</td>\n","      <td>0.553072</td>\n","      <td>0.543808</td>\n","      <td>-0.183592</td>\n","      <td>-0.326155</td>\n","    </tr>\n","    <tr>\n","      <th>270</th>\n","      <td>-1.372177</td>\n","      <td>-0.394885</td>\n","      <td>-1.043925</td>\n","      <td>0.034653</td>\n","      <td>Buckingham</td>\n","      <td>-0.394224</td>\n","      <td>male</td>\n","      <td>0.776412</td>\n","      <td>0.681405</td>\n","      <td>small</td>\n","      <td>-0.248049</td>\n","      <td>0.947317</td>\n","      <td>0.193441</td>\n","      <td>-0.361020</td>\n","      <td>0.452752</td>\n","    </tr>\n","    <tr>\n","      <th>348</th>\n","      <td>-1.936059</td>\n","      <td>-0.498023</td>\n","      <td>-0.324229</td>\n","      <td>-1.200652</td>\n","      <td>Louisa</td>\n","      <td>-0.541273</td>\n","      <td>female</td>\n","      <td>1.259812</td>\n","      <td>0.134703</td>\n","      <td>medium</td>\n","      <td>-1.310909</td>\n","      <td>-0.166428</td>\n","      <td>0.543808</td>\n","      <td>0.348692</td>\n","      <td>-0.812973</td>\n","    </tr>\n","    <tr>\n","      <th>102</th>\n","      <td>-0.199303</td>\n","      <td>0.610882</td>\n","      <td>0.012883</td>\n","      <td>-0.102494</td>\n","      <td>Louisa</td>\n","      <td>-0.466755</td>\n","      <td>female</td>\n","      <td>-1.308419</td>\n","      <td>0.631705</td>\n","      <td>large</td>\n","      <td>0.039025</td>\n","      <td>0.131616</td>\n","      <td>0.718992</td>\n","      <td>1.413259</td>\n","      <td>-1.072608</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>322 rows × 15 columns</p>\n","</div>"],"text/plain":["         chol  stab.glu       hdl  ...     waist       hip  time.ppn\n","353 -0.041417 -0.472007  1.080314  ... -0.332110 -0.538447 -0.472201\n","233 -0.266969  0.290480  0.797224  ... -0.507293 -1.070731 -0.910336\n","3   -2.928491 -0.220006 -4.235595  ... -0.857660 -0.893303  0.452752\n","18  -0.312080 -0.524198 -0.868755  ... -1.383211 -1.603015 -0.715609\n","131 -0.447411 -0.630551 -0.184903  ...  1.594909  1.768115 -0.650700\n","..        ...       ...       ...  ...       ...       ...       ...\n","71  -0.988738 -0.394885 -0.545865  ...  1.069359  0.703548  0.258025\n","106  1.920891 -0.420440  2.072602  ...  0.543808 -0.183592 -0.326155\n","270 -1.372177 -0.394885 -1.043925  ...  0.193441 -0.361020  0.452752\n","348 -1.936059 -0.498023 -0.324229  ...  0.543808  0.348692 -0.812973\n","102 -0.199303  0.610882  0.012883  ...  0.718992  1.413259 -1.072608\n","\n","[322 rows x 15 columns]"]},"metadata":{"tags":[]},"execution_count":29}]},{"cell_type":"markdown","metadata":{"id":"vsuPAaxzW-gP"},"source":["### Unique Values Preprocessing"]},{"cell_type":"code","metadata":{"id":"T9CM15-QW-gP","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695364,"user_tz":-330,"elapsed":25,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"2451dc74-4b93-4997-fc0c-84bc4af436f8"},"source":["x_train[\"location\"].unique()"],"execution_count":30,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['Louisa', 'Buckingham'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":30}]},{"cell_type":"code","metadata":{"id":"S4PfjMyGW-gQ","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695364,"user_tz":-330,"elapsed":23,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"af097e3f-77e0-4895-81e1-d6a5d20249f6"},"source":["x_train[\"gender\"].unique()"],"execution_count":31,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['male', 'female'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":31}]},{"cell_type":"code","metadata":{"id":"HiY_a9bNW-gQ","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695365,"user_tz":-330,"elapsed":23,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"2b88398e-0e34-42c8-b5b3-a22581ca1b93"},"source":["x_train[\"frame\"].unique()"],"execution_count":32,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['small', 'medium', 'large'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":32}]},{"cell_type":"markdown","metadata":{"id":"JjSiHwA_W-gQ"},"source":["### Label Encoding"]},{"cell_type":"code","metadata":{"id":"6ML6SzxPW-gQ","executionInfo":{"status":"ok","timestamp":1625477695365,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.preprocessing import LabelEncoder"],"execution_count":33,"outputs":[]},{"cell_type":"code","metadata":{"id":"BaeIJZ76W-gQ","executionInfo":{"status":"ok","timestamp":1625477695366,"user_tz":-330,"elapsed":23,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["le = LabelEncoder()"],"execution_count":34,"outputs":[]},{"cell_type":"code","metadata":{"id":"EXPZtCzYW-gR","executionInfo":{"status":"ok","timestamp":1625477695366,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["combine = x_train.append(x_test)"],"execution_count":35,"outputs":[]},{"cell_type":"code","metadata":{"id":"s3hiOMzBW-gR","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477695366,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"91040fe4-6c9b-4a40-ebdc-e6aba5f67ed4"},"source":["combine.shape"],"execution_count":36,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(403, 15)"]},"metadata":{"tags":[]},"execution_count":36}]},{"cell_type":"code","metadata":{"id":"DXrKHLEZW-gR","executionInfo":{"status":"ok","timestamp":1625477695367,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["combine[\"location\"] = le.fit_transform(combine[\"location\"])"],"execution_count":37,"outputs":[]},{"cell_type":"code","metadata":{"id":"EWgzklitW-gR","executionInfo":{"status":"ok","timestamp":1625477695367,"user_tz":-330,"elapsed":21,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["combine[\"gender\"] = le.fit_transform(combine[\"gender\"])"],"execution_count":38,"outputs":[]},{"cell_type":"code","metadata":{"id":"c8p-uqB4W-gS","executionInfo":{"status":"ok","timestamp":1625477695368,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["combine[\"frame\"] = le.fit_transform(combine[\"frame\"])"],"execution_count":39,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"De_QoBtOW-gS"},"source":["### One Hot Encoding"]},{"cell_type":"code","metadata":{"id":"yKUbBDxtW-gS","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1625477696176,"user_tz":-330,"elapsed":829,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"a5f4291c-5a3d-4978-d451-a06e3720690d"},"source":["combine"],"execution_count":40,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>353</th>\n","      <td>-0.041417</td>\n","      <td>-0.472007</td>\n","      <td>1.080314</td>\n","      <td>-1.001985</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>1</td>\n","      <td>0.776412</td>\n","      <td>-0.610801</td>\n","      <td>2</td>\n","      <td>0.223454</td>\n","      <td>1.073274</td>\n","      <td>-0.332110</td>\n","      <td>-0.538447</td>\n","      <td>-0.472201</td>\n","    </tr>\n","    <tr>\n","      <th>233</th>\n","      <td>-0.266969</td>\n","      <td>0.290480</td>\n","      <td>0.797224</td>\n","      <td>-0.816145</td>\n","      <td>1</td>\n","      <td>0.352171</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-0.933853</td>\n","      <td>1</td>\n","      <td>1.679430</td>\n","      <td>1.778906</td>\n","      <td>-0.507293</td>\n","      <td>-1.070731</td>\n","      <td>-0.910336</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>0</td>\n","      <td>1.148155</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>0</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>-0.312080</td>\n","      <td>-0.524198</td>\n","      <td>-0.868755</td>\n","      <td>0.690563</td>\n","      <td>1</td>\n","      <td>-0.541273</td>\n","      <td>1</td>\n","      <td>-0.496206</td>\n","      <td>-1.281755</td>\n","      <td>1</td>\n","      <td>-1.310909</td>\n","      <td>-0.479763</td>\n","      <td>-1.383211</td>\n","      <td>-1.603015</td>\n","      <td>-0.715609</td>\n","    </tr>\n","    <tr>\n","      <th>131</th>\n","      <td>-0.447411</td>\n","      <td>-0.630551</td>\n","      <td>-0.184903</td>\n","      <td>-0.033104</td>\n","      <td>1</td>\n","      <td>-0.947960</td>\n","      <td>0</td>\n","      <td>0.278792</td>\n","      <td>1.228108</td>\n","      <td>1</td>\n","      <td>-0.652145</td>\n","      <td>-0.982130</td>\n","      <td>1.594909</td>\n","      <td>1.768115</td>\n","      <td>-0.650700</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>45</th>\n","      <td>0.793128</td>\n","      <td>-1.369639</td>\n","      <td>0.645228</td>\n","      <td>-0.102494</td>\n","      <td>0</td>\n","      <td>-0.466755</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>1.377209</td>\n","      <td>1</td>\n","      <td>-1.310909</td>\n","      <td>-0.015589</td>\n","      <td>1.945276</td>\n","      <td>2.477827</td>\n","      <td>-0.812973</td>\n","    </tr>\n","    <tr>\n","      <th>90</th>\n","      <td>-1.101514</td>\n","      <td>-0.344215</td>\n","      <td>-0.324229</td>\n","      <td>-0.398089</td>\n","      <td>1</td>\n","      <td>-0.394224</td>\n","      <td>1</td>\n","      <td>0.529432</td>\n","      <td>-0.213199</td>\n","      <td>0</td>\n","      <td>0.131908</td>\n","      <td>-0.243268</td>\n","      <td>-0.682477</td>\n","      <td>-0.538447</td>\n","      <td>1.134296</td>\n","    </tr>\n","    <tr>\n","      <th>248</th>\n","      <td>0.657797</td>\n","      <td>0.356161</td>\n","      <td>-0.184903</td>\n","      <td>0.636739</td>\n","      <td>0</td>\n","      <td>1.381418</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>-0.088949</td>\n","      <td>0</td>\n","      <td>1.152068</td>\n","      <td>-0.560674</td>\n","      <td>0.018257</td>\n","      <td>0.171264</td>\n","      <td>-0.131429</td>\n","    </tr>\n","    <tr>\n","      <th>337</th>\n","      <td>1.199123</td>\n","      <td>-0.028022</td>\n","      <td>1.691196</td>\n","      <td>-0.907566</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>0.507454</td>\n","      <td>1</td>\n","      <td>0.746684</td>\n","      <td>0.687334</td>\n","      <td>0.718992</td>\n","      <td>1.058404</td>\n","      <td>-1.040154</td>\n","    </tr>\n","    <tr>\n","      <th>390</th>\n","      <td>-0.266969</td>\n","      <td>0.399485</td>\n","      <td>1.034911</td>\n","      <td>-1.099606</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>0</td>\n","      <td>-1.033326</td>\n","      <td>-0.759902</td>\n","      <td>1</td>\n","      <td>0.402688</td>\n","      <td>0.818708</td>\n","      <td>-0.682477</td>\n","      <td>-0.183592</td>\n","      <td>0.452752</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>403 rows × 15 columns</p>\n","</div>"],"text/plain":["         chol  stab.glu       hdl  ...     waist       hip  time.ppn\n","353 -0.041417 -0.472007  1.080314  ... -0.332110 -0.538447 -0.472201\n","233 -0.266969  0.290480  0.797224  ... -0.507293 -1.070731 -0.910336\n","3   -2.928491 -0.220006 -4.235595  ... -0.857660 -0.893303  0.452752\n","18  -0.312080 -0.524198 -0.868755  ... -1.383211 -1.603015 -0.715609\n","131 -0.447411 -0.630551 -0.184903  ...  1.594909  1.768115 -0.650700\n","..        ...       ...       ...  ...       ...       ...       ...\n","45   0.793128 -1.369639  0.645228  ...  1.945276  2.477827 -0.812973\n","90  -1.101514 -0.344215 -0.324229  ... -0.682477 -0.538447  1.134296\n","248  0.657797  0.356161 -0.184903  ...  0.018257  0.171264 -0.131429\n","337  1.199123 -0.028022  1.691196  ...  0.718992  1.058404 -1.040154\n","390 -0.266969  0.399485  1.034911  ... -0.682477 -0.183592  0.452752\n","\n","[403 rows x 15 columns]"]},"metadata":{"tags":[]},"execution_count":40}]},{"cell_type":"code","metadata":{"id":"zhkvV4mtW-gS","executionInfo":{"status":"ok","timestamp":1625477696176,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.preprocessing import OneHotEncoder"],"execution_count":41,"outputs":[]},{"cell_type":"code","metadata":{"id":"nFKW__tZW-gS","executionInfo":{"status":"ok","timestamp":1625477696177,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["combine = pd.concat([combine,pd.get_dummies(combine[\"frame\"])],axis=1)\n","combine.drop(columns=\"frame\",inplace=True)"],"execution_count":42,"outputs":[]},{"cell_type":"code","metadata":{"id":"S1Z4qpJ5W-gT","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1625477696177,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"55dfbcbd-c733-4062-dfef-63e6b186efb0"},"source":["combine"],"execution_count":43,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","      <th>0</th>\n","      <th>1</th>\n","      <th>2</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>353</th>\n","      <td>-0.041417</td>\n","      <td>-0.472007</td>\n","      <td>1.080314</td>\n","      <td>-1.001985</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>1</td>\n","      <td>0.776412</td>\n","      <td>-0.610801</td>\n","      <td>0.223454</td>\n","      <td>1.073274</td>\n","      <td>-0.332110</td>\n","      <td>-0.538447</td>\n","      <td>-0.472201</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>233</th>\n","      <td>-0.266969</td>\n","      <td>0.290480</td>\n","      <td>0.797224</td>\n","      <td>-0.816145</td>\n","      <td>1</td>\n","      <td>0.352171</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-0.933853</td>\n","      <td>1.679430</td>\n","      <td>1.778906</td>\n","      <td>-0.507293</td>\n","      <td>-1.070731</td>\n","      <td>-0.910336</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>0</td>\n","      <td>1.148155</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>-0.312080</td>\n","      <td>-0.524198</td>\n","      <td>-0.868755</td>\n","      <td>0.690563</td>\n","      <td>1</td>\n","      <td>-0.541273</td>\n","      <td>1</td>\n","      <td>-0.496206</td>\n","      <td>-1.281755</td>\n","      <td>-1.310909</td>\n","      <td>-0.479763</td>\n","      <td>-1.383211</td>\n","      <td>-1.603015</td>\n","      <td>-0.715609</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>131</th>\n","      <td>-0.447411</td>\n","      <td>-0.630551</td>\n","      <td>-0.184903</td>\n","      <td>-0.033104</td>\n","      <td>1</td>\n","      <td>-0.947960</td>\n","      <td>0</td>\n","      <td>0.278792</td>\n","      <td>1.228108</td>\n","      <td>-0.652145</td>\n","      <td>-0.982130</td>\n","      <td>1.594909</td>\n","      <td>1.768115</td>\n","      <td>-0.650700</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</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","      <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>45</th>\n","      <td>0.793128</td>\n","      <td>-1.369639</td>\n","      <td>0.645228</td>\n","      <td>-0.102494</td>\n","      <td>0</td>\n","      <td>-0.466755</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>1.377209</td>\n","      <td>-1.310909</td>\n","      <td>-0.015589</td>\n","      <td>1.945276</td>\n","      <td>2.477827</td>\n","      <td>-0.812973</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>90</th>\n","      <td>-1.101514</td>\n","      <td>-0.344215</td>\n","      <td>-0.324229</td>\n","      <td>-0.398089</td>\n","      <td>1</td>\n","      <td>-0.394224</td>\n","      <td>1</td>\n","      <td>0.529432</td>\n","      <td>-0.213199</td>\n","      <td>0.131908</td>\n","      <td>-0.243268</td>\n","      <td>-0.682477</td>\n","      <td>-0.538447</td>\n","      <td>1.134296</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>248</th>\n","      <td>0.657797</td>\n","      <td>0.356161</td>\n","      <td>-0.184903</td>\n","      <td>0.636739</td>\n","      <td>0</td>\n","      <td>1.381418</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>-0.088949</td>\n","      <td>1.152068</td>\n","      <td>-0.560674</td>\n","      <td>0.018257</td>\n","      <td>0.171264</td>\n","      <td>-0.131429</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>337</th>\n","      <td>1.199123</td>\n","      <td>-0.028022</td>\n","      <td>1.691196</td>\n","      <td>-0.907566</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>0</td>\n","      <td>-0.496206</td>\n","      <td>0.507454</td>\n","      <td>0.746684</td>\n","      <td>0.687334</td>\n","      <td>0.718992</td>\n","      <td>1.058404</td>\n","      <td>-1.040154</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>390</th>\n","      <td>-0.266969</td>\n","      <td>0.399485</td>\n","      <td>1.034911</td>\n","      <td>-1.099606</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>0</td>\n","      <td>-1.033326</td>\n","      <td>-0.759902</td>\n","      <td>0.402688</td>\n","      <td>0.818708</td>\n","      <td>-0.682477</td>\n","      <td>-0.183592</td>\n","      <td>0.452752</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>403 rows × 17 columns</p>\n","</div>"],"text/plain":["         chol  stab.glu       hdl     ratio  ...  time.ppn  0  1  2\n","353 -0.041417 -0.472007  1.080314 -1.001985  ... -0.472201  0  0  1\n","233 -0.266969  0.290480  0.797224 -0.816145  ... -0.910336  0  1  0\n","3   -2.928491 -0.220006 -4.235595  1.224437  ...  0.452752  1  0  0\n","18  -0.312080 -0.524198 -0.868755  0.690563  ... -0.715609  0  1  0\n","131 -0.447411 -0.630551 -0.184903 -0.033104  ... -0.650700  0  1  0\n","..        ...       ...       ...       ...  ...       ... .. .. ..\n","45   0.793128 -1.369639  0.645228 -0.102494  ... -0.812973  0  1  0\n","90  -1.101514 -0.344215 -0.324229 -0.398089  ...  1.134296  1  0  0\n","248  0.657797  0.356161 -0.184903  0.636739  ... -0.131429  1  0  0\n","337  1.199123 -0.028022  1.691196 -0.907566  ... -1.040154  0  1  0\n","390 -0.266969  0.399485  1.034911 -1.099606  ...  0.452752  0  1  0\n","\n","[403 rows x 17 columns]"]},"metadata":{"tags":[]},"execution_count":43}]},{"cell_type":"markdown","metadata":{"id":"hR2TQfRXW-gT"},"source":["### Separation OF Train And Test after using embedding"]},{"cell_type":"code","metadata":{"id":"BMI18TDEW-gT","executionInfo":{"status":"ok","timestamp":1625477696178,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["x_train = combine.iloc[:322]\n","x_test = combine.iloc[322:]\n"],"execution_count":44,"outputs":[]},{"cell_type":"code","metadata":{"id":"djYSY1GpW-gT","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477696178,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"d84ef322-cb6b-4300-921c-4887ca918002"},"source":["x_train.shape,y_train.shape,x_test.shape,y_test.shape"],"execution_count":45,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((322, 17), (322,), (81, 17), (81,))"]},"metadata":{"tags":[]},"execution_count":45}]},{"cell_type":"code","metadata":{"id":"t4XXMB1xL-Ne","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1625477696178,"user_tz":-330,"elapsed":12,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"36709eb9-be6d-4e2a-a3bc-afac0fbc428c"},"source":["# data now\n","x_train.head()"],"execution_count":46,"outputs":[{"output_type":"execute_result","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>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","      <th>0</th>\n","      <th>1</th>\n","      <th>2</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>353</th>\n","      <td>-0.041417</td>\n","      <td>-0.472007</td>\n","      <td>1.080314</td>\n","      <td>-1.001985</td>\n","      <td>1</td>\n","      <td>0.458841</td>\n","      <td>1</td>\n","      <td>0.776412</td>\n","      <td>-0.610801</td>\n","      <td>0.223454</td>\n","      <td>1.073274</td>\n","      <td>-0.332110</td>\n","      <td>-0.538447</td>\n","      <td>-0.472201</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>233</th>\n","      <td>-0.266969</td>\n","      <td>0.290480</td>\n","      <td>0.797224</td>\n","      <td>-0.816145</td>\n","      <td>1</td>\n","      <td>0.352171</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-0.933853</td>\n","      <td>1.679430</td>\n","      <td>1.778906</td>\n","      <td>-0.507293</td>\n","      <td>-1.070731</td>\n","      <td>-0.910336</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>-2.928491</td>\n","      <td>-0.220006</td>\n","      <td>-4.235595</td>\n","      <td>1.224437</td>\n","      <td>0</td>\n","      <td>1.148155</td>\n","      <td>1</td>\n","      <td>0.278792</td>\n","      <td>-1.455706</td>\n","      <td>-1.310909</td>\n","      <td>-3.037533</td>\n","      <td>-0.857660</td>\n","      <td>-0.893303</td>\n","      <td>0.452752</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>-0.312080</td>\n","      <td>-0.524198</td>\n","      <td>-0.868755</td>\n","      <td>0.690563</td>\n","      <td>1</td>\n","      <td>-0.541273</td>\n","      <td>1</td>\n","      <td>-0.496206</td>\n","      <td>-1.281755</td>\n","      <td>-1.310909</td>\n","      <td>-0.479763</td>\n","      <td>-1.383211</td>\n","      <td>-1.603015</td>\n","      <td>-0.715609</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>131</th>\n","      <td>-0.447411</td>\n","      <td>-0.630551</td>\n","      <td>-0.184903</td>\n","      <td>-0.033104</td>\n","      <td>1</td>\n","      <td>-0.947960</td>\n","      <td>0</td>\n","      <td>0.278792</td>\n","      <td>1.228108</td>\n","      <td>-0.652145</td>\n","      <td>-0.982130</td>\n","      <td>1.594909</td>\n","      <td>1.768115</td>\n","      <td>-0.650700</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["         chol  stab.glu       hdl     ratio  ...  time.ppn  0  1  2\n","353 -0.041417 -0.472007  1.080314 -1.001985  ... -0.472201  0  0  1\n","233 -0.266969  0.290480  0.797224 -0.816145  ... -0.910336  0  1  0\n","3   -2.928491 -0.220006 -4.235595  1.224437  ...  0.452752  1  0  0\n","18  -0.312080 -0.524198 -0.868755  0.690563  ... -0.715609  0  1  0\n","131 -0.447411 -0.630551 -0.184903 -0.033104  ... -0.650700  0  1  0\n","\n","[5 rows x 17 columns]"]},"metadata":{"tags":[]},"execution_count":46}]},{"cell_type":"code","metadata":{"id":"jGj7D50tW-gv","executionInfo":{"status":"ok","timestamp":1625477696179,"user_tz":-330,"elapsed":12,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["## Metric Table Function\n","from sklearn.metrics import r2_score,mean_squared_error,mean_absolute_error\n","from prettytable import PrettyTable\n","\n","def metrics(y_test,y_pred):\n","    r2score = r2_score(y_test,y_pred)\n","    MAD = np.mean(np.abs(y_pred-np.mean(y_test)))\n","    MAE = mean_absolute_error(y_test,y_pred)\n","    RMSE = np.sqrt(mean_squared_error(y_test,y_pred))\n","    MSE=mean_squared_error(y_test,y_pred)\n","    t = PrettyTable(['Error Metric', 'Value'])\n","    t.add_row([\"r2_score\",r2score])\n","    t.add_row([\"MSE\",MSE])\n","    t.add_row(['MAE', MAE])\n","    t.add_row([\"RMSE\",RMSE,])\n","    t.add_row([\"MAD\",MAD])\n","    return t #returns table"],"execution_count":47,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"wQM2onytTKjr"},"source":["# Machine Learning"]},{"cell_type":"markdown","metadata":{"id":"Dpuy0XNUW-hB"},"source":["## Models used for this Ensemble\n","1. Ridge()\n","2. Random forest\n","3. Lasso\n","4. XGBRegressor()"]},{"cell_type":"markdown","metadata":{"id":"BNf77RvHEErF"},"source":["##1. Ridge Regression :"]},{"cell_type":"code","metadata":{"id":"VOSFO64dW-hB","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477700470,"user_tz":-330,"elapsed":4303,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"62f4a750-3993-4a06-c708-8a1e1825382f"},"source":["### Ridge\n","from sklearn.linear_model import Ridge\n","ridge_reg = Ridge()\n","from sklearn.model_selection import GridSearchCV\n","params_Ridge = {'alpha': [1,0.1,0.01,0.001,0.0001,0] , \"fit_intercept\": [True, False], \"solver\": ['svd', 'cholesky', 'lsqr', 'sparse_cg', 'sag', 'saga']}\n","Ridge_GS = GridSearchCV(ridge_reg, param_grid=params_Ridge, n_jobs=-1, cv=10)\n","Ridge_GS.fit(x_train,y_train)\n","print(Ridge_GS.best_params_)\n","Ridge_best_model = Ridge_GS.best_estimator_\n","Ridge_best_model.fit(x_train,y_train)"],"execution_count":48,"outputs":[{"output_type":"stream","text":["{'alpha': 0, 'fit_intercept': True, 'solver': 'cholesky'}\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["Ridge(alpha=0, copy_X=True, fit_intercept=True, max_iter=None, normalize=False,\n","      random_state=None, solver='cholesky', tol=0.001)"]},"metadata":{"tags":[]},"execution_count":48}]},{"cell_type":"code","metadata":{"id":"EVwKe2M-W-hC","executionInfo":{"status":"ok","timestamp":1625477700470,"user_tz":-330,"elapsed":10,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["y_Ridge_GS_pred= Ridge_best_model.predict(x_test)"],"execution_count":49,"outputs":[]},{"cell_type":"code","metadata":{"id":"J0uIL76CW-hC","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477700470,"user_tz":-330,"elapsed":9,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"135aeeae-30b2-4c7d-b8da-eee16030808a"},"source":["# Metric table\n","print(metrics(y_test,y_Ridge_GS_pred))"],"execution_count":50,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7922249168951028 |\n","|     MSE      | 1.1210124540983644 |\n","|     MAE      | 0.7771605061234568 |\n","|     RMSE     | 1.0587787559723534 |\n","|     MAD      | 1.2809571682868461 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"1boEIXOiETzt"},"source":["## 2. Random forest"]},{"cell_type":"code","metadata":{"id":"qk2PWQO2W-gw","executionInfo":{"status":"ok","timestamp":1625477700471,"user_tz":-330,"elapsed":9,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.ensemble import RandomForestRegressor"],"execution_count":51,"outputs":[]},{"cell_type":"code","metadata":{"id":"4u8xJbNxW-gw","executionInfo":{"status":"ok","timestamp":1625477700471,"user_tz":-330,"elapsed":8,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["rf = RandomForestRegressor(n_estimators=20,\n","    max_depth=2,\n","    min_samples_split=2,\n","    min_samples_leaf=1,)\n","rf.fit(x_train,y_train)\n","y_rf = rf.predict(x_test)"],"execution_count":52,"outputs":[]},{"cell_type":"code","metadata":{"id":"Vcw-PFEpPwkr","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477700472,"user_tz":-330,"elapsed":9,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"287b83f0-d0c8-4ab3-99c1-8b7a258a602a"},"source":["print(metrics(y_test,y_rf))"],"execution_count":53,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.683902822332021  |\n","|     MSE      | 1.7054445007356893 |\n","|     MAE      | 0.8518478884977486 |\n","|     RMSE     | 1.3059266827566123 |\n","|     MAD      | 1.2171707327062158 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"CBZW1CZoEUKR"},"source":["## 3. Lasso"]},{"cell_type":"code","metadata":{"id":"IvWV7Np0W-hC","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477701275,"user_tz":-330,"elapsed":811,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"f41b6704-78e4-46d5-adbc-46ba28051ffa"},"source":["# lasso\n","from sklearn.linear_model import Lasso\n","lasso_reg = Lasso()\n","params_lasso = {'alpha':[0.02, 0.024, 0.025, 0.026, 0.03] , \"fit_intercept\": [True, False]}\n","lasso_GS = GridSearchCV(lasso_reg, param_grid=params_lasso, n_jobs=-1,cv=10)\n","lasso_GS.fit(x_train,y_train)\n","print(lasso_GS.best_params_)\n","Lasso_best_model = lasso_GS.best_estimator_\n","Lasso_best_model.fit(x_train,y_train)"],"execution_count":54,"outputs":[{"output_type":"stream","text":["{'alpha': 0.03, 'fit_intercept': False}\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["Lasso(alpha=0.03, copy_X=True, fit_intercept=False, max_iter=1000,\n","      normalize=False, positive=False, precompute=False, random_state=None,\n","      selection='cyclic', tol=0.0001, warm_start=False)"]},"metadata":{"tags":[]},"execution_count":54}]},{"cell_type":"code","metadata":{"id":"KFbo9JTOW-hC","executionInfo":{"status":"ok","timestamp":1625477701275,"user_tz":-330,"elapsed":5,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["y_lasso_GS_pred= Lasso_best_model.predict(x_test)"],"execution_count":55,"outputs":[]},{"cell_type":"code","metadata":{"id":"bVItQIHMW-hD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477701276,"user_tz":-330,"elapsed":6,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"2833e13e-fdd8-4de6-cf2c-7f085170042f"},"source":["print(metrics(y_test,y_lasso_GS_pred))"],"execution_count":56,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.8007416258485252 |\n","|     MSE      | 1.075062108840182  |\n","|     MAE      | 0.7623060882468625 |\n","|     RMSE     | 1.036852018776152  |\n","|     MAD      | 1.3003931892210152 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"aEza1ZqEEjUj"},"source":["## 4. XGBRegressor"]},{"cell_type":"code","metadata":{"id":"4kzHdWKRW-hD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477763671,"user_tz":-330,"elapsed":62400,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"7866807a-f9dd-45c1-e911-7ca35a7263be"},"source":["## XGBRegressor\n","import xgboost as xgb\n","from xgboost.sklearn import XGBRegressor\n","xgb1 = XGBRegressor()\n","parameters = {'nthread':[4], \n","              'objective':['reg:linear'],\n","              'learning_rate': [.03, 0.05, .07],\n","              'max_depth': [5, 6, 7],\n","              'min_child_weight': [4],\n","              'silent': [1],\n","              'subsample': [0.7],\n","              'colsample_bytree': [0.7],\n","              'n_estimators': [500]}\n","\n","xgb_grid = GridSearchCV(xgb1,parameters,cv = 10,n_jobs = 5,verbose=True)\n","xgb_grid.fit(x_train,y_train)\n","\n","print(xgb_grid.best_score_)\n","print(xgb_grid.best_params_)\n","\n","xgb_best_model = xgb_grid.best_estimator_\n","xgb_best_model.fit(x_train,y_train)"],"execution_count":57,"outputs":[{"output_type":"stream","text":["Fitting 10 folds for each of 9 candidates, totalling 90 fits\n"],"name":"stdout"},{"output_type":"stream","text":["[Parallel(n_jobs=5)]: Using backend LokyBackend with 5 concurrent workers.\n","[Parallel(n_jobs=5)]: Done  40 tasks      | elapsed:   28.0s\n","[Parallel(n_jobs=5)]: Done  90 out of  90 | elapsed:  1.0min finished\n"],"name":"stderr"},{"output_type":"stream","text":["0.22119865680570988\n","{'colsample_bytree': 0.7, 'learning_rate': 0.03, 'max_depth': 7, 'min_child_weight': 4, 'n_estimators': 500, 'nthread': 4, 'objective': 'reg:linear', 'silent': 1, 'subsample': 0.7}\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n","             colsample_bynode=1, colsample_bytree=0.7, gamma=0,\n","             importance_type='gain', learning_rate=0.03, max_delta_step=0,\n","             max_depth=7, min_child_weight=4, missing=None, n_estimators=500,\n","             n_jobs=1, nthread=4, objective='reg:linear', random_state=0,\n","             reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=1,\n","             subsample=0.7, verbosity=1)"]},"metadata":{"tags":[]},"execution_count":57}]},{"cell_type":"code","metadata":{"scrolled":true,"id":"1Z2a2eouW-hD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477763671,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6db12bb1-4447-4208-bdab-7cf3a9bb7de1"},"source":["y_XGBReg_pred= xgb_best_model.predict(x_test)\n","print(metrics(y_test,y_XGBReg_pred))"],"execution_count":58,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7089551457410138 |\n","|     MSE      | 1.5702792724229064 |\n","|     MAE      | 0.8085919927257035 |\n","|     RMSE     | 1.2531078454877322 |\n","|     MAD      |     1.3093013      |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"qKBllY7VW-hD"},"source":["## Ensemble Learning with Average weights"]},{"cell_type":"code","metadata":{"id":"dRcJZBKGW-hE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477763672,"user_tz":-330,"elapsed":13,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"628f9425-1482-44cf-c185-51f6db6916eb"},"source":["Ensemble_average_prediction_1 = ( y_XGBReg_pred+ y_lasso_GS_pred+ y_rf + y_Ridge_GS_pred ) / 4\n","print(metrics(y_test,Ensemble_average_prediction_1))"],"execution_count":59,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7785267928436886 |\n","|     MSE      | 1.1949181767189496 |\n","|     MAE      | 0.723711856092992  |\n","|     RMSE     | 1.0931231297154724 |\n","|     MAD      | 1.2452054067168867 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"lp0Oe6eVE09F"},"source":["## Ensemble Learning with Average weight using only **Ridge** and **Lasso**"]},{"cell_type":"code","metadata":{"id":"ei4dm_WuW-hE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477763672,"user_tz":-330,"elapsed":12,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"2974bf04-f648-4233-961a-447c7397d97c"},"source":["Ensemble_Weighted_average_prediction_2 = y_Ridge_GS_pred*0.1 + y_lasso_GS_pred*0.9\n","print(metrics(y_test,Ensemble_Weighted_average_prediction_2))\n","\n"],"execution_count":60,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.8002404531819427 |\n","|     MSE      | 1.0777660942868346 |\n","|     MAE      | 0.7625936049507885 |\n","|     RMSE     | 1.0381551397969546 |\n","|     MAD      | 1.298295266139944  |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"2lR-Ywf1FLmV"},"source":["## Ensemble Learning with Custom Weights"]},{"cell_type":"code","metadata":{"id":"Kt30AydYW-hE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477763673,"user_tz":-330,"elapsed":12,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"9a8072aa-d5e4-42c6-bee8-88aa1f48ec29"},"source":["Ensemble_average_prediction_3=  y_XGBReg_pred*0.12 + y_lasso_GS_pred*0.5+ y_rf*0.12 + y_Ridge_GS_pred*0.25\n","print(metrics(y_test,Ensemble_average_prediction_3))"],"execution_count":61,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7904509508247761 |\n","|     MSE      | 1.1305835635320214 |\n","|     MAE      | 0.7414504378330029 |\n","|     RMSE     | 1.063289031040959  |\n","|     MAD      | 1.2851913254711373 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"GRXTT1m1W-hI"},"source":["## Ensemble Learning with Optimzed Weights for\n","1. Ridge()\n","2. Random forest\n","3. Lasso\n","4. XGBRegressor()"]},{"cell_type":"code","metadata":{"id":"-5NLYNY1tuXU","executionInfo":{"status":"ok","timestamp":1625477763673,"user_tz":-330,"elapsed":10,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from scipy.optimize import minimize"],"execution_count":62,"outputs":[]},{"cell_type":"code","metadata":{"id":"s5GfUhazppUm","executionInfo":{"status":"ok","timestamp":1625477763673,"user_tz":-330,"elapsed":9,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["rmse_optimize =[]"],"execution_count":63,"outputs":[]},{"cell_type":"code","metadata":{"id":"-ZYXUGXjs9My","executionInfo":{"status":"ok","timestamp":1625477763674,"user_tz":-330,"elapsed":10,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["def rmse_loss_func(weights):\n","    ''' scipy minimize will pass the weights as a numpy array '''\n","    final_prediction = 0\n","    for weight, prediction in zip(weights, predictions):\n","            final_prediction += weight*prediction\n","\n","    print(np.sqrt(mean_squared_error(y_test,final_prediction)),weights)\n","    rmse_optimize.append(np.sqrt(mean_squared_error(y_test,final_prediction)))\n","    return np.sqrt(mean_squared_error(y_test,final_prediction))"],"execution_count":64,"outputs":[]},{"cell_type":"code","metadata":{"id":"eNw6fPB5W-hI","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477765014,"user_tz":-330,"elapsed":1349,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"bfc16a0b-6d32-407a-97b3-681ada6fd3a8"},"source":["# add every model's prediction into list\n","predictions = []\n","predictions.append(y_Ridge_GS_pred)\n","predictions.append(y_rf)\n","predictions.append(y_lasso_GS_pred)\n","predictions.append(y_XGBReg_pred)\n","#starting Value\n","starting_values = [0.5]*len(predictions)\n","#cons = ({'type':'eq','fun':lambda w: 1-sum(w)})\n","#our weights are bound between 0 and 1\n","bounds = [(0,1)]*len(predictions)\n","res = minimize(rmse_loss_func, starting_values, method='Powell')"],"execution_count":65,"outputs":[{"output_type":"stream","text":["5.772912859603106 [0.5 0.5 0.5 0.5]\n","5.772912859603106 [0.5 0.5 0.5 0.5]\n","11.647733830757952 [1.5 0.5 0.5 0.5]\n","4.15637316302882 [-1.118034  0.5       0.5       0.5     ]\n","1.4402208227880486 [-0.57724436  0.5         0.5         0.5       ]\n","1.4402208227880486 [-0.57724436  0.5         0.5         0.5       ]\n","2.0834020541703593 [-0.16577364  0.5         0.5         0.5       ]\n","2.3330955858729006 [-0.78380762  0.5         0.5         0.5       ]\n","1.224295375792719 [-0.45357858  0.5         0.5         0.5       ]\n","1.2255091607932564 [-0.43948316  0.5         0.5         0.5       ]\n","1.2267202819677698 [-0.46311436  0.5         0.5         0.5       ]\n","1.224295375792719 [-0.45357858  0.5         0.5         0.5       ]\n","6.0212963006755755 [-0.45357858  1.5         0.5         0.5       ]\n","9.445976921371631 [-0.45357858 -1.118034    0.5         0.5       ]\n","1.224295375792719 [-0.45357858  0.5         0.5         0.5       ]\n","3.7421291033985433 [-0.45357858 -0.11803397  0.5         0.5       ]\n","2.598460394665514 [-0.45357858  0.881966    0.5         0.5       ]\n","1.2367862919219488 [-0.45357858  0.45650561  0.5         0.5       ]\n","1.2229008925675944 [-0.45357858  0.49397894  0.5         0.5       ]\n","1.222506396648038 [-0.45357858  0.48862488  0.5         0.5       ]\n","1.222506493682852 [-0.45357858  0.48873863  0.5         0.5       ]\n","1.2225066593273233 [-0.45357858  0.48851113  0.5         0.5       ]\n","1.222506396648038 [-0.45357858  0.48862488  0.5         0.5       ]\n","5.938214282507337 [-0.45357858  0.48862488  1.5         0.5       ]\n","9.712246894109212 [-0.45357858  0.48862488 -1.118034    0.5       ]\n","1.222506396648038 [-0.45357858  0.48862488  0.5         0.5       ]\n","3.929116808453904 [-0.45357858  0.48862488 -0.11803397  0.5       ]\n","2.484840949827489 [-0.45357858  0.48862488  0.881966    0.5       ]\n","1.2408933079708844 [-0.45357858  0.48862488  0.47594272  0.5       ]\n","1.2210477831318387 [-0.45357858  0.48862488  0.52610264  0.5       ]\n","1.219293215732418 [-0.45357858  0.48862488  0.51502963  0.5       ]\n","1.2192934644715714 [-0.45357858  0.48862488  0.51487933  0.5       ]\n","1.2192936119510023 [-0.45357858  0.48862488  0.51517992  0.5       ]\n","1.219293215732418 [-0.45357858  0.48862488  0.51502963  0.5       ]\n","6.08497090702 [-0.45357858  0.48862488  0.51502963  1.5       ]\n","9.517911577071047 [-0.45357858  0.48862488  0.51502963 -1.118034  ]\n","1.219293215732418 [-0.45357858  0.48862488  0.51502963  0.5       ]\n","3.7591708872820035 [-0.45357858  0.48862488  0.51502963 -0.11803397]\n","2.6251802068764003 [-0.45357858  0.48862488  0.51502963  0.881966  ]\n","1.2310327383516366 [-0.45357858  0.48862488  0.51502963  0.45474853]\n","1.2170648564617736 [-0.45357858  0.48862488  0.51502963  0.49143897]\n","1.2167260597613527 [-0.45357858  0.48862488  0.51502963  0.48653165]\n","1.2167262268808434 [-0.45357858  0.48862488  0.51502963  0.48666633]\n","1.2167264282624832 [-0.45357858  0.48862488  0.51502963  0.48639697]\n","5.924682516822867 [-1.40715715  0.47724975  0.53005925  0.4730633 ]\n","1.2167260597613527 [-0.45357858  0.48862488  0.51502963  0.48653165]\n","5.986335421051562 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0.06904816]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"Lb7Cr675uUCz","executionInfo":{"status":"ok","timestamp":1625477765015,"user_tz":-330,"elapsed":7,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"4c839ff0-6bcb-4d44-e294-e2145e778b3c"},"source":["\n","g = sns.relplot(x=range(len(rmse_optimize)), y=rmse_optimize, kind=\"line\")\n","g.fig.set_size_inches(10,8)\n","plt.title(\"RMSE - Weights Optimization\")\n","plt.ylabel('RMSE')\n","plt.xlabel('Number of Iterations')\n","g.fig.autofmt_xdate()\n"],"execution_count":66,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x576 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"K-_CXQz7W-hJ","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477765921,"user_tz":-330,"elapsed":911,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"5873bebd-96a3-47d3-fb68-f5b6f6317903"},"source":["print('Ensamble Score: {best_score}'.format(best_score=res['fun']))\n","print('Best Weights: {weights}'.format(weights=res['x']))"],"execution_count":67,"outputs":[{"output_type":"stream","text":["Ensamble Score: 1.0179985211189333\n","Best Weights: [-0.02401126  0.00520755  0.98216522  0.06904938]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"OQ4aNe4oW-hJ"},"source":["1. Ridge()\n","2. Random forest\n","3. Lasso\n","4. XGBRegressor()"]},{"cell_type":"code","metadata":{"id":"SL2YXDYovdxe","executionInfo":{"status":"ok","timestamp":1625477765921,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["best_weights=res[\"x\"]"],"execution_count":68,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7ayNt_ZSvXe2","executionInfo":{"status":"ok","timestamp":1625477765922,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"4cdf8bdd-df5d-4f88-917a-78223e1e218a"},"source":["w1,w2,w3,w4 = best_weights[0],best_weights[1],best_weights[2],best_weights[3]\n","w1"],"execution_count":69,"outputs":[{"output_type":"execute_result","data":{"text/plain":["-0.024011260261695627"]},"metadata":{"tags":[]},"execution_count":69}]},{"cell_type":"code","metadata":{"id":"qop3TTIpW-hJ","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477765922,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"f13c12b9-75f2-4e5b-cc74-c8e3966d0cdf"},"source":["Ensemble_average_prediction_2 = ( y_XGBReg_pred*w4+ y_lasso_GS_pred*w3 + y_rf*w2 +\n","                                 y_Ridge_GS_pred*w1)\n","print(metrics(y_test,Ensemble_average_prediction_2))"],"execution_count":70,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.8079221342941474 |\n","|     MSE      | 1.0363209890003355 |\n","|     MAE      | 0.7716336155288626 |\n","|     RMSE     | 1.0179985211189335 |\n","|     MAD      | 1.2602669980224543 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"EscvINY1kY04"},"source":["## Model Comparison Charts\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"IpOw0Nw2z08o","executionInfo":{"status":"ok","timestamp":1625477765923,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"af339e20-935f-4a7d-f2e0-5c430f66fed8"},"source":["fig = plt.figure(figsize=(7,5))\n","ax = fig.add_axes([0,0,1,1])\n","models = ['Ridge', 'LASSO', 'Random Forest', 'XGBRegressor', 'Ensemble']\n","\n","r2_score_list = [round(r2_score(y_test,y_Ridge_GS_pred),3),\n","                 round(r2_score(y_test,y_lasso_GS_pred),3),\n","                 round(r2_score(y_test,y_rf),3),\n","                 round(r2_score(y_test,y_XGBReg_pred),3),\n","                 round(r2_score(y_test,Ensemble_average_prediction_2),3)]\n","\n","ax.bar(models,r2_score_list)\n","ax.set_ylabel('R2 Score',fontsize= 12)\n","ax.set_xlabel('Models',fontsize= 12)\n","ax.set_title('Model Comparison')\n","for i, v in enumerate(r2_score_list):\n","  ax.text(i - 0.1,v + 0.01, str(v), color='black', fontweight='bold')\n","#plt.savefig('barplot_1.png',dpi=200, format='png', bbox_inches='tight')\n","plt.show()"],"execution_count":71,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 504x360 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"54Dnxwe0kYNs","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477770785,"user_tz":-330,"elapsed":4878,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"ba809789-450a-45be-cb45-76572e0ed08e"},"source":["!pip install regressormetricgraphplot"],"execution_count":72,"outputs":[{"output_type":"stream","text":["Collecting regressormetricgraphplot\n","  Downloading https://files.pythonhosted.org/packages/b1/48/e51f42f8bfcbb285c5bfe465dc72f94d4b18870ef5f0c8a1b370d5407cd0/regressormetricgraphplot-0.0.3-py3-none-any.whl\n","Installing collected packages: regressormetricgraphplot\n","Successfully installed regressormetricgraphplot-0.0.3\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"XZCQY666l4w_","executionInfo":{"status":"ok","timestamp":1625477770786,"user_tz":-330,"elapsed":23,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from regressormetricgraphplot import CompareModels"],"execution_count":73,"outputs":[]},{"cell_type":"code","metadata":{"id":"XVXVvuGDmx9R","executionInfo":{"status":"ok","timestamp":1625477770786,"user_tz":-330,"elapsed":21,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["plot = CompareModels()\n","plot.add(model_name='Ridge Regression', y_test=y_test, y_pred=y_Ridge_GS_pred)\n","#plot.show(figsize=(10, 5))"],"execution_count":74,"outputs":[]},{"cell_type":"code","metadata":{"id":"vdWQLAQvnKJL","executionInfo":{"status":"ok","timestamp":1625477770787,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["plot.add(model_name='LASSO Regression', y_test=y_test, y_pred=y_lasso_GS_pred)\n","plot.add(model_name='Random Forest', y_test=y_test, y_pred=y_rf)\n","plot.add(model_name='XGBRegressor', y_test=y_test, y_pred=y_XGBReg_pred)"],"execution_count":75,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"e1JrjaLCnngK","executionInfo":{"status":"ok","timestamp":1625477770788,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"537b744e-ac0d-46de-ea24-46fdd0209c54"},"source":["plot.show(figsize=(10, 10))"],"execution_count":76,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"zDVjbMFzoFcC","executionInfo":{"status":"ok","timestamp":1625477770790,"user_tz":-330,"elapsed":23,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["plot.add(model_name='Ensemble Model', y_test=y_test, y_pred=Ensemble_average_prediction_2)"],"execution_count":77,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"q1pqdgv_oSVU","executionInfo":{"status":"ok","timestamp":1625477770790,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6661d74f-b563-4e8e-ce38-5ca80710ed23"},"source":["plot.show(figsize=(10, 10))"],"execution_count":78,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"K7RC33pJK9pT","executionInfo":{"status":"ok","timestamp":1625477770791,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"a271e633-66cd-4f91-c199-a25f4da4dcfe"},"source":["y_test_array=y_test.to_numpy()\n","y_test_array"],"execution_count":79,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 4.59000015,  4.86999989,  4.42999983,  5.65999985,  4.38000011,\n","        4.28999996,  6.48999977,  4.96000004,  9.27999973,  7.21999979,\n","       10.06999969,  3.93000007,  4.67000008,  4.6500001 , 12.97000027,\n","        5.05000019,  8.81000042,  5.36000013,  5.78000021,  4.30999994,\n","        6.3499999 , 16.11000061,  4.13999987,  5.38000011,  4.80999994,\n","        6.78000021,  5.28000021, 10.09000015,  4.96000004,  3.41000009,\n","        5.09000015,  4.84000015,  4.30999994,  4.82999992,  4.23999977,\n","        4.67999983,  5.19999981,  4.19999981,  5.51999998,  4.94999981,\n","        5.03000021,  4.82999992,  4.9000001 ,  4.30999994,  4.05000019,\n","        3.02999997,  4.17999983,  6.48000002, 11.59000015,  3.83999991,\n","        4.03999996, 12.73999977,  4.84000015,  6.13999987,  5.53000021,\n","        3.61999989,  5.19999981,  4.38999987,  7.90999985,  4.40999985,\n","        4.98000002,  4.4000001 ,  5.11000013,  4.86999989,  3.79999995,\n","        4.84000015,  4.38999987,  9.77000046,  4.46999979,  4.30999994,\n","        5.73999977,  4.42999983,  5.46999979,  7.4000001 ,  4.80999994,\n","        4.80999994,  4.40999985,  5.01999998,  7.51000023,  5.11999989,\n","        9.36999989])"]},"metadata":{"tags":[]},"execution_count":79}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ASalXceULHKr","executionInfo":{"status":"ok","timestamp":1625477770792,"user_tz":-330,"elapsed":22,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"abda2c23-c222-47a2-d7e3-1eb2a987310d"},"source":["Ensemble_average_prediction_2"],"execution_count":80,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 5.07948144,  6.4624354 ,  5.76412214,  5.43075579,  4.71374093,\n","        5.34808511,  6.7153863 ,  5.05729216,  8.82258143,  6.53117181,\n","       10.52674785,  4.49338324,  4.33615332,  5.15138912, 11.77405461,\n","        5.85717139,  6.9998413 ,  5.36993787,  5.47367216,  4.70675976,\n","        4.87350893, 12.49376382,  4.8078052 ,  5.32059548,  5.25494125,\n","        6.15296896,  5.13367838,  9.57605724,  5.11555865,  4.80828827,\n","        5.03981928,  3.57308193,  5.08495674,  4.25685212,  4.95982885,\n","        4.97018917,  6.66464503,  4.52488017,  5.02942897,  3.92535315,\n","        5.48663042,  4.99720634,  5.37866895,  3.95203062,  4.75418647,\n","        4.20388059,  4.52479595,  5.64668869, 12.0062309 ,  4.63975322,\n","        5.38765152, 10.3984242 ,  5.634869  ,  8.72954114,  6.62975516,\n","        4.75635252,  4.71823214,  3.57752484,  9.12191969,  4.2232334 ,\n","        5.3674731 ,  4.17130883,  5.66931294,  6.71992059,  4.62974105,\n","        5.41260358,  5.48203452,  8.27912592,  5.15433659,  3.95035294,\n","        5.56093604,  4.53948869,  5.9522441 ,  6.12790121,  4.73027467,\n","        5.12993427,  3.68659139,  4.9339989 ,  6.61725901,  5.64537536,\n","        6.30139099])"]},"metadata":{"tags":[]},"execution_count":80}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"jSwcOhBJKYmM","executionInfo":{"status":"ok","timestamp":1625477770792,"user_tz":-330,"elapsed":21,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"d23aaa81-aea8-4349-cf17-51bc9fa4b4f1"},"source":["#Ensemble_average_prediction_2\n","labels =[\"Actual Values\", \"Predicted Values\"]\n","plt.plot(y_test_array)\n","plt.plot(Ensemble_average_prediction_2)\n","plt.xlabel(\"Frequency\")\n","plt.ylabel(\"Glyhb\")\n","plt.title(\"Ensemble Predicted Values VS Actual Values\")\n","plt.legend(labels)"],"execution_count":81,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.legend.Legend at 0x7fc4f1389e90>"]},"metadata":{"tags":[]},"execution_count":81},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"IOF0XZ93w72s"},"source":["\n","\n","---\n","\n"]},{"cell_type":"markdown","metadata":{"id":"mvOzWDYVw-gy"},"source":["# Feature **Importance**"]},{"cell_type":"code","metadata":{"id":"1al_5fTv2Q4a","executionInfo":{"status":"ok","timestamp":1625477770792,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["import matplotlib.pyplot as plt\n","import matplotlib\n","%matplotlib inline"],"execution_count":82,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jr7d-pzC2w-1"},"source":["### Lasso Important features"]},{"cell_type":"code","metadata":{"id":"zwA-8OVF1d_S","executionInfo":{"status":"ok","timestamp":1625477770793,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# lasso \n","coef = pd.Series(Lasso_best_model.coef_, index = x_train.columns)"],"execution_count":83,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"D64NndnV150w","executionInfo":{"status":"ok","timestamp":1625477770793,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"39deb995-7a54-4f29-e586-522a45ab5616"},"source":["print(\"Lasso picked \" + str(sum(coef != 0)) + \" variables and eliminated the other \" +  str(sum(coef == 0)) + \" variables\")"],"execution_count":84,"outputs":[{"output_type":"stream","text":["Lasso picked 13 variables and eliminated the other 4 variables\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"M3d6aENm2dI4","executionInfo":{"status":"ok","timestamp":1625477770793,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["imp_coef = pd.concat([coef.sort_values().head(11),\n","                     coef.sort_values().tail(11)])"],"execution_count":85,"outputs":[]},{"cell_type":"code","metadata":{"id":"z3YQQeyS2Bxy","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1625477772205,"user_tz":-330,"elapsed":1428,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"3c4757dd-27eb-4977-e2b6-be15cb658562"},"source":["matplotlib.rcParams['figure.figsize'] = (8.0, 10.0)\n","imp_coef.plot(kind = \"barh\")\n","plt.title(\"Coefficients in the Lasso Model\")"],"execution_count":86,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Coefficients in the Lasso Model')"]},"metadata":{"tags":[]},"execution_count":86},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAgAAAAJOCAYAAADBKr/mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deZhlZX3u/e/NoIhAEKjwgtqWigGZgxsVxQFjPChGSERRiQZD0ofjiB7UNg4RT8zLkXOiRkRtCaCRoAHEYDDECWQQxWpooJtBjbQvikMhMwIq/N4/9mrdlFXd1d1Ve6j1/VxXXbWGZz3rt3ZB73s/z9p7p6qQJEntstGgC5AkSf1nAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgzaEkOydZnuTOJG9I8rAkX0hye5Izkhye5Euz6OdvkpzUj5rXUMOiJHcl2XiO+ntPkk/PRV9tk2RVkufOot14kkqyST/q0mgzAKiVkrwiyUTzBPfjJP+RZP856PqtwPlVtWVV/SNwKLA9sG1VvaSqTquq562tk6r6+6r6qw0tZkOeEKrq/6uqLarq/vU477OT/HBdj1uH/k9N8nfz1f/6auqqJAdP2f6BZvsRAypN+h0GALVOkjcDHwT+nu6T8yLgRODgNR03S48BVk5Z/05V/XoO+tZo+A7wqtUrTfh6KfBfA6tImoYBQK2S5PeA9wKvrarPVdXdVfWrqvpCVb2lafPQJB9MclPz88EkD+3p44XNMP9tSb6RZM9m+9eAA4ATmpGF04F3A4c160cmOSLJxT197Zbky0luSfLTJH/TbH/QcHmSpzbnui3JlUme3bPvgiT/K8klzdTDl5Js1+y+sPl9W1PDfkl2SvL1Zlri5iSfneGxetDowVrO03vcw4H/AHZsznlXkh2b3Q9J8qnm+JVJOj3H7ZjkrCSTSW5I8obZ/E2nOf+HktyY5I4ky5I8o2ffk5uRnzuax/sfmu2bJfl0kp83j/G3k2zfU9c5zd/oe0n+ei0lfAHYP8kjmvUDgauAn/TUsVGSdyb5QZKfNY/J7/Xsf2Wz7+dJ3jHl+jZKsiTJfzX7/zXJNuvzWKndDABqm/2AzYCz19DmHcBTgb2BvYAnA+8ESPKHwMnAfwe2BT4OnJPkoVX1HOAi4HXN0PnL6Y4yfLZZ/6fekyTZEvgKcB6wI7AT8NWpxSR5JHAu8HfANsAxwFlJxnqavQJ4NfD7wEOaNgDPbH5v3dRwKfC/gC8BjwAeBXx4DY/FVDOd5zeq6m7g+cBNzTm3qKqbmt0vAj4DbA2cA5zQXONGdJ84rwQeCfwRcHSS/7YOta32bbp/u22AfwHOSLJZs+9DwIeqaivg8cC/Ntv/Avg94NF0/65HAfc0+z4D/JDu3+hQ4O+TPGcN578X+DfgZc36q4BPTWlzRPNzAPA4YAt++1jsCnwUeGVzzm3p/p1Wez1wCPCsZv+twEfWUI80LQOA2mZb4Oa1DMkfDry3qn5WVZPAsXT/MQZYDHy8qr5VVfdX1SeB++gGhnX1QuAnVfV/q+reqrqzqr41Tbs/B75YVV+sqgeq6svABPCCnjanVNV3quoeuk9qe6/hvL+iOzWxY3Pei9fQdqp1Oc90Lm6u437gn+kGLIB9gbGqem9V/bKqvg98gt8+ic5aVX26qn5eVb+uqv8LPBTYudn9K2CnJNtV1V1V9c2e7dsCOzV/12VVdUeSRwNPB97WPFbLgZPoGeKfwaeAVyXZmu4T9een7D8c+Ieq+n5V3QW8HXhZM9pyKPDvVXVhVd0HvAt4oOfYo4B3VNUPm/3vAQ6NN/5pHRkA1DY/B7Zbyz+WOwI/6Fn/QbMNuk+c/7MZJr4tyW10XzXuyLp7NLObF34M8JIp59wf2KGnzU96ln9B9xXlTN4KBLisGYb/y3WoeV3OM5vjN2v+Fo+hO2XQe41/Q/cejXWS5Jgk1zZTHLfRfWW/eqriSOAPgOuaYf4XNtv/GfhP4DPpTvu8P8mmdP+ut1TVnT2n+AHdUYoZNaFqjO5o0r83ganXdP+NbdJc747AjT193U33v9vVHgOc3fM4XQvcz3o8Vmo3E6Pa5lK6r9gPAc6coc1NPPhmvkXNNuj+w/y+qnrfHNRyI7N7hXsj8M9Vtba55+n8ztd9VtVPgL8GSPedD19JcmFVfW89+p/1edfiRuCGqnrChpy0me9/K90phJVV9UCSW+kGHqrqu8DLmymHPwPOTLJt8yR7LHBsknHgi8D1dKdKtkmyZU8IWAT8aBblfJruPSAHTLNv9X9jqy0Cfg38FPgx8MSea9qc7ujEajcCf1lVl0xz/eOzqEsCHAFQy1TV7XT/Uf5IkkOSbJ5k0yTPT/L+ptnpwDuTjDU3ub2b7j/m0B2WPirJU9L18CQHNfP56+rfgR2SHJ3ujYdbJnnKNO0+DfxJkv+WZOPmhrVnJ3nUNG2nmqQ7fPy41RuSvKTn2FvpPlk/MM2xG+KnwLa9N7atxWXAnUnelu5nJ2ycZPck+67hmNWPxeqfhwBb0n0inQQ2SfJuYKvVByT58yRjVfUAcFuz+YEkByTZI93PPLiD7pTAA1V1I/AN4P9tzrEn3VGE2XyewT8Cf8xvb8TsdTrwpiSPTbIFv71X5Nd0g+kLk+zfXNN7efC/1R8D3pfkMc01jWXK2w6l2TAAqHWaeeE3072xb5LuK6rX8dt52r+jO8d+FXA1cHmzjaqaoPvq+QS6T57fo3sz1/rUcSfdJ4g/oTs0/l2mebXYPAkdTHdIfHW9b2EW//9W1S+A9wGXNEPGT6U73/6tJHfRvRHvjc2c+5ypquvoPsl9vznvGqdImnsCXkj3noIbgJvpzrWvKUAsoXuj3uqfr9Edxj+P7lvxfkD3hrwbe445EFjZXPuHgJc1w/P/D90n3jvoDql/ne60AMDLgXG6r9rPBv62qr4yi8fglqr6alVNNxpyctP/hc313kv35j6qaiXwWro3MP6Y7n9nvZ+p8CG6f7cvJbkT+CYwXXCU1ijT/7cpSZIWMkcAJElqIQOAJEktZACQJKmFDACSJLVQqz4HYLvttqvx8fFBlyFJUl8sW7bs5qoam25fqwLA+Pg4ExMTgy5DkqS+SPKDmfY5BSBJUgsZACRJaiEDgCRJLWQAkCSphVp1E2C/jS85d9AlSJJGyKrjDurbuRwBkCSphQwAkiS1kAFAkqQWGukAkOTkJD9LsmLQtUiSNEpGOgAApwIHDroISZJGzUgHgKq6ELhl0HVIkjRqRjoAzEaSxUkmkkxMTk4OuhxJkobCgg8AVbW0qjpV1Rkbm/YLkSRJap0FHwAkSdLvMgBIktRCIx0AkpwOXArsnOSHSY4cdE2SJI2Ckf4ugKp6+aBrkCRpFI10ABh2/fxSB0mS1sVITwFIkqT1YwCQJKmFDACSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACQJKmFDACSJLWQ3wUwj8aXnDvoEiRJAzLs3wfjCIAkSS1kAJAkqYVGOgAkOTDJ9Um+l2TJoOuRJGlUjGwASLIx8BHg+cCuwMuT7DrYqiRJGg0jGwCAJwPfq6rvV9Uvgc8ABw+4JkmSRsIoB4BHAjf2rP+w2fYgSRYnmUgyMTk52bfiJEkaZqMcAGalqpZWVaeqOmNjY4MuR5KkoTDKAeBHwKN71h/VbJMkSWsxygHg28ATkjw2yUOAlwHnDLgmSZJGwsh+EmBV/TrJ64D/BDYGTq6qlQMuS5KkkTCyAQCgqr4IfHHQdUiSNGpGOgAMu2H/HGhJUnuN8j0AkiRpPRkAJElqIQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACQJKmF/DKgeTS+5NxBlyBJGoBR+DI4RwAkSWohA4AkSS00sgEgyaOTnJ/kmiQrk7xx0DVJkjQqRvkegF8D/7OqLk+yJbAsyZer6ppBFyZJ0rAb2RGAqvpxVV3eLN8JXAs8crBVSZI0GkY2APRKMg78IfCtafYtTjKRZGJycrLfpUmSNJRGPgAk2QI4Czi6qu6Yur+qllZVp6o6Y2Nj/S9QkqQhNNIBIMmmdJ/8T6uqzw26HkmSRsXIBoAkAf4JuLaq/mHQ9UiSNEpGNgAATwdeCTwnyfLm5wWDLkqSpFEwsm8DrKqLgQy6DkmSRtHIBoBRMAqfBS1JaqdRngKQJEnryQAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS3klwHNo/El5w66BE3DL2mSJEcAJElqJQOAJEktNCcBIMnRSTafRbtVSbbbgPNs0PGSJKlrrkYAjgbWGgAkSdJwWOcAkOThSc5NcmWSFUn+FtgROD/J+U2bjyaZSLIyybFTunhrkquTXJZkp2n63zzJvya5JsnZSb6VpDOlzXiSFT3rxyR5z7peiyRJbbU+7wI4ELipqg4CSPJ7wKuBA6rq5qbNO6rqliQbA19NsmdVXdXsu72q9kjyKuCDwAun9P8a4Naq2jXJ7sDy9ajxN5IsBhYDLFq0aEO6kiRpwVifKYCrgT9O8r+TPKOqbp+mzUuTXA5cAewG7Nqz7/Se3/tNc+z+wGcAqmoFcNU0bWatqpZWVaeqOmNjYxvSlSRJC8Y6jwBU1XeS7AO8APi7JF/t3Z/kscAxwL5VdWuSU4HNeruYYXld/JoHh5fNZmooSZJ+1/rcA7Aj8Iuq+jRwPLAPcCewZdNkK+Bu4PYk2wPPn9LFYT2/L53mFJcAL23OtSuwxzRtfgr8fpJtkzyU351GkCRJa7A+9wDsARyf5AHgV8D/oDuUf16Sm6rqgCRXANcBN9J9Qu/1iCRXAfcBLwdI8iKgU1XvBk4EPpnkmqaPlcCDphmq6ldJ3gtcBvyoaSdJkmYpVes7Cj8/mhsHN62qe5M8HvgKsHNV/XJD++50OjUxMbHBNc6WHwU8nPwoYEltkWRZVXWm2zeM3wWwOd23FG4KBHjNXDz5D4JPNJKkYTV0AaCq7gSmTSuSJGlu+F0AkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFAkqQWGrqPAl5I5uLLgPw+AUnSfHAEQJKkFjIASJLUQgYASZJayAAgSVILDVUASPL5JMuSrEyyuNl2ZJLvJLksySeSnNBsH0tyVpJvNz9PH2z1kiSNjmF7F8BfVtUtSR4GfDvJucC7gH2AO4GvAVc2bT8EfKCqLk6yCPhP4IlTO2yCxGKARYsW9eESJEkafsMWAN6Q5E+b5UcDrwS+XlW3ACQ5A/iDZv9zgV2TrD52qyRbVNVdvR1W1VJgKUCn06l5rl+SpJEwNAEgybPpPqnvV1W/SHIBcB3TvKpvbAQ8taru7U+FkiQtHMN0D8DvAbc2T/67AE8FHg48K8kjkmwCvLin/ZeA169eSbJ3X6uVJGmEDVMAOA/YJMm1wHHAN4EfAX8PXAZcAqwCbm/avwHoJLkqyTXAUX2vWJKkETU0UwBVdR/w/Knbk0xU1dJmBOBs4PNN+5uBw/pbpSRJC8MwjQDM5D1JlgMrgBtoAoAkSVp/QzMCMJOqOmbQNawvv8hHkjSsRmEEQJIkzTEDgCRJLWQAkCSphQwAkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphYb+uwBG2fiSc9frOL9DQJI03xwBkCSphQwAkiS10FAGgCSnJjl0HdqPJ1kxnzVJkrSQDGUAkCRJ82soAkCSVyW5KsmVSf652fzMJN9I8v3VowHpOj7JiiRXJzlsgGVLkjSyBv4ugCS7Ae8EnlZVNyfZBvgHYAdgf2AX4BzgTODPgL2BvYDtgG8nuXAt/S8GFgMsWrRovi5DkqSRMgwjAM8BzqiqmwGq6pZm++er6oGqugbYvtm2P3B6Vd1fVT8Fvg7su6bOq2ppVXWqqjM2NjZPlyBJ0mgZhgAwk/t6ljOwKiRJWoCGIQB8DXhJkm0BmimAmVwEHJZk4yRjwDOBy/pQoyRJC8rA7wGoqpVJ3gd8Pcn9wBVraH42sB9wJVDAW6vqJ0nG571QSZIWkIEHAICq+iTwyTXs36L5XcBbmp/e/auA3eexREmSFpShCAALlZ/pL0kaVsNwD4AkSeozA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZBfBjSPxpecO+u2fnGQJKmfHAGQJKmFDACSJLXQGgNAkq2TvKZZ3jHJmf0pS5Ikzae1jQBsDbwGoKpuqqpD578kSZI039YWAI4DHp9keZIzkqwASHJEks8n+XKSVUlel+TNSa5I8s0k2zTtHp/kvCTLklyUZJepJ2j6+rckFyT5bpK/bbaPJ7kuyWlJrk1yZpLNm32rkhyb5PIkV0/XryRJmtnaAsAS4L+qam/gLVP27Q78GbAv8D7gF1X1h8ClwKuaNkuB11fVk4BjgBNnOM+TgRcDewIvSdJptu8MnFhVTwTuoBmNaNxcVfsAH236nlaSxUkmkkxMTk6u5XIlSWqHDbkJ8PyqurOqJoHbgS80268GxpNsATwNOCPJcuDjwA4z9PXlqvp5Vd0DfA7Yv9l+Y1Vd0ix/umc7TTuAZcD4TEVW1dKq6lRVZ2xsbN2uUJKkBWpDPgfgvp7lB3rWH2j63Qi4rRk9WJuaYX2m7b3nvx8/z0CSpHWythGAO4Et16fjqroDuCHJSwDStdcMzf84yTZJHgYcAqx+1b8oyX7N8iuAi9enFkmS9GBrDABV9XPgkubmv+PXo//DgSOTXAmsBA4GSPKiJO/taXcZcBZwFXBWVU00268HXpvkWuARdOf7JUnSBlrr0HlVvWKabacCp/asj0+3r6puAA6c5vhzgHN6Nv2wqg6Z5vS/rqo/n+b43vNNAM9e81VIkqRezp3PIz/fX5I0rAYeAKaOJvRsX0X3rYaSJGmO+V0AkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFAkqQWMgDMo/El5zK+5NxBlyFJ0u8wAEiS1EIGAEmSWsgAIElSC/UlACQZT7JiPY/dNsn5Se5KcsJc1yZJUhttMugCZuFe4F3A7s2PJEnaQP2cAtgkyWlJrk1yZpLNk6xK8v4kVye5LMlOUw+qqrur6mK6QeA3kmyc5NQkK5rj39S3K5EkacT1MwDsDJxYVU8E7gBe02y/var2AE4APrgO/e0NPLKqdm+OP2W6RkkWJ5lIMjE5ObkB5UuStHD0MwDcWFWXNMufBvZvlk/v+b3fOvT3feBxST6c5EC6oeJ3VNXSqupUVWdsbGx96pYkacHpZwCoGdZrDW1m7qzqVmAv4ALgKOCkDSlOkqQ26WcAWJRk9Sv8VwAXN8uH9fy+dLadJdkO2KiqzgLeCewzV4VKkrTQ9fNdANcDr01yMnAN8FHg9cAjklwF3Ae8HCDJi4BOVb27WV8FbAU8JMkhwPOATYFTkqwOMW/v47VIkjTS+hIAqmoVsMvU7UkAjq+qt01pfw5wTs/6+Axd+6pfkqT1MAqfAzCyVh130KBLkCRpWgMNAGt4ZS9JkuaR3wUgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA8A8Gl9yLuNLzh10GZIk/Q4DgCRJLWQAkCSpheYlACQZT7JiHdofleRVa2lzRJITZtj3N+taoyRJbTYUIwBV9bGq+tQGdGEAkCRpHcxnANg4ySeSrEzypSQPS/L4JOclWZbkoiS7ACR5T5JjmuV9k1yVZHmS46eMJOzYHP/dJO9v2h8HPKxpf9o8Xo8kSQvGfAaAJwAfqardgNuAFwNLgddX1ZOAY4ATpznuFOC/V9XewP1T9u0NHAbsARyW5NFVtQS4p6r2rqrDp3aWZHGSiSQTk5OTc3ZxkiSNsvkMADdU1fJmeRkwDjwNOCPJcuDjwA69ByTZGtiyqi5tNv3LlD6/WlW3V9W9wDXAY9ZWRFUtrapOVXXGxsbW/2okSVpANpnHvu/rWb4f2B64rXllP1d9zmf9kiQtWP28CfAO4IYkLwFI1169DarqNuDOJE9pNr1sln3/Ksmmc1eqJEkLW7/fBXA4cGSSK4GVwMHTtDkS+EQzTfBw4PZZ9LsUuMqbACVJmp1U1aBreJAkW1TVXc3yEmCHqnrjXPTd6XRqYmJiLrqaldUfA7zquIP6dk5JklZLsqyqOtPtG8Y59IOSvJ1ubT8AjhhsOevPJ35J0rAaugBQVZ8FPjvoOiRJWsiG4pMAJUlSfxkAJElqIQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACYR6u/DVCSpGFjAJAkqYUMAJIktdDQB4AkJyXZdQ37j0iyYz9rkiRp1G0y6ALWpqr+ai1NjgBWADfNfzWSJC0MfRsBSPKWJG9olj+Q5GvN8nOSnJbko0kmkqxMcmzPcRck6STZOMmpSVYkuTrJm5IcCnSA05IsT/Kwfl2PJEmjrJ9TABcBz2iWO8AWSTZttl0IvKOqOsCewLOS7Dnl+L2BR1bV7lW1B3BKVZ0JTACHV9XeVXXP1JMmWdwEi4nJycl5ujRJkkZLPwPAMuBJSbYC7gMupRsEnkE3HLw0yeXAFcBuwNR5/+8Dj0vy4SQHAnfM5qRVtbSqOlXVGRsbm6NLkSRptPUtAFTVr4Ab6M7Zf4Puk/4BwE7APcAxwB9V1Z7AucBmU46/FdgLuAA4CjipT6VLkrTg9PtdABfRfaK/sFk+iu4r/q2Au4Hbk2wPPH/qgUm2AzaqqrOAdwL7NLvuBLac/9IlSVo4+v0ugIuAdwCXVtXdSe4FLqqqK5NcAVwH3AhcMs2xjwROSbI6tLy9+X0q8LEk9wD7TXcfgCRJerC+BoCq+iqwac/6H/QsHzHDMc/uWd1nmv1nAWfNWZGSJLXA0H8Q0ChbddxBgy5BkqRpGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJaaOgDQJKjk2zes/7FJFsPsiZJkkbdUASAdM1Uy9HAbwJAVb2gqm7rT2WSJC1MAwsAScaTXJ/kU8AK4J+STCRZmeTYps0bgB2B85Oc32xblWS7ZvnNSVY0P0cP6lokSRo1mwz4/E8A/qKqvplkm6q6JcnGwFeT7FlV/5jkzcABVXVz74FJngS8GngKEOBbSb5eVVdMabcYWAywaNGiflyTJElDb9BTAD+oqm82yy9NcjlwBbAbsOtajt0fOLuq7q6qu4DPAc+Y2qiqllZVp6o6Y2Njc1m7JEkja9AjAHcDJHkscAywb1XdmuRUYLNBFiZJ0kI26BGA1baiGwZuT7I98PyefXcCW05zzEXAIUk2T/Jw4E+bbZIkaS0GPQIAQFVdmeQK4DrgRuCSnt1LgfOS3FRVB/Qcc3kzUnBZs+mkqfP/kiRpeqmqQdfQN51OpyYmJgZdhiRJfZFkWVV1pts3LFMAkiSpjwwAkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFAkqQWMgBIktRCQ/FtgAvV+JJzZ9121XEHzWMlkiQ9mCMAkiS1kAFAkqQWWmMASLJ1ktc0yzsmObM/ZUmSpPm0thGArYHXAFTVTVV16PyXJEmS5tvaAsBxwOOTLE9yRpIVAEmOSPL5JF9OsirJ65K8OckVSb6ZZJum3eOTnJdkWZKLkuwy9QRNX/+W5IIk303yt8328STXJTktybVJzkyyebNvVZJjk1ye5Orp+pUkSTNbWwBYAvxXVe0NvGXKvt2BPwP2Bd4H/KKq/hC4FHhV02Yp8PqqehJwDHDiDOd5MvBiYE/gJUk6zfadgROr6onAHTSjEY2bq2of4KNN39NKsjjJRJKJycnJtVyuJEntsCE3AZ5fVXdW1SRwO/CFZvvVwHiSLYCnAWckWQ58HNhhhr6+XFU/r6p7gM8B+zfbb6yqS5rlT/dsp2kHsAwYn6nIqlpaVZ2q6oyNja3bFUqStEBtyOcA3Nez/EDP+gNNvxsBtzWjB2tTM6zPtL33/Pfj5xlIkrRO1jYCcCew5fp0XFV3ADckeQlAuvaaofkfJ9kmycOAQ4DVr/oXJdmvWX4FcPH61CJJkh5sjQGgqn4OXNLc/Hf8evR/OHBkkiuBlcDBAElelOS9Pe0uA84CrgLOqqqJZvv1wGuTXAs8gu58vyRJ2kBrHTqvqldMs+1U4NSe9fHp9lXVDcCB0xx/DnBOz6YfVtUh05z+11X159Mc33u+CeDZa74KSZLUy08ClCSphVI19T67havT6dTExMTaG0qStAAkWVZVnen2OQIgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJhH40vOZXzJuYMuQ5Kk32EAkCSphQwAkiS1UF8CQJLxJCvW89htk5yf5K4kJ8x1bZIktdEmgy5gFu4F3gXs3vxIkqQN1M8pgE2SnJbk2iRnJtk8yaok709ydZLLkuw09aCquruqLqYbBH4jycZJTk2yojn+TX27EkmSRlw/A8DOwIlV9UTgDuA1zfbbq2oP4ATgg+vQ397AI6tq9+b4U6ZrlGRxkokkE5OTkxtQviRJC0c/A8CNVXVJs/xpYP9m+fSe3/utQ3/fBx6X5MNJDqQbKn5HVS2tqk5VdcbGxtanbkmSFpx+BoCaYb3W0GbmzqpuBfYCLgCOAk7akOIkSWqTfgaARUlWv8J/BXBxs3xYz+9LZ9tZku2AjarqLOCdwD5zVagkSQtdP98FcD3w2iQnA9cAHwVeDzwiyVXAfcDLAZK8COhU1bub9VXAVsBDkhwCPE86j1cAABSeSURBVA/YFDglyeoQ8/Y+XoskSSOtLwGgqlYBu0zdngTg+Kp625T25wDn9KyPz9C1r/olSVoPo/A5ACNr1XEHDboESZKmNdAAsIZX9pIkaR75XQCSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EIGgHk0vuRcxpecO+gyJEn6HQYASZJayAAgSVILzUsASDKeZMU6tD8qyavW0uaIJCfMsO9v1rVGSZLabChGAKrqY1X1qQ3owgAgSdI6mM8AsHGSTyRZmeRLSR6W5PFJzkuyLMlFSXYBSPKeJMc0y/smuSrJ8iTHTxlJ2LE5/rtJ3t+0Pw54WNP+tHm8HkmSFoz5DABPAD5SVbsBtwEvBpYCr6+qJwHHACdOc9wpwH+vqr2B+6fs2xs4DNgDOCzJo6tqCXBPVe1dVYdP7SzJ4iQTSSYmJyfn7OIkSRpl8xkAbqiq5c3yMmAceBpwRpLlwMeBHXoPSLI1sGVVXdps+pcpfX61qm6vqnuBa4DHrK2IqlpaVZ2q6oyNja3/1UiStIBsMo9939ezfD+wPXBb88p+rvqcz/olSVqw+nkT4B3ADUleApCuvXobVNVtwJ1JntJsetks+/5Vkk3nrlRJkha2fr8L4HDgyCRXAiuBg6dpcyTwiWaa4OHA7bPodylwlTcBSpI0O6mqQdfwIEm2qKq7muUlwA5V9ca56LvT6dTExMRcdDUrqz8GeNVxB/XtnJIkrZZkWVV1pts3jHPoByV5O93afgAcMdhy1p9P/JKkYTV0AaCqPgt8dtB1SJK0kA3FJwFKkqT+MgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFAkqQWMgBIktRCBoB5tPrLgCRJGjYGAEmSWsgAIElSCw19AEhyUpJd17D/iCQ79rMmSZJG3dB9HfBUVfVXa2lyBLACuGn+q5EkaWHo2whAkrckeUOz/IEkX2uWn5PktCQfTTKRZGWSY3uOuyBJJ8nGSU5NsiLJ1UnelORQoAOclmR5kof163okSRpl/ZwCuAh4RrPcAbZIsmmz7ULgHVXVAfYEnpVkzynH7w08sqp2r6o9gFOq6kxgAji8qvauqnumnjTJ4iZYTExOTs7TpUmSNFr6GQCWAU9KshVwH3Ap3SDwDLrh4KVJLgeuAHYDps77fx94XJIPJzkQuGM2J62qpVXVqarO2NjYHF2KJEmjrW8BoKp+BdxAd87+G3Sf9A8AdgLuAY4B/qiq9gTOBTabcvytwF7ABcBRwEl9Kl2SpAWn3+8CuIjuE/2FzfJRdF/xbwXcDdyeZHvg+VMPTLIdsFFVnQW8E9in2XUnsOX8ly5J0sLR73cBXAS8A7i0qu5Oci9wUVVdmeQK4DrgRuCSaY59JHBKktWh5e3N71OBjyW5B9hvuvsAJEnSg/U1AFTVV4FNe9b/oGf5iBmOeXbP6j7T7D8LOGvOipQkqQWG/oOAJEnS3DMAzKNVxx006BIkSZqWAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktNPQBIMnRSTbvWf9ikq0HWZMkSaNuKAJAumaq5WjgNwGgql5QVbf1pzJJkhamgQWAJONJrk/yKWAF8E9JJpKsTHJs0+YNwI7A+UnOb7atSrJds/zmJCuan6MHdS2SJI2aTQZ8/icAf1FV30yyTVXdkmRj4KtJ9qyqf0zyZuCAqrq598AkTwJeDTwFCPCtJF+vqiumtFsMLAZYtGhRP65JkqShN+gpgB9U1Teb5ZcmuRy4AtgN2HUtx+4PnF1Vd1fVXcDngGdMbVRVS6uqU1WdsbGxuaxdkqSRNegRgLsBkjwWOAbYt6puTXIqsNkgC5MkaSEb9AjAalvRDQO3J9keeH7PvjuBLac55iLgkCSbJ3k48KfNNkmStBaDHgEAoKquTHIFcB1wI3BJz+6lwHlJbqqqA3qOubwZKbis2XTS1Pl/SZI0vVTVoGvom06nUxMTE4MuQ5KkvkiyrKo60+0blikASZLURwYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFhrqAJDk1CSHDroOSZIWmqEOAOsqySaDrkGSpFEwZwEgybuSXJ/k4iSnJzkmyeOTnJdkWZKLkuzStD01yT8m+UaS769+lZ+uE5p+vgL8fk//T0ry9aav/0yyQ7P9giQfTDIBvHGurkeSpIVsTl4xJ9kXeDGwF7ApcDmwDFgKHFVV303yFOBE4DnNYTsA+wO7AOcAZwJ/CuwM7ApsD1wDnJxkU+DDwMFVNZnkMOB9wF82fT2kqjoz1LYYWAywaNGiubhcSZJG3lwNmT8d+Lequhe4N8kXgM2ApwFnJFnd7qE9x3y+qh4ArkmyfbPtmcDpVXU/cFOSrzXbdwZ2B77c9LUx8OOevj47U2FVtZRuEKHT6dT6X6IkSQvHfM6ZbwTcVlV7z7D/vp7lzNCmd//Kqtpvhv13r2txkiS12VzdA3AJ8CdJNkuyBfBC4BfADUleAr+Z399rLf1cCByWZONmjv+AZvv1wFiS/Zq+Nk2y2xzVLklS68xJAKiqb9Odx78K+A/gauB24HDgyCRXAiuBg9fS1dnAd+nO/X8KuLTp/5fAocD/bvpaTnd6QZIkrYdUzc20eJItququJJvTfSW/uKoun5PO50in06mJiYlBlyFJUl8kWTbTTfJzeQ/A0iS70r3575PD9uQvSZJ+a84CQFW9Yq76kiRJ82tBfRKgJEmaHQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EIGAEmSWsgAIElSCxkAJElqIQOAJEktZACQJKmFDACSJLWQAUCSpBYyAEiS1EJDGQCSjCdZMc329yZ57iBqkiRpIdlk0AWsi6p696BrkCRpIRjKEYDGxkk+kWRlki8leViSU5McCpBkVZL3J7k6yWVJdhp0wZIkjYphDgBPAD5SVbsBtwEvnqbN7VW1B3AC8MHpOkmyOMlEkonJycn5q1aSpBEyzAHghqpa3iwvA8anaXN6z+/9puukqpZWVaeqOmNjY3NfpSRJI2iYA8B9Pcv3M/39CjXDsiRJWoNhDgCzcVjP70sHWYgkSaNkpN4FMI1HJLmK7mjBywddjCRJo2IoA0BVrQJ271n/PzM0Pb6q3taXoiRJWkBGfQpAkiSth6EcAZiNqhofdA2SJI0qRwAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFlqvAJDkrrksIskhSXbtWX9vkufO5TkkSdJvDcsIwCHAbwJAVb27qr4ywHokSVrQNigApOv4JCuSXJ3ksJ59b2u2XZnkuGbbXyf5drPtrCSbJ3ka8CLg+CTLkzw+yalJDm2O+aMkVzR9nZzkoc32VUmOTXJ5s2+XDbkWSZLaZENHAP4M2BvYC3gu3SfxHZI8HzgYeEpV7QW8v2n/uarat9l2LXBkVX0DOAd4S1XtXVX/tbrzJJsBpwKHVdUewCbA/+g5/81VtQ/wUeCY6QpMsjjJRJKJycnJDbxcSZIWhg0NAPsDp1fV/VX1U+DrwL50w8ApVfULgKq6pWm/e5KLklwNHA7stpb+dwZuqKrvNOufBJ7Zs/9zze9lwPh0HVTV0qrqVFVnbGxs3a5OkqQFqt/3AJwKvK55NX8ssNkG9ndf8/t+uqMDkiRpFjY0AFwEHJZk4yRjdF+dXwZ8GXh1ks0BkmzTtN8S+HGSTemOAKx2Z7NvquuB8SQ7NeuvpDvKIEmSNsCGBoCzgauAK4GvAW+tqp9U1Xl05/Unkiznt/Pz7wK+BVwCXNfTz2eAtzQ3+z1+9caquhd4NXBGM23wAPCxDaxZkqTWS1UNuoa+6XQ6NTExMegyJEnqiyTLqqoz3b5h+RwASZLURwYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQgYASZJayAAgSVILGQAkSWohA4AkSS1kAJAkqYUMAJIktZABQJKkFhp4AEhyUpJd19Lm1CSHTrN9PMkr5q86SZIWpoEHgKr6q6q6Zj0PHwcMAJIkraM5CwBJ3pLkDc3yB5J8rVl+TpLTkjwvyaVJLk9yRpItmv0XJOk0y0cm+U6Sy5J8IskJPad4ZpJvJPl+z2jAccAzkixP8qa5uhZJkha6uRwBuAh4RrPcAbZIsmmz7SrgncBzq2ofYAJ4c+/BSXYE3gU8FXg6sMuU/ncA9gdeSPeJH2AJcFFV7V1VH5iuqCSLk0wkmZicnNzAS5QkaWGYywCwDHhSkq2A+4BL6QaBZwD3ALsClyRZDvwF8Jgpxz8Z+HpV3VJVvwLOmLL/81X1QDNdsP1si6qqpVXVqarO2NjYel2YJEkLzSZz1VFV/SrJDcARwDfovuo/ANgJuAH4clW9fANOcV/PcjagH0mSWm+ubwK8CDgGuLBZPgq4Avgm8PQkOwEkeXiSP5hy7LeBZyV5RJJNgBfP4nx3AlvOVfGSJLXFfASAHYBLq+qnwL105+gn6Y4MnJ7kKrrTAw+a46+qHwF/D1wGXAKsAm5fy/muAu5PcqU3AUqSNHupqkHX8BtJtqiqu5oRgLOBk6vq7Lnqv9Pp1MTExFx1J0nSUEuyrKo60+0b+OcATPGe5ibBFXTvG/j8gOuRJGlBmrObAOdCVR0z6BokSWqDYRsBkCRJfWAAkCSphQwAkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFgHowvOZfxJecOugxJkmZkAJAkqYUMAJIktdC8B4Ak40lWrOex2yY5P8ldSU5YQ7sj1rRfkiQ92CaDLmAt7gXeBeze/EiSpDnQrymATZKcluTaJGcm2TzJqiTvT3J1ksuS7DT1oKq6u6ouphsEHiTJq5N8J8llwNP7cRGSJC0U/QoAOwMnVtUTgTuA1zTbb6+qPYATgA/OtrMkOwDH0n3i3x/YdQ1tFyeZSDIxOTm5vvVLkrSg9CsA3FhVlzTLn6b7pA1wes/v/dahv6cAF1TVZFX9EvjsTA2ramlVdaqqMzY2tq51S5K0IPUrANQM67WGNpIkaZ70KwAsSrL6Ff4rgIub5cN6fl+6Dv19C3hW8y6BTYGXzE2ZkiS1Q7/eBXA98NokJwPXAB8FXg88IslVwH3AywGSvAjoVNW7m/VVwFbAQ5IcAjyvqq5J8h66oeE2YHmfrkOSpAVh3gNAVa0Cdpm6PQnA8VX1tintzwHO6Vkfn6HfU4BT5rBUSZJaY9g/B2AkrTruoEGXIEnSGg0sAMz0yl6SJM0/vwtAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaiEDgCRJLWQAkCSphQwAkiS1kAFAkqQWMgBIktRCfhfABhhfcu4a9/udAJKkYeUIgCRJLWQAkCSphYYyACQZT7Jitm2SPDvJv/enOkmSRt9QBgBJkjS/hvkmwI2TfAJ4GvAj4GBgV+DkZv+XBlWYJEmjbphHAJ4AfKSqdgNuA14MnAK8vqr2mm0nSRYnmUgyMTk5OU+lSpI0WoY5ANxQVcub5WXAOLB1VV3YbPvn2XRSVUurqlNVnbGxsXkoU5Kk0TPMAeC+nuX7ge0GVYgkSQvNMAeAqW4Dbkuyf7N++CCLkSRplI1SAAB4NfCRJMuBDLoYSZJG1VC+C6CqVgG796z/n57dvTcAvrXZfwFwQR9KkyRpQRi1EQBJkjQHhnIEYFT4ZT+SpFHlCIAkSS1kAJAkqYUMAJIktZABQJKkFjIASJLUQqmqQdfQN0kmgR/08ZTbATf38XyjxMdmzXx8ZuZjs2Y+PjNr42PzmKqa9otwWhUA+i3JRFV1Bl3HMPKxWTMfn5n52KyZj8/MfGwezCkASZJayAAgSVILGQDm19JBFzDEfGzWzMdnZj42a+bjMzMfmx7eAyBJUgs5AiBJUgsZACRJaiEDwDxIcmCS65N8L8mSQdczTJKcnORnSVYMupZhk+TRSc5Pck2SlUneOOiahkmSzZJcluTK5vE5dtA1DZskGye5Ism/D7qWYZNkVZKrkyxPMjHoeoaB9wDMsSQbA98B/hj4IfBt4OVVdc1ACxsSSZ4J3AV8qqp2H3Q9wyTJDsAOVXV5ki2BZcAh/rfTlSTAw6vqriSbAhcDb6yqbw64tKGR5M1AB9iqql446HqGSZJVQKeq2vZBQDNyBGDuPRn4XlV9v6p+CXwGOHjANQ2NqroQuGXQdQyjqvpxVV3eLN8JXAs8crBVDY/quqtZ3bT58RVMI8mjgIOAkwZdi0aDAWDuPRK4sWf9h/iPuNZRknHgD4FvDbaS4dIMcS8HfgZ8uap8fH7rg8BbgQcGXciQKuBLSZYlWTzoYoaBAUAaMkm2AM4Cjq6qOwZdzzCpqvuram/gUcCTkziNBCR5IfCzqlo26FqG2P5VtQ/wfOC1zXRkqxkA5t6PgEf3rD+q2SatVTO3fRZwWlV9btD1DKuqug04Hzhw0LUMiacDL2rmuT8DPCfJpwdb0nCpqh81v38GnE13urbVDABz79vAE5I8NslDgJcB5wy4Jo2A5ia3fwKurap/GHQ9wybJWJKtm+WH0b3R9rrBVjUcqurtVfWoqhqn+2/O16rqzwdc1tBI8vDmxlqSPBx4HtD6dyIZAOZYVf0aeB3wn3Rv4vrXqlo52KqGR5LTgUuBnZP8MMmRg65piDwdeCXdV2/Lm58XDLqoIbIDcH6Sq+gG7S9XlW9302xsD1yc5ErgMuDcqjpvwDUNnG8DlCSphRwBkCSphQwAkiS1kAFAkqQWMgBIktRCBgBJklrIACBJUgsZACRJaqH/H6QuTbLFOdOnAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 576x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"nJV5zefS3QS2"},"source":["### XGBRegressor"]},{"cell_type":"code","metadata":{"id":"Mm8JOHVN3ORd","executionInfo":{"status":"ok","timestamp":1625477772206,"user_tz":-330,"elapsed":19,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# XGBRegressor\n","coef = pd.Series(xgb_best_model.feature_importances_, index = x_train.columns)"],"execution_count":87,"outputs":[]},{"cell_type":"code","metadata":{"id":"CgZeQqPj3ORf","executionInfo":{"status":"ok","timestamp":1625477772206,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["imp_coef = pd.concat([coef.sort_values().head(11),\n","                     coef.sort_values().tail(11)])"],"execution_count":88,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"0Y8zuZaK3ORf","executionInfo":{"status":"ok","timestamp":1625477772207,"user_tz":-330,"elapsed":19,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"e7779a90-7a14-4fd5-9cb9-d395ef4961c9"},"source":["matplotlib.rcParams['figure.figsize'] = (8.0, 10.0)\n","imp_coef.plot(kind = \"barh\")\n","plt.title(\"Coefficients in the Lasso Model\")"],"execution_count":89,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Coefficients in the Lasso Model')"]},"metadata":{"tags":[]},"execution_count":89},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"WJoAqGXf35nh"},"source":["##  Random forest"]},{"cell_type":"code","metadata":{"id":"qDWFlGjB4FHp","executionInfo":{"status":"ok","timestamp":1625477772207,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Random forest\n","coef = pd.Series(rf.feature_importances_, index = x_train.columns)"],"execution_count":90,"outputs":[]},{"cell_type":"code","metadata":{"id":"g_AyX0oW4FHq","executionInfo":{"status":"ok","timestamp":1625477772207,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["imp_coef = pd.concat([coef.sort_values().head(11),\n","                     coef.sort_values().tail(11)])"],"execution_count":91,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"mb4-azlA4FHq","executionInfo":{"status":"ok","timestamp":1625477772208,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"e88088d9-9b67-428f-f54b-d70588aca5f5"},"source":["matplotlib.rcParams['figure.figsize'] = (8.0, 10.0)\n","imp_coef.plot(kind = \"barh\")\n","plt.title(\"Coefficients in the Lasso Model\")"],"execution_count":92,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Coefficients in the Lasso Model')"]},"metadata":{"tags":[]},"execution_count":92},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"LE5MiSoZ4exO"},"source":["### Ridge Important features"]},{"cell_type":"code","metadata":{"id":"7QnapuJd4exS","executionInfo":{"status":"ok","timestamp":1625477772208,"user_tz":-330,"elapsed":16,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["# Ridge\n","coef = pd.Series(Ridge_best_model.coef_, index = x_train.columns)"],"execution_count":93,"outputs":[]},{"cell_type":"code","metadata":{"id":"jnN6w67K4exT","executionInfo":{"status":"ok","timestamp":1625477772208,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["imp_coef = pd.concat([coef.sort_values().head(11),\n","                     coef.sort_values().tail(11)])"],"execution_count":94,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"J5qu8lA14exT","executionInfo":{"status":"ok","timestamp":1625477772209,"user_tz":-330,"elapsed":16,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"26fb624e-990d-4c3e-8ee9-236c4f3addad"},"source":["matplotlib.rcParams['figure.figsize'] = (8.0, 10.0)\n","imp_coef.plot(kind = \"barh\")\n","plt.title(\"Coefficients in the Ridge Model\")"],"execution_count":95,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Coefficients in the Ridge Model')"]},"metadata":{"tags":[]},"execution_count":95},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"p0dXGGJIJimi","executionInfo":{"status":"ok","timestamp":1625477772209,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"cc8752b7-c998-4b0f-eaee-eb94aa555796"},"source":["x_train.columns"],"execution_count":96,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index([    'chol', 'stab.glu',      'hdl',    'ratio', 'location',      'age',\n","         'gender',   'height',   'weight',    'bp.1s',    'bp.1d',    'waist',\n","            'hip', 'time.ppn',          0,          1,          2],\n","      dtype='object')"]},"metadata":{"tags":[]},"execution_count":96}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"g_-lL2WjJn5U","executionInfo":{"status":"ok","timestamp":1625477772209,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6376aaa6-76eb-41f4-b0e2-c98bbd3380ec"},"source":["y_train"],"execution_count":97,"outputs":[{"output_type":"execute_result","data":{"text/plain":["353    4.88\n","233    4.34\n","3      4.63\n","18     5.28\n","131    4.79\n","       ... \n","71     5.23\n","106    5.17\n","270    4.62\n","348    3.98\n","102    5.44\n","Name: glyhb, Length: 322, dtype: float64"]},"metadata":{"tags":[]},"execution_count":97}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"3m3Yv-T2_Tls","executionInfo":{"status":"ok","timestamp":1625477773188,"user_tz":-330,"elapsed":992,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"ff8f3754-8b8d-430e-e59a-891d2c465665"},"source":["plt.figure(figsize=(20,10))\n","sns.jointplot(x=x_train[2],y=y_train,kind=\"reg\")\n","plt.show()"],"execution_count":98,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1440x720 with 0 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"v-vRR12tL6sy","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1625477774799,"user_tz":-330,"elapsed":1616,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"09e00608-e686-45e2-837d-df035b52a0a0"},"source":["# Plot for mse \n","from matplotlib import pyplot\n","from sklearn.metrics import mean_squared_error\n","# real value\n","expected = y_test.to_numpy()\n","# predicted value\n","predicted = Ensemble_average_prediction_2\n","# calculate errors\n","errors = list()\n","for i in range(len(expected)):\n","\t# calculate error\n","\terr = (expected[i] - predicted[i])**2\n","\t# store error\n","\terrors.append(err)\n","\t# report error\n","\tprint('>%.1f, %.1f = %.3f' % (expected[i], predicted[i], err))\n","# plot errors\n","pyplot.plot(errors)\n","pyplot.xticks(ticks=[i for i in range(len(errors))], labels=predicted)\n","pyplot.xlabel('Predicted Value')\n","pyplot.ylabel('Mean Squared Error')\n","plt.xticks(rotation = 90)\n","pyplot.show()"],"execution_count":99,"outputs":[{"output_type":"stream","text":[">4.6, 5.1 = 0.240\n",">4.9, 6.5 = 2.536\n",">4.4, 5.8 = 1.780\n",">5.7, 5.4 = 0.053\n",">4.4, 4.7 = 0.111\n",">4.3, 5.3 = 1.120\n",">6.5, 6.7 = 0.051\n",">5.0, 5.1 = 0.009\n",">9.3, 8.8 = 0.209\n",">7.2, 6.5 = 0.474\n",">10.1, 10.5 = 0.209\n",">3.9, 4.5 = 0.317\n",">4.7, 4.3 = 0.111\n",">4.7, 5.2 = 0.251\n",">13.0, 11.8 = 1.430\n",">5.1, 5.9 = 0.652\n",">8.8, 7.0 = 3.277\n",">5.4, 5.4 = 0.000\n",">5.8, 5.5 = 0.094\n",">4.3, 4.7 = 0.157\n",">6.3, 4.9 = 2.180\n",">16.1, 12.5 = 13.077\n",">4.1, 4.8 = 0.446\n",">5.4, 5.3 = 0.004\n",">4.8, 5.3 = 0.198\n",">6.8, 6.2 = 0.393\n",">5.3, 5.1 = 0.021\n",">10.1, 9.6 = 0.264\n",">5.0, 5.1 = 0.024\n",">3.4, 4.8 = 1.955\n",">5.1, 5.0 = 0.003\n",">4.8, 3.6 = 1.605\n",">4.3, 5.1 = 0.601\n",">4.8, 4.3 = 0.328\n",">4.2, 5.0 = 0.518\n",">4.7, 5.0 = 0.084\n",">5.2, 6.7 = 2.145\n",">4.2, 4.5 = 0.106\n",">5.5, 5.0 = 0.241\n",">4.9, 3.9 = 1.050\n",">5.0, 5.5 = 0.209\n",">4.8, 5.0 = 0.028\n",">4.9, 5.4 = 0.229\n",">4.3, 4.0 = 0.128\n",">4.1, 4.8 = 0.496\n",">3.0, 4.2 = 1.378\n",">4.2, 4.5 = 0.119\n",">6.5, 5.6 = 0.694\n",">11.6, 12.0 = 0.173\n",">3.8, 4.6 = 0.640\n",">4.0, 5.4 = 1.816\n",">12.7, 10.4 = 5.483\n",">4.8, 5.6 = 0.632\n",">6.1, 8.7 = 6.706\n",">5.5, 6.6 = 1.209\n",">3.6, 4.8 = 1.291\n",">5.2, 4.7 = 0.232\n",">4.4, 3.6 = 0.660\n",">7.9, 9.1 = 1.469\n",">4.4, 4.2 = 0.035\n",">5.0, 5.4 = 0.150\n",">4.4, 4.2 = 0.052\n",">5.1, 5.7 = 0.313\n",">4.9, 6.7 = 3.422\n",">3.8, 4.6 = 0.688\n",">4.8, 5.4 = 0.328\n",">4.4, 5.5 = 1.193\n",">9.8, 8.3 = 2.223\n",">4.5, 5.2 = 0.468\n",">4.3, 4.0 = 0.129\n",">5.7, 5.6 = 0.032\n",">4.4, 4.5 = 0.012\n",">5.5, 6.0 = 0.233\n",">7.4, 6.1 = 1.618\n",">4.8, 4.7 = 0.006\n",">4.8, 5.1 = 0.102\n",">4.4, 3.7 = 0.523\n",">5.0, 4.9 = 0.007\n",">7.5, 6.6 = 0.797\n",">5.1, 5.6 = 0.276\n",">9.4, 6.3 = 9.416\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAe4AAAKyCAYAAAATsz1HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzde5Qk2V0f+O+NyEdV1qO7q7u6ex4tjUbzEsiYx2AEGPDysg5g8NqwBoQXY7zyOWCQ2V1jOAZsr30wZ9drLXsM9pHF26x2jQyLjo0BIZC0u5IljR4GiZG6Z3oePdM93dVd3VWVVfmIiHv3j4gbGRkZERmZGRlxc+L7OUdnuqtLUzEzVfnL3+/+7u8nlFIgIiKi1WBV/QBERESUHwM3ERHRCmHgJiIiWiEM3ERERCuEgZuIiGiFMHATERGtkEbVD5DHuXPn1EMPPVT1YxAREZXi4x//+G2l1G7Sn61E4H7ooYfw1FNPVf0YREREpRBCvJD2ZyyVExERrRAGbiIiohXCwE1ERLRCGLiJiIhWCAM3ERHRCmHgJiIiWiEM3ERERCuEgZuIiGiFMHATERGtEAZuIiKiFcLATUREtEIYuImIiFYIAzcREdEKYeAmIiJaIQzcREREK4SBm4iIaIUwcBMREa0QBm4iIqIVwsBNRES0Qhi4iYiIVggDNxER0Qph4CZj7R8PMXRl1Y9BRGQUBm4y1je+/YP41Q8/X/VjEBEZhYGbjHW7O8Dt7rDqxyAiMgoDNxlJSgUAUEpV/CRERGZh4CYjeUHA9iQDNxFRFAM3GUkHbI8ZNxHRGAZuMpIXlsorfhAiIsMwcJORWConIkrGwE1GkiyVExElYuAmI+lMWzLjJiIaw8BNRtKZtmTGTUQ0hoGbjCSDSaceJ54SEY1h4CYjuUHkZsZNRDSOgZuMpDNuBm4ionEM3GQkXgcjIkrGwE1GCrvKmXETEY1h4CYjSWbcRESJGLjJSKOMu+IHISIyDAM3GYkDWIiIkjFwk5G4HYyIKBkDNxlpNDmt4gchIjIMAzcZSbJUTkSUiIGbjBSWyhm4iYjGMHCTkcIBLDzjJiIaw8BNRtIjTxUDNxHRGAZuMpJeMsJSORHROAZuMlI4OY1xm4hoDAM3GUnv4WZXORHROAZuMhKXjBARJWPgJiNxyQgRUTIGbjISM24iomQM3GQkyZGnRESJGLjJSK7HkadEREkYuMlInJxGRJSMgZuMJDmrnIgoEQM3GUln2ky4iYjGMXCTkZhxExElY+AmI4VrPZlyExGNYeAmI7lSl8oZuImIopYWuIUQvyiEuCWE+HTkY/+LEOKzQog/FkL8lhDi9LK+Pq02Tk4jIkq2zIz7lwG8Ofax9wJ4o1LqCwBcBvDjS/z6tML0khEGbiKicUsL3EqpDwLYj33s95VSbvDb/wzgwWV9fVptnJxGRJSsyjPuvwngP6X9oRDirUKIp4QQT+3t7ZX4WGQCzionIkpWSeAWQvwDAC6AX0/7HKXUO5RSTyqlntzd3S3v4cgIHq+DERElapT9BYUQfwPAtwD4OsWWYUoxKpXzW4SIKKrUwC2EeDOAHwXwNUqpkzK/Nq0WV/KMm4goyTKvg70LwIcBPC6EeEkI8f0A/iWALQDvFUJ8Sgjxr5f19Wm1cXIaEVGypWXcSqnvSvjwLyzr69GrSzRgS6lgWaLCpyEiMgcnp5GRoqNOOfaUiGiEgZuMJKMZNwM3EVGIgZuMFM2ypazwQYiIDMPATUaKnnGzVE5ENMLATUYaC9zsLCciCjFwk5G8SHmcc3qIiEYYuMlI0YY0ZtxERCMM3GQknnETESVj4CYjRYM14zYR0QgDNxnJ81gqJyJKwsBNRvJ4xk1ElIiBm4zEyWlERMkYuMlIY5PTGLeJiEIM3GQkDmAhIkrGwE1GkoqlciKiJAzcZCSPZ9xERIkYuMlILJUTESVj4CYjjWXcXOtJRBRi4CYjReavcOQpEVEEAzcZSUoFSwS/ZuAmIgoxcJORPKnQtP1vT8kzbiKiEAM3GUkqhVYQuNmcRkQ0wsBNRnKlQrMRZNyM20REIQZuMpKUCk3bP+TmGTcR0QgDNxnJU6MzbpbKiYhGGLjJSJ6MnHEz4yYiCjFwk5GkVGgEpXLFwE1EFGLgJiONl8orfhgiIoMwcJORPAmecRMRJWDgJiN5UoZn3CyVExGNMHCTkTyp0Gz4Z9xsTiMiGmHgJiNJxVI5EVESBm4y0tiscmbcREQhBm4ykheZVc593EREIwzcZKToPW6ecRMRjTBwk5FcrvUkIkrEwE3G0YG6yZGnREQTGLjJODpQt8LtYFU+DRGRWRi4yTheLONmqZyIaISBm4yjr381G7zHTUQUx8BNxpnIuHnGTUQUYuAm4+h7201Ln3EzcBMRaQzcZBw3iNyjUnmVT0NEZBYGbjKO7ipnqZyIaBIDNxlHl8rD62BsTiMiCjFwk3HiGTcHsBARjTBwk3F0hm1bzLiJiOIYuMk4XiRw25bg5DQioggGbjKOGw3cQrBUTkQUwcBNxtFd5LYlIARL5UREUQzcZJywVC78UjlHnhIRjTBwk3F0oLaCUjnjNhHRCAM3GScslYugVM4zbiKiEAM3GSfeVc5SORHRCAM3GUdn2FZ4HYyBm4hIY+Am47ieH6gbloAlGLiJiKIYuMk4+t62JfzAzVI5EdEIAzcZRy8ZGZ1xV/s8REQmYeAm43jhABbAsgDFUjkRUYiBm4yjJ6WFpXIGbiKiEAM3GceLzyrnGTcRUYiBm4zjRjNuXgcjIhrDwE3G0YG6YQcjT9mcRkQUYuAm40SXjAgBnnETEUUwcJNxJian8YybiCjEwE3Gia/15Bk3EdHI0gK3EOIXhRC3hBCfjnxsRwjxXiHEleCvZ5b19Wl1RbvK/etgFT8QEZFBlplx/zKAN8c+9mMA3qeUehTA+4LfE42JlsotAZbKiYgilha4lVIfBLAf+/C3AfiV4Ne/AuAvL+vr0+rS18EaXOtJRDSh7DPuC0qpG8GvXwFwoeSvTysgPjmNZ9xERCOVNacpfwB16iuyEOKtQoinhBBP7e3tlfhkVLX4GTcDNxHRSNmB+6YQ4j4ACP56K+0TlVLvUEo9qZR6cnd3t7QHpOrpZjTdVc5SORHRSNmB+z0Avjf49fcC+O2Svz6tgLBUbiEYeVrxAxERGWSZ18HeBeDDAB4XQrwkhPh+AD8D4BuEEFcAfH3we6Ixo7WeArYAS+VERBGNZf2NlVLflfJHX7esr0mvDl58rSdTbiKiECenkXG8yHUwi2fcRERjGLjJOPF93KyUExGNMHCTcaRSEAIQQsCyuB2MiCiKgZuM40kFWwgA/jk3R54SEY0wcJNxPKVgWX7g5nYwIqJxDNxkHBnJuG0hWConIopg4CbjuFKhEWTcQghIWfEDEREZhIGbjCNltFQOXgcjIopg4CbjeErB5hk3EVEiBm4yjif9bnIgKJUzcBMRhRi4yThSKtjBd6bNkadERGMYuMk4nop0lXPkKRHRGAZuMo4XaU6zOPKUiGgMAzcZx4tcB7MER54SEUUxcJNx4pPTWConIhph4CbjRCenWRZL5UREUQzcZBxPju5xs1RORKb7++/+Y/yNX/poaV+PgZuMI5UK73HzOhgRmW6vO8Cd7rC0r8fATcYZy7iDv3K1JxGZyo3chCkDAzcZx40Ebn3WzelpRGQqGbkJUwYGbjKOVJMZN8+5ichUrpTha1YZGLjJOF60q1xn3FztSUSG8phxU91JCVh6VnnwV5bKichU0eO9MjBwk3Giaz11xs1SORGZSjJwU915cnQdbFQqZ+AmIjO5LJVT3UWvg+m/8i43EZnKY8ZNdTe2ZETf42bcJiJD8Yybai86OU3/LLA5jYhM5Z9xlxdOGbjJOF7CABaWyonIVDzjptqLrvUclcoZuInITDzjptqLrvW0OYCFiAznShm+VpWBgZuMM3aP2xp9jIjIRJ4EbJuBm2rM8xIGsPCMm4gM5UnJM26qN09FSuXBD4Nixk1EhuJ1MKo9T46a0jjylIhMF12MVAYGbjKOv9bT/zVL5URkOk8qnnFTvUXfveryE7vKichUXOtJtSfl6B4313oSkcmUUsEZNyenUY25kYxb8IybiAymT/F4xk215qnReZHNtZ5EZDA3OMdr8Iyb6kwmnXEzbhORgXT/Da+DUa1FJ6fp6hO7yonIRGHGzcBNdaWUglKja2BhqZxn3ERkIJ1UMOOm2or/EOi/MuMmIhO5DNxUd/EfAq71JCKTSQZuqjsdoONLRhi4ichEOtngGTfVVlgqj51xe5ycRkQGGh3vcQAL1ZS+WmHF9nEz4yYiE42O98r7mgzcZBQ9IU3PMrA4gIWIDMaMm2ovtaucGTcRGcjjGTfVnS6JT+zjZsZNRAbSA1jYVU61Fe/Q1D8MTLiJyETxhtoyMHCTUfRZts60LY48JSKDhYGbS0aoruJn3BbXehKRwXjGTbXnqeTmNMXATUQG4shTqr14qXw0q7yyRyIiSsUzbqq9eMYdrvVkxk1EBgpL5TzjprpyvVjGzQEsRGQwDmCh2tP3uOPXwTjylIhMxCUjVHvxrnLBASxEZDAvGMBi8Yyb6io+OY0ZNxGZTDfO8oybakv/EHCtJxGtAo48pdrTJXHd58G1nkRkMg5godqTavxOJNd6EpHJOICFas+N3Ym0OfKUiAwmGbip7iaWjITNaZU9EhFRKmbcVHvx62CAvyGMpXIiMtHojPtVPoBFCPEjQojPCCE+LYR4lxBirYrnIPPoknj0TqRtCZbKichItci4hRAPAPhhAE8qpd4IwAbwnWU/B5kp6bzIEoIZNxEZyavRdbAGgHUhRANAB8D1ip6DDBNfMqJ/zetgRGSicADLqzlwK6VeBvDPAbwI4AaAA6XU78c/TwjxViHEU0KIp/b29sp+TKqIJydL5ZYQHMBCREaqRcYthDgD4NsAvA7A/QA2hBDfE/88pdQ7lFJPKqWe3N3dLfsxqSJJwwwswQEsRGQmtyb7uL8ewHNKqT2llAPgNwF8RQXPQQZK6ipnqZyITOVJBSFGV1fLUEXgfhHAm4QQHeGvfvo6AE9X8BxkoPiSEUCXyhm4icg8nlSlnm8D1ZxxfwTAuwF8AsCfBM/wjrKfg8wUXzIC+EGcGTcRmciTqtTzbcDv7i6dUuofAviHVXxtMlt4jzvyltJmxk1EhnKlKnX4CsDJaWQYmdDo4Z9xV/VERETpPKlQcsKdHbiFEJYQgo1jVBo3YXyg4MhTIjKUJxUatkEZt1JKAvi5kp6FaLRkJFoq58hTIjKUW8EZd563Ce8TQvzVoAOcaKkSJ6cJlsqJyEyelEZ2lf9tAL8BYCiEOBRCHAkhDpf8XFRTSZPTWConIlO5Uo29XpVhale5UmqrjAchApKXjNgWu8qJyExSKjRswwI3AAghvhXAVwe/fb9S6j8s75GozsJSeXxWOc+4ichARp5xCyF+BsDbAPxp8L+3CSH+2bIfjOopLJXHMm7FwE1EBqpiclqejPubAHxh0GEOIcSvAPgkgB9f5oNRPSX9EHDkKRGZys+4DboOFnE68utTy3gQIsAvlceH9VuWgMe4TUQGklKh5GvcuTLunwbwSSHEHwEQ8M+6f2ypT0W1JaWaWI9ns6uciAxVRcadGbiFEBYACeBNAL40+PDfV0q9suwHo3ry5ORCeq71JCJTGXfGrZSSQogfVUr9OwDvKemZqMakmpz7K3jGTUSGcqU0r6scwB8IIf5HIcQlIcSO/t/Sn4xqKWlFnj85jYGbiMwjJSaO95Ytzxn3Xwv++oORjykADxf/OFR3SedFtiUw9Cp6ICKiDK6UaDfL3ZCd54z7x5RS/1dJz0M1l9ShKQRYKiciIyVVCZctz3awv1fSsxDBUwld5WxOIyJDuRU0p/GMm4wi5eQ9bpvNaURkKM/EJSPgGTeVyFOTZSfL4lpPIjKTZ+KSEaXU68p4ECIgOC8S8ZGnHMBCRGbyTBp5KoT40civvyP2Zz+9zIei+vKSSuUWt4MRkZlMO+P+zsiv4wtF3ryEZyFKXTLC5jQiMlEVZ9xZgVuk/Drp90SF8CenJQRulsqJyEBVjDzNCtwq5ddJvycqROLkNJbKichQrlSwDWpO+7NCiEP42fV68GsEv19b+pNRLXkKk2s9hYCUFT0QEVEGT0pzlowopewyH4QI0Gs9xz9mW+AZNxEZyTXsjJuodEmlcosDWIjIUNKwM26i0iUGbo48JSJDVXHGzcBNRkmanOav9azogYiIMpjWVU5UuqQ7kRa3gxGRodyEaY/LltqcJoQ4Qsa1L6XU9lKeiGpNps0qZ+AmIsPo16WyR55mdZVvAYAQ4p8AuAHg1+BfBXsLgPtKeTqqnaRZ5bbgPW4iMo8bBO6yl4zkeZvwrUqpn1dKHSmlDpVS/wrAty37waie0maVszmNiEzjhRm3eYH7WAjxFiGELYSwhBBvAXC87AejekrKuAUHsBCRgdzghcnE5rTvBvDfALgZ/O87go8RFc5Tk1crbAsslRORcXRCUfYAljz7uJ8HS+NUEpl2xs3mNCIyTJhxm3bGLYR4TAjxPiHEp4Pff4EQ4ieW/2hUR0n3uEUQyBWzbiIyiMln3P8G/j5uBwCUUn+M8V3dRIWRcrLspH8omHUTkUnCrnIDA3dHKfXR2MfcZTwMkT/ydPxjYeBmxk1EBtHJhIlLRm4LIV6PYBiLEOLb4d/rJipcUqncCkvlVTwREVEyr6J73FOb0wD8IIB3AHhCCPEygOfgD2EhKlzydrDRnxERmcI1bXIaAAghbAA/oJT6eiHEBgBLKXVUzqNRHSVOTmOpnIgM5Jl4xq2U8gD8+eDXxwzatGwyYXKaLpVzXjlV4dr+CT798kHVj0EGquqMO0+p/JNCiPcA+A1EJqYppX5zaU9FteWp9IybcZuq8C/eexl/ev0Qv/cjX131o5Bhqsq48wTuNQB3AHxt5GMKAAM3FY5n3GSa44GL4yEv0tAkPYAlPu1x2fJMTvu+Mh6ECPDXek6UysOMm4Gbyud4Eo7HYfk0ydiMWwixBuD7AXw+/OwbAKCU+ptLfC6qqaSl9Pr3DNxUBcdTGLoM3DQpnJxm4D3uXwNwEcBfBPABAA8CYJMaFU4pBaUmxwfqxg+WyqkKfsbN7z2aZPLI00eUUj8J4Fgp9SsAvhnAly33saiO0n4IwlI5kx6qgONJDFkqpwRuRQNY8gRuJ/jrPSHEGwGcAnB+eY9EdaXvaccDtx6BynvcVAXHU3A8ySU3NMEzcQBL4B1CiDMAfhLAewBsAvippT4V1VLabluLZ9xUIT9o+9lVs+TMisxW1Rl3nq7ydwa//ACAh5f7OFRno4x7/OMcwEJV0h3ljifRjH9zUq25FZ1x5+kqT8yulVL/U/GPQ3WWNoWII0+pSroxzXEV0Kr4YcgoJi8ZOY78eg3AtwB4ejmPQ3WWdidylHGX/khEcIOMmw1qFBcOYDEt41ZK/a/R3wsh/jmA31vaE1FtpXaVB7/lGTdVYRhk3AzcFGfkkpEUHfh3uYkKpQNzfHJaWCrnGTdVIDzj5hAWijF2yYgQ4k/gzyYHABvALgCeb1Ph0jo0LZ5xU4XcSHMaUZTJZ9zfEvm1C+CmUooT96lw4bvXeMYdBHLeo6UqOCyVUwpju8oxOd50W0QyIqXUfqFPRLWlS+UTGXc48rT0R6KaU0qFAZvzyiludMZt3gCWTwC4BOAuAAHgNIAXgz9T4N1uKkja+ED9M8Ezbipb9HuO88opzuQlI+8F8JeUUueUUmfhl85/Xyn1OqUUgzYVRqbd4+bkNKpINFjzjJviwsBt4KzyNymlfkf/Rin1nwB8xfIeieoqbVY593FTVaLn2iyVU5xr6j5uANeFED8B4N8Gv38LgOvLeySqq7SrFVzrSVVxo4GbGTfFeBUNYMmTcX8X/CtgvxX873zwMaJC6clok9vBmHFTNVgqpyz6W8LEJSP7AN4GAMGWsHuK93JoCdKWjNgceUoViQZrBm6K86SEEJNXWJctNeMWQvyUEOKJ4NdtIcQfAngGwE0hxNeX9YBUH2mlcv1bDmChsjk846YMrlSln28D2aXyvwbgc8Gvvzf43PMAvgbATy/yRYUQp4UQ7xZCfFYI8bQQ4ssX+fvRq0PanciwVM4zbipZtFQ+5HUwivGkKv18G8gulQ8jJfG/COBdSikPwNNCiDxNbVl+FsDvKqW+XQjRgj//nGpuNDlt/ONc60lVGSuVM+OmGE+q0s+3geyMeyCEeKMQYhfAfwXg9yN/NnegFUKcAvDVAH4BAJRSQ6XUvXn/fvTqkT45Tf952U9EdcczbsriVpRxZwXutwF4N4DPAni7Uuo5ABBCfBOATy7wNV8HYA/ALwkhPimEeKcQYmOBvx+9SqSv9WSpnKoxVipnxk0xnlRoxLtpS5D6FZVSH1FKPaGUOquU+ieRj/+OUmqR62ANAF8M4F8ppb4IwDGAH4t/khDirUKIp4QQT+3t7S3w5WhVeFzrSYZhxk1ZTMy4l+UlAC8ppT4S/P7d8AP5GKXUO5RSTyqlntzd3S31AakaMm2tJ0eeUkXGusrZnEYx0sAz7qVQSr0C4JoQ4vHgQ18H4E/Lfg4yT9qKPI48papwAAtlqSrjXrQ7fF4/BODXg47yqwC+r6LnIIPIlMBtc60nVYT3uCmLJ+XENsMy5ArcQoivAPBQ9POVUr867xdVSn0KwJPz/v/p1Sl9ycj4nxOVhWfclMXYjFsI8WsAXg/gUwC84MMKwNyBmyhJ2uQ0nXFz0i6VbXwACwM3jZOqmslpeTLuJwF8HueT07LJtIyb28GoIjrLXm/aY0GcCABcT00kGmXI05z2aQAXl/0gRGmbdixeB6OK6LWeG20bQ9eb8tlUN/49bjMz7nMA/lQI8VEAA/1BpdS3Lu2pqJb0btu0kaes+VDZ9BWwTqvBjJsm+Gfc5d+qzhO4/9GyH4IIGGXc8SUjunLO5jQqm864Oy2bzWk0wdgzbqXUB8p4EKLR5LTxj/OMm6riRAI3r4NRnOsZOoBFCPEmIcTHhBBdIcRQCOEJIQ7LeDiql7TJaVzrSVWJlsrZVU5xVa31zFOc/5cAvgvAFQDrAP4WgJ9b5kNRPaUtGbHDkaelPxLVnOtJNG2BdsNiqZwmuBUNYMl1qq6UegaArZTylFK/BODNy30sqiOZsmRE8IybKuJ4Eg3LQtO24Lj8/qNxVWXceZrTToLRpJ8SQvzPAG6gmuUk9CrnpZTKhRCwBEvlVD7HU2jaAk1m3JTAU4aecQP468Hn/R34KzgvAfiry3woqqe0JSP6Y8y4qWyOJ9FqWGjZFgZsTqMY1zM041ZKvSCEWAdwn1LqH5fwTFRTaUtGAD/r5nYwKpsulbcaghk3TahqAEuervK/BH9O+e8Gv/9CIcR7lv1gVD/hkpGE0pMtBEvlVDrHU2g2hH/GzcBNMV5FA1jyfMV/BODPAbgHhJu9XrfEZ6Ka0oE53pwGBKVyvm5SgQ56DroDN/NzHE+iaQfNaZycRjH+GXf5XzdP4HaUUgexj/E7mArnqfTzIkuApXIq1A/8+sfxU7/96czPcTyJpmWh1bA4gIUm+GfcZo48/YwQ4rsB2EKIRwH8MIAPLfexqI48mVwmB/wsnIGbivTKQX/qZqdoqXzoSSilICroIiYzebKakad53ir8EIDPh79g5F0ADgH83WU+FNWTJ+XEuFPNFoIjT6lQfUdO7RQPm9OCeqjL70GKcKWCbeJ2MKXUCYB/EPyPaGk8OblgRGPGTUXrO97U8rfjSbSCM279e/1rIlnRPe7UwD2tc5xrPaloUimkVZ38ASzlPg+9uuUL3AprTf+MGwCGrkSnVcbT0SpwPWncPe4vB3ANfnn8IwB4sENLlTU+0BYcwELFUUqh53hTF4e4nkSj3QizbC4aoaiqzrizAvdFAN8Af8HIdwP4jwDepZT6TBkPRvWT2VVu8R43FcfxFKTC1Ix76Ck0bX9ymv7/EWlVnXGnHtYEC0V+Vyn1vQDeBOAZAO8XQvyd0p6OakVKldrla/OMmwrUdz0AwCD4axp/5KlAs+F/Xzq8EkYRxp1xA4AQog3gm+Fn3Q8B+N8B/NbyH4vqKKtUbgkBJjtUlP7QD9jTMm437Cq3/c9nqZwiXNNK5UKIXwXwRgC/A+AfK6WyJxUQLSg7cHM7GBWn7/gBOE9zmj85TeT6fKoPKRWUgnEDWL4H/jawtwH44cjQAQFAKaW2l/xsVDNZZ9z+yFMGbipGzwky7ikZ9DAslY+ugxEBozv9VSwZSQ3cSileVqRSeTL9vMjidjAqUD8I3I6n/N6KlDeMo1I5m9NonH49quI6GIMzGUOq9BdQBm4qkg7cQHbWrUvl0XvcRMAo466iOY2Bm4yRlXGzVE5F6uUM3ENPhrPKAZbKacTzmHETwZPJKz0BPfK05AeiVy3dnAZkZ9FusB0sbE5j4KaAG4xyrOKMm4GbjOFJibQx0FzrSUWK3t9OC9ye9Ie0jA9gYeAmn8czbiLAy7hawe1gVKTecHrg1kG62RA846YJHs+4ifx7kWlVJ4tn3FSgPM1pYeC2LJ5x0wSXZ9xE05eMsFJORenlOOPWV7+atogsGeE3Ifm8Cu9xM3CTMTyVPqvcssDtYFSYaMadNq98VCqPnHGzVE6B0Rl3+WGUgZuMIafNKmepnArSd6OBe3qpPDzjZqmcAjzjJsL0kafsKqei9HM1pwWl8oYIr4Mx4yaNZ9xEmL4djIGbipLnHneYcdsWbEtACDan0Uh4xs3ATXU2bVY5XzOpKNFS+bSu8oZlQQi/QY3NaaTpASw2m9OozryMZQ+2xbWeVJze0MNaM/tuti6Vtxr+92TbtniPm0LhkhGecVOdSZU9q5ylcipK35U4td4EkB643UipHPC7y1kqJ02fcbNUTrWWdcYthOB1MCpM3/FGgTslGA8jpXLAv8/NwE1a2FXOwE11JlX6khFbCJbKqTB9x8P2WnbGHS+VN1kqpwiXA1iI/GaPtJ8B22LGTcXpOx62g4w77R53vFTeali8x00h/XqUNjRqmRi4yRhSpk8hEsL/c6Ii9BwPW2sNANOvg+lSecvmGX7nvDAAACAASURBVDeNeOEZNyenUY35Z9zJf2bzHjcVqO9IrDdttOz0LHqYUCp3eB2MAi7PuImmT07jyFMqSt/xsNa00WpYGDg5u8ptwTNuCnHJCBH8e9rpS0YEGLepKNHAPfSyl4w0eMZNCUZLRhi4qcayMm5LgKVyKoQnFRxPjUrlKVn0MLLW0/8rz7hpxNOT09icRnXmZWTcNreDUUH0Ss+1pr/1a+oAFjanUQIuGSGCH7jTphBZFu9xUzF6YeC2M8vf0X3cAO9x0ziecROB28GoHDrjnlYqd2Kl8laDXeU0wjNuIvhn2OlLRjiAhYqhA3e7aaHdtFIHsDixUjkzbooKR57yjJvqbNpaTw5goSLoXdxrUzNuCdsS4ZvJVoOzymnE5QAWqjulVPascotd5VSMsVJ55hm3CsvkQJBxM3BTIMy4ecZNdaX7zrIybpbKqQjR5rR2Rle548mwTA4EXeUslVNAvx5xrSfVlqvvRKZ8R1pCQCk/MydahC6Vhxl3VuBujL4hm2xOowidcXPJCNWWPr9OWzKiOzd5l5sWNXaPO6P87bjJpXK+eSQgesbNwE01Nbpakfzn+meDcZsWFb/HnTar3JFyrPGoFQRxZt0E+JPThEjvy1kmBm4ywrSyk/7hYIMaLWqQewCLQitSKte/Zmc5AX6yUUW2DTBwkyHklBV5ummNpXJaVG+sVG6nn3G7cqJUDjBwk8/NGNG8bAzcZIRpU4jCM25m3LSgsXvcWbPKY6VyHbh5JYwAwPOYcVPNySmlchF8XPE1kxbUdzw0LIGmbYWl8qSGs6GnxrrKWzpw80oYwc+4qxh3CjBwkyFcmd2hqSuWzLhpUb1gFzcAtBvpWbTjyrAhDYiecfN7kPx+m0ZaN+2SMXCTEcLmtGmlcp5x04L6jpwM3AlZdFqpnGfcBPCMmyjsFk+dnBYEbt6hpUUNHA9rzWDHdkbgjpfKdaMaS+UE8IybaDT3N2OtJ8BSOS0uWipvZTScxUvlzYyyOtUPz7ip9nTGnVoq53UwKkjf8bCuA/cMpfK2LpUz4yboM+6aBW4hhC2E+KQQ4j9U9QxkDp3ETCuVc7UnLco/455eKnfipXI2p1FEXTPutwF4usKvTwYZLRlJK5X7f+XkNFpUUql8kHTGzQEslMGTMjXRWLZKArcQ4kEA3wzgnVV8fTLPaMkIB7DQcvWjgbuRHrhdOb7WUwfxpM+l+nG9+mXc/xuAHwXAnwACkGfJiC6VM3DTYpICd3qpfPTC3OascorwZI3OuIUQ3wLgllLq41M+761CiKeEEE/t7e2V9HRUlWlLRuxwyUhpj0SvUn1HYj044542gKVp8x43JfOUSl1DvGxVfNWvBPCtQojnAfyfAL5WCPFv45+klHqHUupJpdSTu7u7ZT8jlUxOmVWuP8yuclpU342ecft/Tcy4JQM3pfOkQkUJd/mBWyn140qpB5VSDwH4TgB/qJT6nrKfg8wS3uNO6yrXpXKecdOCesMZSuUJzWkcwEKAf8bdqFHGTTRBcuQplUAphYErJwO35419npQKnlRjGffoc/k9SEHGXVFzWqOSrxpQSr0fwPurfAYyw7QlI8y4qQi6I3wtfsYdy6Kd4JrDWOBmqZwiPKXCoTxlY8ZNRvCmTE4LB7AwcNMCekM/s15rZJfK9ZCV8VK5/2tOTiOAS0aIwlJ52hn3aORpaY9Er0J91w/c663se9yuN5lx25aAEJxVTj5PSi4ZoXqbumQk+E5lxk2LCDNuPfI0ZcmI/n1037IQAi3bYuAmAPUcwEI0JlwyMq2rnM1ptIC+4wfd9fh2sJRSeSt236dlW3Bcfg9STZeMEEV5HHlKJdCl8nYQuC1LoGmLicCtS+Xx6z7NhsXmNALAM26iHEtGeB2MFtePNacBfhY9mXEHZ9yNWOBOCPJUT55UPOOmess7OY0JNy0i3pwG+A1q8ea0oZtSKmfGTQH/jJvXwajGpu3j5gAWKoI+49bNaYAfjCdK5TKlVM7mNApIxYybam40OS35z8NSOVNuWkD8HjcQBG4vX6m8ZTPjJp8rVerciWVj4CYjeFNK5eF2MGbctIDEUnnCGbculTdjpfJmwudSPfGMm2ov/5KR0h6JXoXCUvlYxm1PDmBJGHnqf64VXhWjenM9yXvcVG9yyshT/frJUjktou8EpfLW6KWvnVUqtxO6ylkqJ/hJBDNuqjXXy7lkhCk3LaDveBBiNHgF0M1p49vBskrlPOMmwK/KMOOmWpuWcXM7GBWhN/Sw1rAhIkcy7Yyu8olSOc+4KVDlWk8GbjLCtDNuXgejIvRdb6wxDUDi/PG0UjnvcZPmsjmN6m5aVznXelIR+o7EWvyKV0LG7WSWylf3e/DKzSPcOxlW/RgrT0oFpcABLFRv4T1urvWkJeo5HtbiGXdS4E4pla/6dbC3vPMj+Pn3P1v1Y6w8nWhwyQjV2rQlI/rDzLhpEQPHG7sKBqTMKnfTSuWr3VW+fzzEnS4z7kV5UxKNZWPgJiN4QYaTdmTEUjkVoe/IsXGnQPKscl0Oj5fKV3ly2tCVcKXC8cCt+lFWniuzb8EsGwM3GcFTfoemmFoqZ+Cm+fWchOa0GUvlzoqWyvW41+MhA/eiwmZaBm6qM0+md5QD0Yy7rCeiV6N+Uqm8YWEQ7yoPm9Mm93Gvaqn8xPEDNjPuxenAzTNuWhlX97r4b3/xozgp8J27VCp1wQgQOeNm5KYF9BwPa83xwN0OzrhV5BjG8SQsMZlR6a5ytYJHNidBxq3/SvNzw6M9Bm5aEU+9cBcfvLyHF/dPCvt7elJlZtzhPe4VfMEkcwwcORG4W8H1sOg1L0dKNOzJl8d2wueuCl0q7zLjXpjHM25aNbrUVuQ7d2/KijyLZ9xUgL7jJTanARgrgTuuGhuLqulmtVVsUNM/ryyVL06PaOYZN62Mbt//we8XGLilyh4fqAP3KpYoyRw9x8N6vFQenHlHG9QcT050lAOjM+9VvMutj7aOWSpfmOQ9blo13WHxGfe08YGjkaeFfUmqGaVUkHEnl8qjwdhNKZXrwL2KGbculQ9duZLPbxKX97hp1ehSW88pMOOWKvOHQMd0nnHTvBxPQSpMlsoTsuhhSqk8qay+KqJvtE8GzLoXMTrj5shTWhHHwQ99r+Az7qxSuRAClmCpnOan32imZtze6Ps5rVTesle3Oe0k8ka7y7vcC+EZN62c7hIybk9lZ9yAX5ZicxrNazAlcA9mKJWv4hl3LxKs2aC2mPCMm4GbVsUyuspljt22liVYKqe59R0/2OY54x66amL4CvDq6CoHGLgX5XJyGq2aZZxxe2r6D4EtBAew0Nz09+tEV7mdnHG3kkrlK3zG3RsL3DzjXoTercDATSsjLJUXeE7mSTk94xYceUrz64el8pR73LHrYEml8vCMewVL5WMZN8+4F6LPuFkqp5URNqcVmXFPmZwGBKVyRm6aU1rGnRi4XZV8j3uFM26Wyoujj+yYcdPKWM7kNGROTgP8HxKu9aR56Yy7ndpVHgncUqacca/wPW7HxelOEwCHsCyK28FopSilwqsk/SLvcSuFhNfJMTa7ymkBo+a06fe4/etg6aXyobt634cnQw+7m20AzLgXxeY0WiknQw866S16Vvm0UrkQgmfcNLd+AaXyVmOFu8oHHs5stCAEA/eiPI8DWGiFRH/gixzA4q/1nFYq51pPml8/5R63nlU+iJXKX233uE8cFxstGxutBrvKF8Qzblop0ZWARTanud70jNsWvMdN80sL3Gld5cnbwVb3jPtk6KHTamCjbTPjXlA48pRLRmgV6HfqLdsqduTplO1ggC6VM3DTfHrBGffkdrBZSuWrG7h7Qw/rOuPmdbCFcMkIrRSdcZ/bbJU+Oc22OICF5hd2lTemN6dNHXm6irPKh55fKm83mHEvSA9g4T1uWgn6B353q11oV3mejNu2BFbw9ZIM0Xc8tBvWRC+FZQk0LDG2ZGToJpfKk4L8qvAz7qBUzutgC9EFF55x00rQJbZzm+3CM+7pS0bYnEbzS9rFrbUaVuyMO2UAy4rOKnc9iaEn0Qmb05hxLyLMuHnGTaugG8m4e45X2JrNPBm3xTNuWkDfkRN3uLVWw8q1HaxhW7DE6gVuvdKzw1J5IcJ73DzjplVwPBhl3MBoqMWiPDm90cPmyFNaQM/xJhrTtJY9yriVUkHGnfzy2LStlRt5qhtJ11s2S+UF4OQ0WindoKv87GYLQHFXwjwppzZ6MOOmReQtlTtBI0XSdjD/49bKnXHrYy2WyosRXgfjABZaBd2+i812AxutBgDgpKBrJV6ufdzcDkbz67tyYk651mpY4QAWNzy/TMm4G9bqlcqDn9P1ZgOddgMnQ4/9IgsIM26ecdMqOB642GjbWGv5L4BFdZZLlWPJCGeV0wL6Qw/raWfckSzaCeaQp5XKW7YVfs6q6EUy7s22/7N7UuCtkLrhGTetlO7QxUa7gU6QuRTVWe7PKs/+HIvbwWgBfTe9VN6OlMr1+XVaqbzZECuYcY83pwHACcvlc+MZN62U44FfKl8PMu6ipqd5MsescmbctIDeML05rd2ww8A9tVRuW2NzzVfBSbQ5LTjm6jJwz210xs3AXZmPv3AXf+tXPrZy76KrcDxwsdEaBe6iym1STZ9VzuY0WkRWxt1qjDrF85XKV+u1ouf4QdqfVe4Hbi4amZ8rFYSYfry3LAzcAP7z1Tv4g6dv4crNbtWPYrzuwMNGuxFmLv2CMm43b3Paar1ekkGm3eOOl8qTBrDoz121N/njXeX+zy7nlc/Pk7Ky822AgRsAcNh3AACfu3lY8ZOYzy+V2+i0ij3jzjurnNvBaF79YUbGHWlO06XyrHvczorN3h2/x60zbgbueeVJNJaJgRvAUd//Bv7sK0cVP4n5/K7yUcZd2D1uTk6jJSuqVN60xere4276A1gAcAjLAjxPVXa+DTBwA4gE7hsM3NN0l9mclueMm81pNAfXk3A8hbXG9AEs00rlqzg57WTooWVbaNgWM+4C5Ek0lomBG8CRLpUz487keBIDVy4l42apnJapHwTl9VbWrHL/e9n1skvl7ZU843bDN9sM3IvLMzBqmRi4Mcq4Xzns497JsOKnMZf+Qd9oN9CwLbRsq7h73DlL5Sv2ekmG0IOCss64B7GRp9ln3Kv1jXgy9MK+FD2DgV3l8/PPuKsLnwzc8DPuzeBdKM+50+l7n3ry0lrTKm5yWo4lI5ZAYdvIqF6mBe722KzyHKXyFTvj9ndx+//sDdvCWtNiV/kCeMZtgKO+iy9+7RkAwGdvsLM8jX6HvtluAvDvhBY1q9zNsWSE28FoXlMz7qA5zd8M9urrKj8ZumHGDYCLRhbEM24DdPsuXr+7gTOdJj53kxl3mm5YKvdfANZbNnoFrPVUSuWaVW7xjJvmpNfPrjXSh6oo5ZdAp5XKox3oq+Jk6KHTbIS/507uxXhSoVHRghGAgRtSKnSHLrbWmnji4jaeZmd5quOwVO6/AKw3bfQKyLh1Ej1toIHNrnKak26iXG+lZ9wAMHTl1FJ5y169WeU9x0OnPfpn77S4k3sRrpw+6XGZah+4u0MXSgHbaw08fnELl28eMTikiDanATrjXvyHfzSwP/vzLMG1njSfPGfcQDxwp5fKV+2MO9qcBvhvvplxz8+TkqXyKumO8q21Bp64uIWToYdrd08qfiozdWMZd6dlF9JVroeq5CqVM3LTHEal8rSM2//4MLjvDWQE7hW8DuYvWBmVyjsFBe6f/YMr+P5f/tjCf59Vw+tgFdN3uLfWmnjivm0A7CxPE8+415p2IQNYvJy7bW1OTqM5jUrl6efWQN5Sud+ctko3HOLNaZvtYkrlH756Gx9/8e7Cf59VwzPuikUz7scubEIITlBLo3/QdXNap6BSuS47pmU4GkeeZlNqtYJJmXSpvJ0xOQ0ABpHAnbbWU3/uKnWWx0vlRXWVX9vv4aDn1K4SxjPuikUz7k6rgdfudLhsJEV34KJpi/DFb72gjFsvedleb2Z+nl8qX/jLvWr91z//Ifzs+65U/RhGGkxrTrOjGbca+1iczsRXpbPckwoDV479sxfRVe54EjcOelAKOOg5iz7mSmGpvGLRjBsAHr+4xYw7hV4woq23ignc+of+1JTAbVtgxp3h8s0jXOZ1xkS9vM1pnoyMPE0fwAJgZXZy63/2sYw7KJUvUqG5fq8XNovuH9dr4qQnFRqcnFadw1jgfuLiNp6/c1zYRLBXk27fxUYrEribxZTKcwduwea0NI4ncTL0apf55DX1HrculTteWCpPy6hGpfLVCNx6SNJ65Ge302qEmfi8XtwfNfHWbVR07dZ6CiEuCSH+SAjxp0KIzwgh3lb2M0TpUvn2mh80nri4BamAKze7VT6WkfRmMK3TsuFKtfDVmLyBW/CMO9Vh8O+QgTtZz/HQtMXUc+uhJzH0FFq2BZFyhqkz7lUplfciKz21zQIWjVzb74W/rmPGXavADcAF8D8opT4PwJsA/KAQ4vMqeA4AfqncP7f1/1U8fnELAPD0KzznjjseumFjGjAqOy6adecvlXMAS5oDBu5MfcdLvQoGjJ9xu55MLZPHP3cVhLu4W+MDWIDFFo1Er83eO6nX913tMm6l1A2l1CeCXx8BeBrAA2U/h3bUd7C11gzfXb/27AbWmhZXfCboDjxsro2CaycovS16zj1L4ObI02T6yOewx6EaSfqOxFpKYxoweR0sLTMHImfcK9JVrgP3eish415g8uGL+yfY3WoDAPZrViqXssZLRoQQDwH4IgAfSfiztwohnhJCPLW3t7e0Zzjqu+H5NuAHh8cubOGzzLgnHA/ccDMYMLoTW0TG3Qo2FmURnJyWSr/5Oew7rEok6Dte5vdXvFSedTVx1c64w1J5a3xWObBYqfyl/RM8cXELLdvC3ZqVymuXcWtCiE0A/x7A31VKTURJpdQ7lFJPKqWe3N3dXdpzxAM34J9zM+OedDyIN6f5v150Q9hhz8H2ejP1TFEzbVb5J1+8i+/41x8yopFRB26lgCOOspyQt1Q+yFEq13+2SGNXmfTPZ7yrHMBCQ1iu3e3h0k4HZzaauFuzjLuWI0+FEE34QfvXlVK/WcUzaEd9B1vt8RLt4xe3cbs7xN7RoKKnMlM34ToYgIUD10HPwan1xtTPM61U/tTzd/Gx5+/ixkG/6kcJm9PivyZf3/FS73ADk7PKMzNue8Uy7oQ77Itm3N2Bi/3jIS6d6eBMp4X943p9z9Uu4xZ+WvULAJ5WSv2Lsr9+XFLG/YagQY1Z94hSKiiVj3eVA1h4XrkfuLPPtwF/cppSMGY62L2en2WYcBUm2pTGBrVJvSkZtx4qpAewZDanrVipXDegxSenAaP9A7O6FlwFe82OH7hN+BkoUx3PuL8SwF8H8LVCiE8F//umCp4DgB+4N2OBW3eW85x7pO9ISIXxjFt3lZcYuAFzzrl1J+09AwLlIQN3pr4j0c55xj0t426uWMYdlsqbk2fcJ3MGbn2H+9LOOnY2WrVrTvMz7upaxKbXJwumlPp/AVT3ViXmsO+Ed7i1s5ttnNtsc9lIxGgz2HKugz2yuzn18/RradV3KDUdsE0oTeuxsYAZz2OavuPhfNABnSTeVZ4ncK/KdbBeQld5eB1szjfdOuO+dKaD051m7ZrT/Neg6r5+rSenSanQHUyWygHgDfexszyqG9sMBox++BfOuE9yZtyWzrjNSLkPdMZtwB3Wg54T/vdgxj3J7ypPL5XbloBtiZylcj2r3Izvw2lOHA8NS4RvTgD/TL9hibnPuF+628NWu4HTnSZ2Nlq1WzRSdcZd68B9PHShFBID9+MXtnDlZjecW1x38ZWewKhUvsgZt5QKRwN3xlK5GS8QJg09Oeg5eM1OJ/w1jbt74mB7SgNky7bCUnnWPe6W7X/fr8ys8uFkY54QYqFFIy/un+DBnQ6EEDjdaUGqelV66njGbYzRgpHJoPHYhS0MXImX7/Um/qyORqXyya7yRUrlR33/zdO0zWDAaF+3Ke/sR81p1b9gHfQcXDy1BtsSDNwxJ0MXBz0H959ez/y8VsMKZ5WnbQYDgGaQca/SGXcnoaN+ozX/Tu5r+ye4dMb/97mz4f/s1ulKWO26yk0S3wwWFU4EqtnZTZqkjLvdsCDEYqXyvFPTgEip3JDXy1FzWvXfI4c9v2pxar3JwB1z/Z5/Xe/+U9MDt59xZ5fKV21W+cnQG5u/oM2bcSulcO3uSVjhOdNpAahX4PaYcVcnuos77sxG/b4ZsyQ1pwkh0FlwQ9gsgVu/lppwl9v1ZPjGz4QSoe7MZ+CedOPAr5rdd2ot8/NatoXBDCNPV6k5LekOe6fdmOs62F53gL4jcSkeuGt0l9ut4wAWU2Rl3DvBN2PdBguk0XdBN2PDatZb9kJn3HNl3AYEbj0bHKi+VC6lwmHfD9zba42xZyPghs64p5TK2w0r7CrPKpW3w3vc1X8f5nEy9BJL5Zvt+X529VawSzu6VB68VtYoyan6ZkutA/dhuNJzMnCf0ec2LJUDiJbKx18A1lv2QpPTwsDdmaE5zYAzbpMGnnSDJsvttSa2mXFPePleD0IAF7anZNxh4M5XKl+ZM27HG9vFrXVa85XKo8NXAOB0p36vlSyVVyirOW2z3UDTFrV6F5klvA4WewFYb9oLzSqfqVQe/KCYUCrXk6Iubq9VPoBFX0vTpXITSvcmuXHQw+5me+w6VBJ9xu1OKZXbloAlVqlU7o7t4tY22425toPpwP3gmU7492naAndLrjxV9UZBSgWpwOtgVckqlQshcKbTqtW7yCzHA78z1Yq9y1xvNdBz5n8Bm6lUrs+4Dci4dbB+zdkODk6czDGs3YGLf/Sez8w9XnIa/e9wm2fciW4c9HHflDI5EFwHc6dvBwP8rHtlMu6UUnmnZc+1j/vaXX+dp74XX8Vr5fO3j/El//S9+PgL+6V9TU0nDhzAUpGjvgPbEuF95LidjRa7ygPHw/EFI9p600JvwYy7aaf/N4jSpXIDEu4wy33tTgdDT6Kf8eblo8/dwS9/6Hl86JnbS3mW8MhnvREGblPmuZvg+r0e7p/SmAYA7Wb0jDu7DKqz81WQ1py2OWdX+Yv7o45y7UynVWoj77N7XUgFPLt3XNrX1HTiwIy7InrBSNo6ybK/GU3WHXhjd7i1TquxcFf5qRwrPYFIqdyEjDv4vnjo3Ib/+4wrYbe7/p/p+c5FO+yNl8o9qRZa1/hqopTyM+4pV8GA0QCWaaVy/bmrnnFvtBvhGtNZXNvvhXe4tbJXe94KNjdWkVjp1x+ecVfkqO8klsm1MxtNZtyBbt+ZaEwD9Bn3/EFC7+LOw6Qz7oOen6nkmVamv4euLSlwH8QCN2DGFTUTHPQcnAw93H96esY93pw2vVS+CmfcUir0UpvTgnnlM5TLHU/ixkEvvAqm+as9y3ut1CuX73TLX73shhk3A3cljvruxC7uKD/j5gsg4P9wJw1xWG/Z6C94HSzP+TaAMCs3oQx8rzfEZruBs8FVmKwrYfrF5YWlZdz+m4jt9Wb4Jojn3L7rOa+CAUCrYQdn3NNL5c2GWInrYH13cqWnpitoszSoXb/Xg1SYDNwbrVKvRd468v+73qkw42bgrshRyoIRbWfD3zNrwvWjqnVju7i19aaNkwJK5XmMRp7O/eUKoxej6GtsmYH7eLml8oOeA0sAm61G+O+SgduXd/gK4Je/dfUoT6m8yDPuvuPh1z78fOHHQPqfJ7E5TQfuGc65wzvcZ8YD905wrFjWa+Wtw+pK5W4wupGBuyL+GXd2xi3V+MrEV7u0bDatOa3TshceeZo7cEfWelbtXs/B6U6+0vSd4Iz7pf3eUl7YDoLjBssSDNwx1w9mybitMIjl6iovsFT+e595BT/525/BJ168W9jfE4is9Ey8Djb7as/oHu6o050mpBrd1Fm2W2GpvPzArUcu84y7Ikd9J3H4ihZOBKrJOfe/+9g1fMXP/GFi083xIDlwrzVtDFw5dzCdJXCbtB3s3skQpztNnA4m7GU1p+nvn6EncTMo8RUpulOegXvc9Xs9NCyBc5vpu7i1dsNCd6gDd7ld5VdudgGMMsmi6DJ4J2UACzBjxn33BA1LTDT7lT09ba/C5jRm3BXTXeVp6jav/FMv3cONgz6evz15xcIvlSffBQUw1/S06KjOPEwK3Ac9B6fXW9ho2WhM2ch1pzvAhW0/cLx4p/hyefTNz/YKNqctc3XujXs9XNhey/Ui22pY4VXDsu9xX755BADYK/iNXVapXB99zTJf4Nr+CR44sz7x77PMRSNKqVFz2vGg9J4XnnFXSCmF7iC7VF63eeU3ghWmnwteRDQ3uKeceI97gdWeRwN/VGf+Urk518F0eVoIvzyddsatlMKd4yG+6NIZAMtpUIsG7q12A0KsTuB+5tYRPu+nfg+fe+Vo+ifP4fpBHw/kKJMDGJtPPi1wt2wLjlvc9+Ezt/yMe6/gLumwVJ5yHQzATJMP/XWenYmPh0lOCRnwQc/B0JM4v9VG35EL3WqZB7vKK3Qy9OBJNfU6GFCfGbw3gvPAy7EXUX0GltacBsy32vMwMvErD1OWjCilcO/ECWc0n+o0U8eeHg89DFyJP/PgKdiWWMqVMP9Knf/fxrIEttdWZ3raJ168h6En8fSNw6X8/W8c9HBfjqtgAMZGok4rlTcLLJX3HQ/P3/GrXDqTLEpWxr0RfKw7w3Wwa3cnr4IBwJngZ6GM0rU+337ivu3SvmaUDO9xcwBL6bLmlGt123pzPSXjPg5Xehabcc8y7hQYjTytOuE+HnpwpcLp9dG5clqGux80z5zfauP+02tL6Sw/CHZxa9vrjZUJ3FeDyVf6TWORpFR4JefwFSAeuKdl3KKwe9zP3T4Ov6eLD9z6jDsj485ZKu8OXOwfDyca04BRxl3GlTDdB/CG+7YAlH8lYex8yAAAIABJREFUjBl3hUa7uNMz7vWmjVbDqkXGfTxww3WQl4NGmeifAUjtKgcwV7lq1sA9ug5WbeTWU9N0xn06o1R+59h/kTm32cZrdjqFB26l1MQQm1WaV351z/9eu3lYfOC+3R3A8VSu4SvAbKXy+Bl33/Hw9vdext/7jf8y85mrPt++/9TaEkvl6dWyvM1pulqUVCrfajfQsMpZyqTvcL/hop9xlz2EhWfcFTrMWDCiCSGwU/JEoKro+64Pn9vA83eOx5rNjjIy7rUFSuUzZ9y6VF5x4B49t59lnO60UgOlvq6ys9HyA3fBzWmDYGDI9tqKBu6gEfKVJWTc+ipY3oy73cxfKm81RoH7jz57C9/w9g/gZ993Bb/x8Zdm/nf/zK0ubEvgS1+3s7xSecJ1MMsS2GjZua+Dxdd5RgkhcLrTCt/ULtOoVF5txs3rYBUYZdzZQePMRj3mlb8cTJj6msd3odSoWQaYlnH7H+s5s9/fnDnjNmTkaXSNpv5r2guWftO3s9HCpZ0O7hwPC90SlvTvcFUCt+tJvBCc7d5YQsatmy2XlXEf9l387V97Ct/3yx9Du2Hjv/uq1wEAXrrbm+k5L988wmvPdvDA6XXc7hY7xEQfYXUSboT4H8+/aORa8M+VdMYNADsljYjeOxqg07LDzL/sxIoZd4X0GXfWPW7A/2asw9hT/SL3Fx4/DwBjXb6jwJ08qxwAesPZz/tW9YxbN6KFzWnrTRz23cQS/u2gVH52s4XX7vgLSYpsUEsP3OUMwljES3d7cDyFVsPCzSVm3Pcv4Yy7aVvYPx7iA5f38KNvfhy/88NfhW/7wgcAAC/dne2/75VbXTx2fgu7W214UhWaKJwMXdiWGHtTErXZbuR+I3lt/wQbLTtsRIs73Wnhbgk3cG4dDXB+q41Oy0a7YVVWKmfGXYE8zWkAarOT+/pBH0IAX/a6HbQa1liDmu46Td4Ops+458u4G5ZIbJxJEt7jrvyMezJwA6MqTtR+d4j1po1OqxGWGIs8507qzN9eb67EtL+rt/2qzpe85gz2uoPCexdu3OthrWmF/52mac/QVf7Nf+Y+fNefu4T3/sjX4Af+wiNoNawwA9RjQfMYuB5euHOCRy9sYnfLv+tf5Dn3ydBDp2mnbt/rtPIvCXpx/wSXdjqpf6+dkrYp3jrs4/zWGoTwB+uUXyr3kxSLgbt8eZrTgGAndw1K5Tfu9XB+q421po1HdjdTMu70M+55BrDMstITMOcet56Sdjo8406fV37neIizm/7n6cC97Ix7e62JoSvn+m9SJt1R/pWPnIUnFW4XnDldP+jh/lPrub+/ohn3tFnlf/7Rc/hnf+ULxsrGpzpNbK01Zsq4n7t9DE8qPHphC7vBdLciz7nTdnFrGzNk3Ff3unh4dyP1z8s6Vtw7GmA3GGi0s1F+DxIz7god9f0S0rRs70zQeDTrdKdPXbtXeYCZRXRn8eMXt8JOV2A0WSk7454/cOdlyuS0g56DVsPCWtDMpAN30rnyneNhuEHsVKeJ7bUGXiiwQS2tVJ72PCa5evsYpztNPBF0Bxd9Jez6vX7uO9wA0LLtyK/ne2l88EwnPAvOQ9/gePR8JOMuMHCn7eLWNtuNXNWygevh2t0eXr+7mfo5Zzr+seKyJ5npUjngB+6y55XzjLtCR30Hm+3G1HfjOxstKDXbi+Bzt4/xl3/u/8N//JMbiz5maa4f9MIJU49d2MKNg374z3w88N/kREuJWthVPkd2N8subsCgwH0yXinQgTJpCMud7gBnI3OyX3O22CthYak8UjlamcC918XD5zZwMdjcVXRn+Y0g485rPOOe70X5wTPrM2Xcz9w8giWAh3c3lha4k66CaZ2WnWsf94t3TuBJlZlx72y04EkV3thZhpOhi+7ADf9dnd2sMuPmAJbSTZtTrs0zr/zZoCNb31E1nVIK1+/1wtWHj1/031VfCbLu44GLjVbyOZkO6PNeB5sl4x6Vymf+UoW6d+KEw1eA0bWwpM7y/eNhOMgHAF67s1FwqXy0i3v0PKsSuI/x8O5mGLiLvMvteBK3jga4L+e4U2C25rQ0l850cG2/lzvrvHyzi4fObqDdsLHZbmCtaRVbKnfcqRl3nq7yZ4PXsqyMO1y4s8Ryuf53c37L/545u9EqfV45B7BU6HDKSk9tnnnlOqOa9VpIVe6dOOg7MnyRe+yCfz9SN6h1B15imVxbb9lzT06bLXD7f636Oti93nCs4SlttadSCne6ozNuwL9K89LdXmHHKAc9BxsteyzQhIF7htsQv/+ZV/DrH3mhkGfK46jv4NbRAA/vbmCn00LTFoWWym8e9qGUP9Qkr2h5fP5S+Tp6jpc7C7xy6wiPXvCDoRACu1vt4pvTMgJ3p5U3cPv9CA9nBO6djeWPPb0VBm5dKi9/XjlL5RU66ju5Mu7Tc8zgHQXu4sdbLsP1YPiKfpF74PQ6Nlp2OLP8eOBiM+PfVaeZvzM1atbArTP+srcBxfkjRkfBOCyVxwJld+Bi6MnwjBvwG9SGnsQrBWWXh/3J44bwjcQMneX/5v+5ire/90ohz5THc8HglYfPbcKyBM5vrRWacV8P5hLMm3HPWyrXzWp5zrkHrofn75zg0fNb4cd2N9uFNun1hl7iLm5ts+0PYJl2U+PZvS4ubq9lvoEvY0OYHnd6fntUKgfKvcvNwF2ho7479Q43MJpXPss347UVy7hvxF7khBB47OJWmHEfD5N3cWtrc2TcUvqjOmfKuA0ZeXpwMp5xtxoWNlr2RGl6NHwlcsatr4QV1KCW9OZn1lK5UgqXb3ZxuzuYKUtfhO4of31wZnrfqbVCz7hvxN6M5tEuoFT+4Bn/ZyjPm/bnb58EHeWjLHZ3q11qc1qnrQcoZf/8Prt3nHm+DUQC9xLvcutxp7oDX78pLvNKGLvKK3Q0cDLfPWpnOrO/o9MZ942D/lJ3DRcl6UXuiYtb+NwrR1BK4ajvZv676rTsmc+4u0MXcoaVnoBJ18GSg2W8Oe120O0aLZUXfSXsIKHBT1eS8gbuve4g/Nxn9pazXjPu6l4XlvCb9QDgwqm1wqoQwOIZ9yKlciDfm3Z9c2Ms415C4M5qTtNvyLPK5UopXL3VzTzfBubrB5rVraMBGpYIX5d1YlXmEBaecVfoKOcZ93rLxnrTzt1woZTCi/snOLXehCdVoS9Gy3L9oI+m7Q8z0B67sIW7Jw5ud4dBc1r2MpZZA3d8bGgeIpycVl3gHrgeTobeWHMaAJzqtCZK5frNXrRUfv/pNdiWKKyzPKlq0bAtbLbzbwi7ElkqEx11u0zP3j7GpZ0O2g0/G7y47WfcRR2D3DjoYXutkevNuRYN1vOWyrfWmjjdaeZ6Y3blVjfsKNd2N9dw98QpbPNYbzitOS1YNJLx87vXHeBo4IbVkTTbaw3Yllhq4N47GmB3qx0OP9GvWeVm3P5/GwbukuksMs8ZN6Av+efMXo4GGLgSb3p4B8BqlMuv3+vh4qm1sUlAj+sGtVeO/MCd2ZzWwMmMpfKDhIlf0+gflCoTbv3c8Wlcp9YbE81pOguIXgdr2BYeOL2OFwoM3NsJb0BnmVeubw9YorzAfXXvGA+fGwWC+06toed4hV0lun6vj/tnyLaB+JKR+V8aL53p5Pq5v3LzCK89uxFeqQQQXnPSW+UWoZTCiTO9OQ3IzrifvRUca5zPzriFEDjTac7UyDur6B1uILJ6udTA7f+VpfKS9RwPnlS5Mm4AOLPRzP0uUr8gf+Uj5wAUOyVrWW7cm9xZ/NjFUWd5d+CG78yTrDct9GfMuA8TBodMY8IZd/jcndbYx0+vt8KJatqdhIwbQKHrPdMa/LYzdoTHXbnVxan1Jh67sFVK4JZS4bnb3bEO5Qvbxd7ljl5vzGt8ycj8L8oPnlnHtRxn3FdudfFoLBgWeZe770gohczJaboikTU9TV8Fy+oo15Y9IvrWYR+7W6P/rlXMK2fGXZGjHCs9o87MsNpTNx192evOQogVybgPehNNPOc22zi70cLnXjnE8dDLzLg7rQZOZtwONuuCESCy1rPCUnk4pzz23Kc7kxnune4QGy17LKMC/M7jIt7QuZ7E8dBL/HfoVwDy/Te5ctMPII+c38QzJcweuHHYR9+RYyXicAhLQUdLNw56M51vA341xBJ+JpV3TGqSSzsdvHw3+y730JV4/vbxWGMaUGzg1hPRklZ6anl2DTy718V608Z929PfCJ1Z8rxyXSrXqphX7nIASzXyzinXdmaYwfvi/gmEAB4618HF7TXjA7eUCjcP+4kvco9d2MIfv3QAT6rsrvKmPfN2sDBw51wAAZixZOReytm8v9ozfsY9wM7meLYN+Bn3/vEwcSnJLHRZeXt98r9N3lK5UgqXbx3h0QtbeOT8Jl6621v6jHM9mOjhc6OgdTEICkVsCesNPdw9ccJJgLNoNayFyuSAn3EPXJkZfJ+/cwxXqnBmglZs4A5Wemb0p4wy7vT/5leDjvI8SzVmqU7OyvEk7hwPx0rlQPnzynXFr8K4Xc/AHb7g5S2Vz5BxX9s/wX3ba2g37JnHH1bhdncAx1OJ12aiM8und5UvP+MOS+UVnnHHV3pqpzpNDGKLPe4cD8eugmmjzvLF3tRl/TvcXssXuG93h7h34oQZt1Kjq1rLEr8KBozu5RaRcetbErOWygG/XL5ImRzAaEtYxpt2/XP1SKxUfi54o1dE4NZXvLJK5fo62MmUUnmeMjmgM+7lnHHrmeT6e0Vb5rzyvuNNNAoy467IrKXynY0WjvounBxXu/TqO8BfOGB6xq13FsfPuAE/cOvkNrM5renf456lI/ig58C2BDZyrvQERu9wq824xzeDaUl3p+90hzi3MZlxv/asXu+5WIDM6hPIm3FfuRVcSbqwGQaRZZfLr+51sdGyx0qe7YaNsxutQqan3cj4np6m1bALybiB7LvcV276HeXxK1btho1T681CpqeNMu6MM+5W9hl33/Hw8r3e1I5y7cyGf8a9jCFJ+g73+a3xN2TLnFf+lnd+BD/xf//J2Mc4gKUio1J53ozb/7w8JaAX90/CjOrBM+t45dDsu9zX7wV3uFNK5Vpmc1rLhlTAYIYrLLOu9ARGpfIqR54e9hwIMfmm73Q4rzwSuI8HY3PKtUsF7eXO6sw/td5ELyFbiNNXwR67sIWHzm6U0ll+9bY/ozz+3/7CdjHT014Ov6dnz7jbBZTKH8hxl/vKrSO8Zqcz0f8AFHeXW59bZ2fc2dv9nrt9DKWyZ5RHnek04UqVe1XoLMKpabFS+bLmlQ9dif9y7R7e9/StsWSBA1gqMnNz2ka+iUC9oYdbR4MwcF8604EnVeHrCot0PeNF7rFI48y0jBuYbSf3rONOgeh1sAoz7uC54+d98dWeSinsHw/HroJpp9abOLXeLCxwJ2bcGatGo67cOsLWWiPcxX5ppxMuyVmWqylTuIqanqYnAV6cp1TesNBsLPaC3Gk1cG6zNTXjfjR2vq3tbhYTuHs5zribtoVWw0q9DpZnuUjUMqen6TnluxNn3MuZV/7cbb8P4c7xEJdvjQYTueEZNwN3qWZuTss5PU3/oOppULpkludqSFVuHPSx3rQTX/y31pphg8+0JSPAbDu5kyZ+TWNKc1paadr/c/975GjgwvHUxFUwzb8Sttgxip5FnvU80+aVX77ZxWMXtsLs95HdzaVm3L2hX3qNNqZp06anPbvXzVW9unHQw7nNdjjcZRYt20KzgLPLB4ItYUmGrsRzt48nroJpRS0a0T+P046jNtuN1AxZ3+F+3bl8pfLwXvUSGtR0qfxc7M3wsuaV6z4EAPjQM3fCX3tSVpptAzUN3N2+CyGQOQ0sSmfc06an6QzqNZEzbsDsK2H+tZm11JK1zrqnNacBs+3knnVOOWDGWs97PWfiKhgwuZP7TsK406jX7HTw4p3FzrjDUnnCkc92wpl7kmdid4kfOb/pZxpL+pccLhdJyLgvbq9h/3iIgTv5fXTjoIdvfPsH8X989MWpX+P6QX+uMjlQTFc5AFzKaEx9IaWjXCuqVK4z7qxSOeD/bKcFvWf3unjg9PrUv4d2eomLRvaO/KOn6GhaYHnzyi/fPIJtCTxweh0fejYauKs93wZqGrgPg9nbeUsded9FxgP3xVNrsAy/y339Xh/3ZzTx6EEs066DAZhp7Ok8pXL9n6vKUvnByXBi+AowKk3rhrH9YPJV0hk34FdlFl3vedBz0LItrDUnf4zzLBq53R1g/3g4VrJ9/flNDD2Za7vVPK7e1sM8kgM3MDrLjProc/vwpMIHL+9N/RrzDF/RiiiVA/6b9pfvJf/3ffqV5I5ybXerjZOhl2vdZpbwHveUBOVND+/gA5f3Er/e1dvdqRPTosKlTEtoFotPTYt/zaKHsFy+eYSHznbw1Y+dw0eu3gnfzDLjroi/GSx/0NDnl9O+GV/cP8FGyw6/kVoNK7jLbXKpPPtF7pveeB++/g0XJs6VoubJuP3AnX+ONOAPWxCi4sCdknFvtf05zbo5TS8YiZf1tNfsdOBKFV5dmsdhz8V2SoOf/v7Omp6mG9PiGTeApZ1z66tgSaVXfSad1BPy1PN3AQAfubqfWQ0YuhIv3T3BA6c7cz3fWrOgjHtnHY6nwvJu1Ps/dwun1pt4/GL6GTew+JUwPYY4q6scAL79Sy7hZOjhdz/9ytjHpVR49tZx7o5yINrIu5wz7qTXobMby5lXfvlmF49f3MKXv/4cjgYuPnP9EIB/xl3l+TZQ28Cdbxe31m7YQTkp+5vxWnAVLPpCavKVsKErcetokDnT+c9eOo13fu+TmS9mujkt7xm3UgqHfXfmjBvw73JXOfL0Xs+ZuMMN+G8qttdGiz1GKz3TS+WAv9pxXoc9J3H4CpAv434maLiJlmx1E9KyroRd3evi/lNriVlg1vS0jz2/j1bDwtHAxaeDF9AkT72wj74z2hUwqx/62kfx33/DY3P9f6P0MVn8nNv1JN739C183RvOp/5MhUNYFswge0MPQoyvK03ypQ+dwWt2Ovj3n3hp7OOvHPbRc7zcd7gB/w2jJZaTce8d9pMD9xLOuPuOhxfuHOPR81v48ofPAkBYLvekYsZdhVkWjGh5JgJFr4JpD55Zx8uGBu6bh30oNd+1mSh9/pW3VN4duPCkmitwW5ao7DqYlCqzxH+604qccWeXyj///m2sN228++PX5n6erGcJA3dG5nP5Zhdb7QYuRAZanFpvYnervbQGNX0VLMmFlOlpBz0Hn7t5hO/80ksAgA89ezv17/+Bz+2haYtwV8Cs3vTwWXzVo7tz/X+jLqXc5f7oc/s46Dn4xs+7mPr/LWp62snQQ6dpT71yKYTAX/niB/Dhq3fCq3RAtKM8f8ZtBSs3iz7jVkphrzuYuMMNjOaVFxm4n7nVhVT+LIvdrTYeu7AZft95UsGucmwa6hq4B07uO9zazpTpaXqd50Tg3ungxkEv1/CWsi0yqCJKZ9y9nPPK/3/2zjw8q+J6/J/JBmGHsMq+qIgIigiCexXr0rpUq5XWatXWVqv91rba1rb218VWba17q9alra1b3VcUxKKyiKwJOyRsARICBJKQPfP745zJnffmfd8sBALtPc9zn/e+c2efM+fMnDnnTEu8pjlIMdBWkvKSihpskjvExe2p4MiOsio6tUuLa6cLwuSvnDSY15dsqXcB2lxIxrgz0lLITE9NuuNeU1jCiD4N7an3l2a5tTahKRjItZAdMlIbiMoXbtyFtXDO0X05sk9n5niKQmGYuaqQCUN7JNXJOBDgpFjhHfd7ywtol5bCqUckXli0JuNOdhe3D5eMG4C18Iq363bHGiOaseMGOVpsbca9a2811bU27hm3MYasjhkUteIZt9Mod8q5k4f3ZP76nVTV1EU77raCluy4uzWyitxeUklFdV29KZiDAd0zqbOBbenBBO58dV933E7s2VR/5fvCuNtSVO5u/+oWRzkNpD17PK3yRLttB988ZRgZaSk8PHNdwji1dZaHZ66Ny9z3VMS/0jOmPknMwdYUlHJE74bnrCN6d2JdYWmrO7TYXlJJaWVNzHWePhhj6BvHCcuC9btITTEcO6gbk4ZnMX/9zria5/nF5awuKOWMI3u3ar1bAu3TU+nTpV3Mjttay3vLtnHqEb2SKox175BBaorZZ8bd2F3cPgzs0YGJQ3vw0sL8+nFft10kMsn0W+LB/vAd7voi7O7UQVandk0u01rLj15cklTRcXVBKRmpKQzOElydNDyLiuo6Fm8qpqbORlrlbQEtYdyNIaPTKB8YR1QOyd0fthVsKW7dHXeyG4Z8aMld3A5SUtqOcdffxZ1QVJ5eLyoX5yvJGXevzu346sTBvLo4nw0JTMMem5XLPdNW8eh/cuPWJ9niJ5nb0x2llewoq2pwOxUI4y6prKl3eNFasLYJ10P26dLQlnv++p2MPqwLHTLSmOwI6MbiBmk/XFUIwOkHAeOGhvotOfl72LK7grNH9UmaLjVFdpCtIipvhkvhS44fQF5RGQs3iiKg+Cjv2Oyb0rp1yGhw4c6+QiJ3pw6as1jIyd/Diws284+5GxLGWV1QwrBeHev1EE7U2x5nrytSUXnEuA8oWGtVOa15TKOxe2bDpmAOBraCLbe1lquf+pS7313Z4jziwdbd5XRpn7bPYkV3xt1Uz2ktuYvbQYox+8UPclOg/krPBDea+YyyqLQyofMVH64/dRipKYaHZ65t8C0nfzf3vr+K1BTDjJUFMQuWujrbqC18l8y0hIx7jYrC43nvqvdZ3sri8g9WFJKeahgzoGvCOH1D3tOqamSXc/xgUTabOCyLFEOMXa2DmSu3M6B7ZrPOZPcnDAzdy/3e8m2kGDjzqOSMG1rHCUt5dW2T7a8Bzjumn+pd5AMiKm+qxzQfenTIaHUNb2cimGj3n9WMi0amLRPt+bm5OxJuAlYXlMQobXbtkM7ow7oye92OSFTeFlBZU0d1rW3BjjudsqrauCI6CK7zdDtsB4Etd8t33O8vL+DDVdt5/KPcVt25bykuT6pR3lRITzWkppgma5Xvi6g8LcVQ1UbXgxU3Uu9uyrjr6tTdaZybwcLQu0t7pk4YxMsL82Pu6C6vquXm5xaR1bEdv/ziKIpKq1i8aVf997KqGups/Cs9HchCIr4UpJ5xx7HR3R+Mu6a2jteWbOGMI3snPGoAmS8FeyrqveMt27Kbypo6ThjSHZA2je7ftcE5d2VNLbPXFXHGkb336S7t1oQB3TuwdXdwV8F7ywqYMLRHo0co0DpOWMoqmy4qB3HEcu7ovry5dAs7SivZuruiWTbcDo7q15ntJZUsT6L931xw0p94Z9wgmuU7yprWX+8u20a7tBRKKmrIyd/d4HtZZQ2bd5XHuHwGmDw8i0Ubd1FaWRPtuA807GnmBSMOAu9p8XcwG73rPH1IT02hX9fMFu+46+osf5q+hv7dMjHE35m1FLYUV7QK4zbG0EFvCGsK7AvjHt67E4s27mo84n6A3arjkOgO8a4dMrBWjmJ2llXFvYs7Hnz7tOGkGMMjHwZj+9u3l5NXVMa9l43lwuP6k55qeG9ZQVCXJvRhF+/MPQxrCkro1C4trg1/787t6NwurV6ruDXg47VFbC+p5Evj+ieN17dL+3r/0BDYbx+vjBvkvHHRpl0xRzPz83axt6qWM0buu0Z4a8GA7pn1dxWsLypjVUFJUm1yH1rDX/neqloy05u3Qbnk+AGUVNTw6Cw5mmmJ9OKi4/qTkZbCc/Mb93LXVCgsqaBjRmpC6WDgrzz5cd3awlLWFpbyrVOHAfElN25RG/ZsN2l4FtW1lvnrd0aM+0BDSf1d3M3ccTfir3yTd51nGORe7pYx7veWb2PF1j384OwjuPyEgbz42eaYndm+QGPOV5oD7TNSm2wO5q70TOZGNRFMOaoPK7eVtEjycNe7K/n5qznNTufALdoaM8HauHMvNXWJ/ZSHoW/X9lx+wkD+vWAzm3ftZcaKAp6Zu5FvnjKMySN60qV9OicOy+L95c1j3MnOuNcUlDKid0ONcpCF2LDeratZ/sqifLpmpnPGyOTnz/UmYXrOPX/9ToZkdYg525w8vCfVtbaeqYNok2ekpTBpWMvMwPYHOHqweVc57y0X8eyURs63HfTs3I6i0sp98stfXt28M26AScOyOKxre/42ez2QXB8hEXTrkMF5o/vyyqL8ZnlTTAbbSyrp3SUxrap3e9qIuNyJyadOHMSRfTrHNS1cva2hfwOAE4b0IC3FUFIR7bgPODT3ZjAH3Rtx5RfPFMzBgO4dWnTRSF2d5b7paxjWsyMXjD2MG84YTkqK4aEP9n3XXV5Vy6691a2y4waxpWzOjrtL+7QWiTTPUsI3Y0Vhs9LNWFHAnz9cxz/nbWjx1ZG7y6vVZjSBiZcyUefWszHlNB++ffpwAH739kpu/fdSRvXrwg/ODhyBTBnVh9yisnpmuqfcLUCTM+7Sypq4nsbWFJY2EAX60JomYaWVNUxbto0vjOnX6MUf/TzvadZaFmzYVX++7WD84O6kpZiY3dLMVYWcOCyrWWe6+xv8S4beW1bA0Yd1Sbi4D0OvTu2oqbP1xzMtgeYqp4Eof35p3AAqa+pIMcHd8c2Fr0wYRElFDW9lb21R+jAk8prmwM21xs7Wpy3bxrEDu9GvayaTR8S3UFhdUEL79JQGY9WxXRrHDuwGtO2VnvA/ybhbJipP5q+8orqWgj2VSRi33Mvd2N3IYXgnZxsrt5XwvbMOJ01F7lMnDOLfCzcn1EIGmqS85UzBWmvHnZme2owz7pZ5TQNxlTmsV0emryhoPLLCzrIqbnspm4E9xDTv9cVbWlR2ogtGHDgR+jq1f+3RhDNuB/27ZfLl8QN5K3srpZU13P+VY2OY3Fmq0OR23U3RzHd97BarDnaVVVFUWsnhcUzBHIzo3YnCkspGbxdrCryTvZUc+32TAAAgAElEQVSK6jq+NG5Ao3F972l5RWXsKKuqP9924AjoHN0tbdyxl9ztZZxx5MEjJgex1kgxsHhTMQs27mqymBxax5a7vKp5ymkO3HHGoB4dWnTDGsDEoT0Y1rMjzzXhUpimwPZGGHc9fU5yzp1fXM7Szbv5/NEyDpOH96Siuo5FIQuFVQUljOjdKe6uevJw8aIW7bgPMLR4x90h8Y47fJ1nGAZ0z8RamuWXurbOct/01Yzo3YkvjDmsPvw7pw8nLcXwYJxdd8GeCi57dA5fe2JeoyZTreV8xUFmRmqTtcpbcsGID1OO6sPc3B31i7BkYK3l9ley2V1exWNXjmfswG68sii/ReUW701+FWn9jlvPhpsqKndww+nD6dOlHb+84OgG2t6HdcvkmP5deV9Frk3RzE/k9tSd4Y1ItuNuRQW1VxblMySrA+MGdWs0bs9O7UhNMRTsrqgXhY8f0tB96eThWWTn72Z3eTUfrj64zMAcuLsKXlmYj7Vw9tFNE5PDvjPuqho5723ujhtEPH7qEb3i9ntTwRjDVyYM5LMNu1jjXY/ZUijcU5FQMQ0Cf+VFSUTl09QX++d1HCYO6yEWCmtjxeWJ/BsATBouRzFpkee0Awst3XE7E6B4/soT2XA7aMn1nm9lb2VNYSnfO/PwmNVdny7tmTpxEK8symd9UbDrXrRxF1988GMWbdzFJ2t38LSeUSUC59pwX52vOGjejrv5d3H7cNaoPlTXWmatTuz60sFri7fwTs42bplyJEf168LFxx7G8q17WLUtOTGJJ7XYXV6V0BQMgh238zjVHFE5CJ7M+fGZXDFhUNzvU0b1YdGmYgpLKup3wsn60YnRw4w78AqVfMcN+864txSXMyd3BxcfN6BJRyOpKYZendqxdXcF89fvpHuH9LgKUpOG96TOigvRmSsLGZLVocl3Rh9IGNCjA+XVtQzq0YGRCS4ViQeBv/KWHeu88Nkm6ixMGJrVovRPX30C91w6pkVpHVwybgDpqYZnP225W18QLe+yqtqENtzQNH/l05Zt48g+nevP7bu0T+eYAd34xDty2V1ezbY9FfW3IobhuEHdaJeWQhvz7f9Fxt2yHXd6agqd26fF9Z62cUd8G24HzXXCUltnuX/6ao7o04nzj+nX4Pt3TpNd9wMfrAFkkl7+6Fzapafwxk0nc+bI3vxh2qr6esWDLcq4+7aSqLxDM5TTWnIXtw/jBnWne4f0RsXlW3eX8/PXcjh+cPd6LdIvjj2M1BSTdNf92Kx1fOHBjxtoqBbvraZbZmJm7Nrk7pxuitlPGJLdOjRlVB+slfP93eXVGCO3kiWsT4f4jHttYSkdM1I5LMnYD+yeSUZqyj7fEvbqYtltXnxccm1yH5xJmDvfjsfwHQGduaqQObk7DrrdtgM3988e1adZOh2OcReVNN8euqK6lgc/WMPxg7tz6uEtU9ZLSTH7bFaX1akdZ4/qy8uLNjdZGhcPtjdiCgaN+ysvKq1k/vqd9bttBycNz2LJpmJK9UrTNSFXp2Fon57KuaP7Jj1mOhDwP8e491TUYAx0aqIPXx8SeefZuLOcDhmpCUWj/bq2JzXFNHnH/caSLazbXsb/nXVEXELeu0t7rjxxMK8uyueWFxZz67+XcsLQ7rx+48mM7NuF31w8mrQUw49fXhp355iTv5snPs7j6MO6tPgMKwztm2kOti+MOzXFcMbI3nywsjDhFY91dZYfvbiU2jrLvZeNrZdaZHVqx2lH9OK1xflxNXa3FJfzx/dWs2zLHh6fldeg3sl23O3SUsnUfujcLq3V+tbByL6dGdA9k/eXF6iCX3pSRh9PVF5YUsGMlQUc0bdzUsKclprC0J4dm2QSlpO/m1++vqzBfcjWWl5emM/4wd0THiPFg75d2rNy2x5yi8oanG87aJ+eyvgh3fn3Z5upqK7j9IPsfNuBc8B09tFNP98GFH9SWuSE5Z/zNlKwp5IfnH1Em9u0XzFhEMV7q+u1uVsCTjqYyN0pNO6vfPryAuosfH507DhMHt6TmjrL/LydgJxvQ3Jp1H1fOY5fXzS6WW1obfifY9yfG9mbX11wdIvuU010683GnWUMCl3n6YMolrVvEuOuqK7lvumrGdm3M+ckmezXnzacjLQUXl6YzzUnDeVv35hQr/ner2smPznvKGav28Fz82PFVKsLSrjyiXl0aZ/OY18f32h9mgpN3XFbm/yGrabClKP6sLu8mgUb4tt0/2PuBj5eW8Tt5x9V72/YwUXH9Wfr7grm5jW04fzDe6uwiHLNo7PWUaga6NaKhm9j9XbfmysmbwoYYzh7VF8+XlvE1t0VSZ2v+HVxYvXtJZVMfXweO0qr+Ol5RzVa3vDeHcnJ35N0t7S3qoYb/rmQp2ev57wHPuJTJYAgriXXFpY2SSnNh75d29efVSY7Z508vCdVtXW0T0/hxGEtEwnvb/ji2H5cf+owjh8cfwGSCIwxLXLCUlZZw58/XMvk4VlMHt72pnGTh2cxsEcmz7ZQSc1aywMz1tA1M50x/ZPrSCTzVz5t2TYG9shkVL8uMeHjh3QnIy2FT/Sce02BSKP6t5K1zf6C/znGfezAblw5aUiL0ibecSe24XYwoHtmk+yv731/Net37OVn549Kurjo1bkdD14xjr987Xh+8cVRpIXu9r1iwkAmDcvizrdW1CvF5RWV8dW/ziM9NYV/XjexVZFTzrgb91VeVlXb4is9fTjliF5kpKbEFZev217K795ZwWlH9GJqnPPiKUf1oVO7NF4Nictz8nfzyiJZCN11yRiqa+v443urAaiorqOqpi6h8xUHbkfeEjF5U2DKqD5U1dQxa/X2Ji8idpdXK9OeS/6ucp66+gROaILi0ZePH8i2PRX87u0VCePc/e4qNu7cy68vGk1meipXPD6Xh2eupa7O8tLCzWSkpsQ97kkG7vgmIy2F0f27JIw3STV8Jw/vmfAWtraGEb0785PzjmqRFnJLGPff5qynqLQqxpSwLSElxfCVEwYxN3dni27Be3VxPvPydnLbOSMbnXuJ6POeimo+WbuDz4/q22Bz1T49leMHda83LVy1rYTD+ySXRh0M8D/HuPcFusdxnu+u8xzcKOPu0OiOe8GGnTz+US5fnTiIk5twNjVlVB/OGR1/V26M4feXHEN1XR0/eyWHzbv28tXH51JbZ/nndRMZ0sqKPJkZaVRUJzd3Kyyp4E/vCyPsnsTtZVOgU7s0ThyexfSQPXdNbR23vLCE9ump3H3pmLgTMDMjlXNG9+Wd7G31u0lrLXe+vYJumenccMZwhvTsyNcnDeGFBZtYsXVPcDNYkjNu8HfczbtRqalwwpDudOuQTmVNXaOMu316KhlpKeRuL2Pq43PZvKucp75xAhObuDs9Y2Rvrj15KH+bs4F34tjjzs0VJcirJw/hyhMH88ZNJ3PO6L7cM20V33h6Pm8s2cJZo3o3SnDD0FcdbRw7oFvS44Yx/bsycWgPLtd7uv/bIJ73tK27y7nt30uZl9tQWrSnoppH/5PLGUf2amD73pbw5eMHkJpieH5+85TUdpdX89u3VjB2YLf6u9iTQSJ/5TNXFlJVW5eQVk4ensXyrXvYWValPsqb73TmQEPEuJsBPTqmN1jRbS+Nf51nGAZ0z6SgpCKhr/Pyqlp++OJS+ncTMXdrwOCsjvzw7COZsbKQLzz4MaWVNfzj2glxL5bYV8hMT6Wqti7umfOmnXv52avZnHzXTJ78JI/zx/Tj/DHN24XFg7OO6k1eUVnMOezDM9exZFMxv7lodL0Xrnhw8XH9Kamsqd+xf7hqO7PX7eB7Zx5er4190+dG0KV9Or99a0WjF4w4qGfc+2nHnZaawudUESuZ8xUHXdqn8+8Fm9m0ay9PXn1Cs0XKt50zkrEDunLrS0tjJEZ7q2q49d9LGZzVgVvPORIQS42HrpDzvznrdrCjrIqLj2uemBwC72njE5xvO0hLTeH56yfV2+X+t0H4opGc/N1c9PAnPP/ZJq54fC5/en91zHx74qM8dpdXc8uUI9uiugmhd5f2nDmyN89/tqn+5rGmwL3vrWJnWRW/vWh0k442E/krf29ZAT07tWPcoPj4NHmEbJLeWrqFHWVVSc+3DxaIGHczoHvHDMqraymvqqWssoa/zV7PZX+ZA8CRjQz2gO4dxJY7wb3cd09bSV5RGXdfOqZFrkATwTdOGspxg7pRXVPH366ZwNGHJb6ZaV/A2Yv6CmqFJRXc8vxiTv/Dhzw/fxNfOq4/H/zgdB6eOm6fbySD4Jal6eqUZOnmYh78YA0XjD0sxvY9Hpw4LKvexramto47317BkKwOTJ04uD5Otw4Z3Hzm4Xy8tohXF4tYPZkDFkmzf0XlELjNbMpxQ4+O6bRPT+HJq06oFy03BzLSUnho6jgAvvvsononQk5EfvclY2LuljbGcOWJg3n5hsn8YMoRLXKKMrJvZ4b27Phfy5CbCr06y5ltdW0dM1YUcNmjc0g1hpe+M4mLjxvA/TPWMPXxeWwpLmdXWRVPfJzHOUf35Zgkt6+1Ffzo80fSMSONL/9lDg/PXNuon4nszbv5x9wNXHniYEb3b1p74vkrn79+Jx+sLOTso/skZP5jBnSlY0ZqvQntocC4W49DNAOMMecA9wOpwF+ttb9vi3o0F5y/8jtez+GdnG2UVNQwdmA3Hv78yEbFjwPrTcLKG4ip5+bu4KlP1nPVpMGtrlCSmmJ45tqJlFXWJPX1u6/Q3jHuqlo6t09n2rJt/OTlbMoqa7h68hCuO2Voqzl7cdC/myibTF9RwFWTh/D95xfTs1M7fn1h4xqfqSmGC489jCc+zuPRWbmsKSzlL18bR0Za7Fr2yhMH84856/nrR6Jh3pj9+f4WlQOcekQvOmakNsmU71cXjqZjRto+EfOBPTpw9yVj+M4/F3LPtJWceVSfehF5Irwf3b9rkwluGLp3zGDmD09vcX3/W8CZhN03fTV//nAdRx/WlSeuGk/vLu05fnAPTjm8J7e/ks2593/EcYO6UVZVw/enHBxn22E4vE9n3v7eKdz+Sjb3TFvFJ2uL+NPlx8aVitXVWX72Wg49OrbjlrObLj3w/ZVndE3hgRlreGjmWgZ078A3TxmWMF16agoTh2XxwUo5djuyGfb2bQUHnHEbY1KBh4EpwGZgvjHmdWvt8gNdl+ZCTyXGLy3M59zRfbnm5KEJxS9hGKBn4PdMW8nawv6cNaoPA7p3oKxSRI6DenTgtnNH7pd6d2y373duNwYdVDloe2kl90xbxYsLNjO6fxfuu/xYRuxHm8ezjurNQzPX8tNXslm3vYx/XDuhyWeqF4/rz6Ozcrln2irGD+4ed4eXkZbCj889im8/swBoXFTurqzcX6JykPF89/9ObZLmemtpW597TD++Pmkwj3+Ux8sL82NE5BHsH+il9ObhmeuYMqoP93/l2BjpxkXH9efYgd24+blFfLhqOxcee9hBzXS6Zqbz4BXHcerhvbjj9WWcc98sfnXhaE4a0ZPuHdLr9VGem7+JJZuKue/yY5ulxOrmw+JNxXzvuTwWbizmS+P68/8uOLpRh1uThwvj7tI+Lam9+MECbbHjngCstdbmAhhjngMuBA56xn3qEb2465JjOPnwXs3WyD6sa3t+MOUIXluyhV++sZxfvrGcUf260CUzjU279vL8tybFTMpDDZxP5KmPz6OkopobzxjO9848osEOtrXhrFF9eOCDtby8MJ+rJg3mlMObLpod2bcLI/t2ZuW2En56/lEJNUk/f3QfJgzpwafrdya9Sxr2rzmYD029rKI14afnHcVn63exfOseHvnquEMaXw8FGKYe4645aSi3nx9fM31Iz478+9uTeXVxfr0/+4MZjDFcdsJAxg3uzs3PLuKmZxcBMm+G9erI0J4dmbGikBOH9eDCY5Mfd4XBHU/d9OwiOrdP44ErjuOCsU3Lw0k6j2zEv8HBAm0x8/oDvnrhZmBiG9Sj2ZCRlsLlJ8R3R9kYGGO46czDuenMw8krKuP95dt4f3kBn+bt5LqThzJh6MGjBdoScIpSXTLTeOKq8fvk57g5MPqwrvTr2p7M9FR+fG7zlfp+dv4oVheUJJWcGGP442Vj+WRtUaP6B2613lqXtxxM0D49lX9cO4F128sOeXw9FGBE784suePsRnedGWkpXDb+0NKsH9G7E6/cOJnZ63awrrCUvKIy8orKmLNuB3XW8usLRzebgfZXb39jB3blT5cfW+9quikwsm9n+nfL5LgmSlDbGkxTbpJq1QKNuRQ4x1p7nf6/Ephorf1uKN63gG8BDBo06PgNGzYc0HoeKCirlIsADoVVXjKorbO8lb2Vz43s3arKdU2B3O2ldGyXllSL/EBBbZ1l/vqdB61DkAgiONjBWttieli4p4IsvaimubC7vJr26Smt7vGwpWCMWWCtjeslqy123PmAvzwcoGExYK19DHgMYPz48Qd2dXEAYX+fPR8oSE0xTRZLtTa4SwMOBkhNMRHTjiCCfYB92cTsiwLuvjqFOpDQFuZg84HDjTFDjTEZwFeA19ugHhFEEEEEEURwyMEB3+5Za2uMMd8FpiHmYE9aa5cd6HpEEEEEEUQQwaEIbSKntda+DbzdFmVHEEEEEUQQwaEMkee0CCKIIIIIIjiEIGLcEUQQQQQRRHAIQcS4I4gggggiiOAQgohxRxBBBBFEEMEhBBHjjiCCCCKIIIJDCCLGHUEEEUQQQQSHEESMO4IIIogggggOIYgYdwQRRBBBBBEcQhAx7ggiiCCCCCI4hCBi3BFEEEEEEURwCEHEuCOIIIIIIojgEIKIcUcQQQQRRBDBIQQR444ggggiiCCCQwgixh1BBBFEEEEEhxBEjDuCCCKIIIIIDiGIGHcEEUQQQQQRHEIQMe4IIogggggiOIQgYtwRRBBBBBFEcAhBxLgjiCCCCCKI4BACY61t6zo0CsaY7cCGVsyyJ1DUimH7I8//lrCDrT4HU9jBVp+oHw6+sIOtPgdT2MFWn0R1bCkMttb2ivvFWvs/9wCftWbY/sjzvyXsYKvPwRR2sNUn6oeDL+xgq8/BFHaw1SdRHffHE4nKI4gggggiiOAQgohxRxBBBBFEEMEhBP+rjPuxVg7bH3n+t4QdbPU5mMIOtvpE/XDwhR1s9TmYwg62+iSqY6vDIaGcFkEEEUQQQQQRCPyv7rgjiCCCCCKI4JCEiHFHEEEEEUQQwSEEEeOOIIIIIogggkMIIsYdQQRNBGNM77auQwQRHKoQzZ/Wg/9Jxm2MSTHGXGOMmWeMWWKMWWiMec4Yc3ooXs/Q/68ZYx4wxnzLGGM07GRjzC3GmM8bY1I0LMMYc7kxpof+TzfG/MwY87ox5k5jTAe/DGNMVpwyrtfn18aYk0L1+FkT2vh1Y8xDxpjXjDEvG2N+b4wZ4X139T67WZ0XpP97nLAeof9xywjH07BxCcpJ8947GWPGxylnqDHmS8aYkaHwD+Lkd5P3nmxc1hpjenhPFvCpMaa7X74xZqQx5s/GmIeNMVnGmF8aY7KNMS8YY/p58e6MU5cOxphbjTFzjTHtjTFXa13+ZYw5TuOcZIz5ozHm/Dh1ftIY8x9jzDPGmIHGmPeNMbuNMZ+59F5ZYVy+0xgzzBjzQ2PM/caYexVH+uv3TGPM/zPGfGqM+YMxpmu88UnW143En+K9X6DtH9lImtVxwiYaY7qE6vyGzqGuXrwGc1fDU8PzTPvlSWPMh4pzjxtjcnQefccY831jzM3GmE+MMVcaYzqF6tTFGDM8FDbSGHNdnLjneGkmGmO+bYw5S8OmGpnDNxpj0r00Y5L1Uyj/nvr7C/29XvHt70bgdmPMm8aYxxSPftNIm8/RPvNp3ThjzHEhXLrFGDPYJJk/Ws44I3P3WmPMEA3vYYz5hTHmqVAd7zHGdE/S1hh6Y4zppfUaY4yZ6MVzc2iOMeatMN4ZY64J/R+h9bnOq880vz6J8Gu/wYHy9HIwPcBTwC+BAuA+4FfAHiAfeJBA236hl+ZnwDQgF3gR+BPwTWAx8CxQpXlcCMzT983AF4E/Ak8DpwHzgec1z/FAJbAWcen6Vy3jKi1nJfB/wALgXq8uCxtp3++AUuBrwL+Be4A8YBHwZa/edwCfAD8GugNdgGu8fAYAM4BqYKe+vw68ofV+XZ9RwGoNWw9M9MqY4ZXh4uUDW4CvA+OA47WvjgPGeeVfreWuBs7VPpkB7AWu0DgXatt2AhXAJmApkK31Xq/Pl4BLNOxL+rhx2at1rwJK9LFAnT55+tTqb67Xlr3ADuBhLfc24EngQ433AIJTu4FH9emhz6uarlTb9RDwgvZPEfBrYLb21XQdRx+Xtmn4FdruO7QfdwPFwBDtoweAQv119dmL4NwcLeNhYDuwHDgdMW25T/ulDNgInAekajv9J1vjFWvcnwLp3ji+GgdHN3rv5dreMq+MEmQO7fHGpNaFe2mXAWn67up8svbZy6G5exU6d730rwD/wptnwCzgOzoOOcAP9H+u5rsO+If2YbH29wvAxToWWxDcXwacANwMrNK46xGcfQZxkbkQ+Lz271btg880/1eQebRUy5yqda4F1mi8UY3QgoWuv7UftgNvaX6bFBdOUVxYgszTZG3+DzKHthPQulXI3PsHAS5ZZD5tJf78OVnrtEHTvqpl3AS8DdylZXyodbxE67UDxS/gU4dfxNK0hdo/a7UO8xD8fBroisyhpdrehQhO3aR5natxP0bo0TIdkz0IrXP1WYXwjddIgl/7jYe1NRM9AEz69TjPboT5lGmcuToQ/4dMxnzgfmCVPwGAjgjzS0eI1Xygl4YNRRjtHuBIDRuMTK7FKCHTdEv1faYrAzhCEaSj/l8KZOt7GkKUFgDtNO8ByMSr1MnxdwLCXIQSN037iabprsjv6n0YQrRq9dmoiP5LbeMLwLe07f/R8k9DCHu1vp+GEIJztYwJyOR1Zbh+y/bi1Wn7dmsfzESIdy7wgdZ7lLZtA8KMyoDhcfpwtvb96zppVmq/D0GIxwzgeWSx9pS28ymEuS7Wdj6g/bfcG+8dwLvAMV5Ypfcer80b9dsmhDBvQCbzVVqXQoQYOUJWqb9VCBM2CKEw2sZdQAcCnMshFpcWef2wUfv8aP2fhxCvE7U+O5GFkqtPDbIwukrL+BBYAQzSfBd6ZXTX/Gcgi931wHvASK+vKxCCei5C2GYD7xDMNzf3cvWpJsDXQgS/y70yshFi2Mfr8zxkcfk7hElMBVZ437d774uAxaG5O07Hag3BgrEKXTASzLNignm20ZuPbix6at0WAWMQxnAlwnBqgOeAs7WslQgedNL4QxCasMWr52wNX6p5L9E+SAVeAn6vff66/l8MjEbm/VoChusvdtzjFjs12g8OX9KB6gT91Vibz0BogaN12cgc/IwAl36gvysSzJ+Z2ufZwOGatpv2YaFXp3x9fx/4NkKnHX4t9eLNB3rp/08J6OoE4G8a55vIRmaxlpuGzLUcLfdP+m05MAmhASdq2FHaf64+i/R3sYZ39Po1e7/ztbZmrPu9gUL8zidgMqfp4E/VyTEOWWE7QrUcIV63IsRoM0Lkl+j3JQghy0Z903qDuAjI0fdcZAWeG0LeFV5ec5GJfRxCRMq9eCvRieSFbUGY8BqEqVYA1yOLjGUERHkjsEPTDNJyXL1XevX+AGHCi5AdqEPc3yAEzE3kFOD7yEQ9Ns4kXBTqm6VeGT4DcPEuQRYCa7088oiVcLwFrPMmX5X3zSdAn3rhFyO71wv0fz7CCL7jxanWeJeExuV4hMDdrO3NRRZHLyK7sM6J2uy17zf63hnZ+e0CDvPKHRQaT9e/m4An9d3hz1JNn6l1uUTj+XWeg+xSvowwhzwNPw0hhEcjuP4VhDn+y6tPFdBO37tr/BeBbyCE7ClEIrQQWVTO17h9CXaQFV5fV4ba9jWEaVyLSCbc3NsL/AFh5g5f1+tvUaiMpVqGPyaOkV2EMLLNwDc13Q5gvL6vQ+bE8d4Y1SEEv4RgwVinvx+E5tkCZB4VaT9kAyO0TpnELm5yvLTLEQbjFqD9kAXJzV78TlqHh5D59rG2LwfIQGhECSKVWQy0d+MO3I7geJaX3wQER2vcOIXoyHHIwnCJ1r87QhdqCaQyi5FFwAmNtNnhfQ4BrmYjC52Fmreb+wN0nOPNnwWOHoboRCqyyHwVwZvdyKJmsbZ5uYdfFdq2JXh+wvX/ohC9cPR4s/bvilD8VOAJZM4tc/PSm4vdEXxy9VmJ0M5cFL/C83q/8rX9XUBbP8iq/4xQ2OeQSVmOMIyJipS9gLu9eDOR1XSevvcjEL1W6qD107SdFbkmaNqnENHMLn3vo+E/RQjM55Cd7SZFrDxkcvXTeC8Aq0P1XghchzCBxQjjnazffES9HJnE72s7z/fqXerVewlCRBwDWUAgUt2JMD5f5LkSIe4PIQTPic23Iyvt9Zp3lVdGMcKEd7t4HvEq0vwGaXyfcS/S/H+n5ZUgIq6TtOwaDavy+iwDISL3IiKszQhB/J6O3wRN85T3uHHpizD5m4GP0B2RfrsAWfzEa/OvtC05obEagYixZwI/1DEfG4rzV017kxd2F7J7KEFE42/ouORr//t1/pzm+w6y+y3Qfl4GnKRxBiC4UoIwMb8+S4HHNd9vIGLEZ5F5MQ/Bs0pkkRVTd817pNfX1UD70PdPtd5bvbAPgMnALH+s9TcvThlD/DGh4WL2V9ruPEQqU43gUrGW7xh0P2Tx8wnevELmwzmhPM9E5qJFRLovIfO4EpGkfITM41kIc13mpZ2NSoa8sP9of/qM6ys6BnU65i8hCyu3a74ZwcddCE7f4aXdoGO8IVTOb4DrQ2Gu/Rv09zvaX4UIo56uT5G2eUUjbV6EMNBlBLTue4pLOx0uaXgv7SM3fyzB0UoJwgzfRBigv/i5QsfF6phN1//5wLe8eNt0vGt0zB0deA2RRmcMlqkAACAASURBVJyE0IwnCejxbn1/D1lI9gVmeHmu1zH5kdb1+8ANmq7Kq89O7ZuV2q+u7CwOwGUjbc5Y2+pBRCQ9vf/3NiNtCsqA9P8JioRDQ/GGAF+Lk/4MRHy7SJH4HWTn7DPJVL8MDXNM9UFF4t4EjDDMOHogq+ZuSdoxHbgGEQfdpJPV7YK26W93jdsXuFPfz0cm82ne00m/9QFu9Mo4DREbXh4vHrJinokwwmJiGWMf4CeIGHC5Tpo3kTO0fnHa0w2YpO9jgW973w5DFkO5TRjffsB5obBMRLTcaJvj4NmNwDPNwK9JwIn6PhxhtJcBKY2kO4v4DLYbcHu4PsiO/FJgZCh+F+2/44GLm1DfscgC7LQ4344D3g/hZRivT2/qmCCMJSX07WoN36J17pMkny7I/KlfMDZxTHoCX9CxmBKiBe1CfTEilHaAPl8NhR+u4/CK4vyfEablpCLdkJ3njaF0U4FzgDVNxalQ+lRkkdsBERePTzCfGrQZoXWZfps1fAoi+RuZoMxMjTPYe9I1fADwpTh1HKTvacgCsQEuhvHLw5VHEVrxW6CzhnclmFeZQGac/AYixzB/QWje9xHpwlvAaK8+ifoshjfsr+d/1uWpaqL2stauC4WPsdYu9f6fChRYa1ep1ukkRMzylhenh7V2Zyifscg5S4VqGV6NiOWXA49ba2sS1KsTIpqsQkTJfvqpCHH6EN39WWt3GWP6Ajdba3/aSJ651tpiL/wY4OfIefJi4EfW2q2qAXq6tfalJF3YYjDG9LbWFnr/DbLzDGuWL7DWlhpj+gCXWmsfDqf18rjAWvu69z9umxPU5+/AnYiyTX8Nzkf6d0Wc+N+w1j6l7zcjSlCbGykjpn6het6K7G5qEfHgDGtttfd9NEKg1lhrpxtjpiK71hXIbq4PMM9aW+rle4619t045XUHaq21e7TfJ4Ta/ClCsAdofXL9fL18+gJYa7cZY3ohCk6rrLXLkvVDgr7paa1Neo+xMWYo0gfnAc9Za6dreDdrbbER7ewHrbWHe2m6IgzOb980jX8cwgyOttb2DpU1CFkkn4Isbq9GcHMZIiXpjPZhkvpOsda+r3TmcKQfd+m3EQiDX2GtXd5Iu2+w1j6SLI7GG2etXZjk+0hr7Up9PxXZdRtkh9iApsVrS5K8s6y1O5LV2xhzMoJrOdba9+LkMR5hmrWIRGRlvLA46QYh+jzFqpU+Hlhprc1JVF9N5/BpdThuGB+NMRmIPoDV/2cg+JCC0IiEvGG/wf5eGbT1gwz8cwSinnRk97KFQKx4gsY9A5mwrwEvIyLLhQgxcxq+TrR0D4FmsRPZLCbQRKxECMWZiCjs38i5zJOIuPDLyMR5DdlF34AQio3IDrQaXWHGSe/OQxciGo1h0dwj3rvT3sxFxPLnefXOQ7XAQ+nPQMTTrh+eQKQDm5Cz7+5eXP+MeQwiEit18Qg0qBd475uRncYfEIb9OLKqfRE9c9P8esR51iOKQF8n0A6/BDk7df9dmz/12pyufbVN2/4WsRryu5FF1df0+bGO54+9+nwXYWobEVH4LALt2QU6hr28evjPNvfu5XeZ1rGUQGt3DiL6W0+gSb9N27eAQNv4SkT8uhvZla3X8t/RtuUgosFiHbvXNK5TQixExH3vIszor8gcccqZThvXLSYuILC2uJ4Ad76j8Z5Bzr2v1TjuDPIjZA64tOdqWl9rd72Wu5Rgjr6q8V8lsBx4Ssu42uvDGmQ+XosnXULwYx2yi/2ZPn/RsK87Ggx0iUMzcpDd6EaCufddAi1l14cbUUVOL63TFt9IoC2+E8HDL+u4rUYkbq7/3RzYiuDcr4FbEAWvIkQE/jqyo70X2UWegjCPhFYZoTY5hbP7EDr2qeLDbGTxPh24J1laff+9ti8bYZK5WsedCM1w9a7W91sINL7v1HouJNCQPw3Rr9iELF7fJBClf+SFfYJsWAZ6dfmx4sV25AhxJUKr9ug4dPTivuq9X0igwV+j4+3TndXE0r8C4Dj99iPts9nI3NpCwBuS9mOr8rW2Zqz7vYGBNuKxBNqI2QRn007z8yWEMKwnMKHK1zhfJdDwXUig4es0ixcjRHgpgSbicgJNxAWoeA94hEAk/IzmeyWyuNiETjzU3EPfFyCruzSEaO7RstxZ8k5kkfF9RCTsnxXPRCb3QmCYTpK3gHP1+wRgthd/p/aDb0rmTCuuQsRmyzTPHloPx1TnIsQp34vnzKmcBnWehhVpX+Vo3IEI8fWVhHxTrD36W40wyzKCs6uniNUWj9dmZ0a1GtmpTiPQkK9BzotP88r2zZyc2VOFF/YWouzitGyXIURju9Z7MaKp7upXQ0DsfeuGt7UtTms3GziVQGt3uJbdR38LgFStYzaBgtAQhNg9hohbq5BzVIPoMjhlIKeEuBKZD495bZ6r/bCCQBt3FXL2WkRgbbEWmQtZyKKjL4Fi0mIC85itGp7vpV2NzAtfa/d9hAGuIL7G8Gz0GEr7aSWyGOikffAF4J/aX69pu1cT55hI6+ifcbuxWOm9l6BWJwRzzylyLvH68C0tZ72Xdo+X1mmL5xBoi8/XfpuFnGNvJZgDpQhDzUXMmu5AFjTrkPNu39Rqr/bNTAKrjM0IDXnAexZruZX6f4f+/lnzcUdtbxCYPLnnU61vBcECdAOyUN6u5Z6g/fWWjrGrd4337ixMXkLm4QZiNeSd9clQZFG6CDnCec+FaR2nAO95Y7cMEXlv1jo4rXK3KdtJYKa32Es3W/vkaB2X9QQWGL/TPvLpn+MDX0ZoSaaWnYZn/aF5pxM6towYd8sYd1iZxe0EhhNoMsZofhKYUOUQaBM6Dd+FyPnLcgKlGl9z2mkiTkOI4GJF0MEavlyRJl0RxOWRBuz16jkNJTAuPaI49KQi2QBFmhORSTgDWRRsUyT+lmP6oTou9Mp0ijDOZMTZL7tw1w9OW9wxiTM0Xj6xDLnevMmLtx3ZRfqmVr6Sjr+aDy8EfqbtOhnYrHHyEGIR1haPp7G6yGuzM/1yGvIlBBryVW58vDwKkEXZOoIzuXUIId5CoGXt+tU3s7nFjYOXXy0NrRtyEWZQQKC16xQFcwhMhpy28TKtdw8Pl8Lase8iu7LKULi/mFuA4FAaIlb042Wg2v7ab659zlTsVoRp5CI7qCWhvl5EYH7lFrnZCdK6ubI49Ps1ZD4O1zx8qc7NBHa/61HLA6/sy5BdUi3wYhx60BXvbJjA6qTAG5dPFUcKCObeEoThLvH60KXd4KXNQyQ8BQTa4osQcf0yhNm117BUDXO74UGI1KmAgBFUESzUnKnVJcgiK2yVUYKYb17lPeXIwrFE/2/W3+uQBWam1w8bicXPGgSfXB5PIZuOpzW/uaF6+8qnlQjNqFfW8sbX4crtyAIni4Cu+hYjy7ww37wtnqlbIcHmaBEyZ7oQmOlVa/3P1vFdEsIbZ4GxgQDnHf2bjRxN5Wh/OLPa9ni8QdOk4tG6/cbX9ncBbf1ox4a1XZ14ztd2zUbOCysJTKjuQsQ15QQavuWKJOsJNIs/QHbC2wg0EccjxM7ZjO9CJu1e4Ewt810CEWG2IqJTBhuErMBneendKtul94mxY/KpCGHbSaz2ptvl7/Hq/QCyK4yxtSRgDL4pWVditWc3IMRihxfm4m3ywsYQMPV6sxDk/Lne9ETj1hK7EMjTcsr0W2dUmYiG2uLONtxvcy6yS9jot1HTLyfQkHcatu8gO9bHEAK3GU/jGBFRPo3s6n6K2P3nIBrZb4byT0F2Ua5+e2lo3XAXskDLIzjKeR3Zze1A8OqPyE51J8HicgYiWi0F/uzltxQhNn8H6rzw6chOrD+BEuJPEFzajuhOTNW2bEFEyk4b19mQ+z4NFiDn7ncAAzRsJWKdsZqGzNzf7XwA/ELb7ebKKoSRfOzFqyVwgONbDvhmSEO0X7/nl6fv30YY4J+1X3+q+dRpPzriX6N51HhpB+q4FRPMvZ3InL/M68N3kMWpv4O/TPtnFYG2+O80jzkIvjmnOp8gomt/DozQcj5Bdp0NzPb0PZ5VRr2VSai/JxOYCjqaNt9r3+2a1+uhtG6cfQuAm5CdcCEiJbkfYfL/T/vM1dtp9+cRWJisQK1vvPxmad8UIccH9yJ497T2kQvbqOPtLzSfRqRB5cim5h+IdLQIeCHUllqNV6N9ugSRFGUQLBQGaJySEP0bo/GLkbm1DsHdEn13vOF27Zu/7He+diCZaFs8CGE4LRQ2Fjmz87VdL0eYRLYiyfkafi6i0AKyA3gEIVinK8J2Qib63xUJw5qI5yNnKpcghO0dVBtZ8xysz3hinWv0RJjOUV76HDztYkS8nqJ1nxcnT/eka10vQHaxpxFoRE9BiIyzlS3QfvBNyZwW67+8Mm5EzvAe98Kmohrqof4ehDAaZxayU8v0TU/W6qS6NsE4bte020Lh/RFx2MZQmzOQFfa/EOL1FCHTL30/H9n9pWjdL9HnRHSnEyrvauRMtwiZuGs1fdcE9U6qzY7sznyt3S4Ik7kdwa1LkTO+pwkkBN00/AtAXy+v671xPckLPwVhqDnI8Yxjgifq/wf1+SUi7q/XxkWIZr02rjeeaaF2fIgQ7cUE5lf3EjKPQebKowhDdXNlK8LUjgrlGU9jeAVqOaD/f0ogZQhL17ojYvMfEJwXH5FgHDbFCfPn3gU6juE+zAIuCaUbgTBIX1v8YkQf4E/a148hTC08Bwq1zI4IQ1hLyGxPy3CmVs4qo5D4GvvxwppktaB4MyhOv5yOMChnFfM2stNP9+o9K066u5H5NtQLS0cWM8XIWXiqhn0POapxYb/R+gz20qYhx0Kv6ftkzSsX73w7wXifhfCBeksUb37vwqN/Gt5H+/l7ikuXI7Sz2dYfrfG0OWM9GB6EWB6PnKckNKHy4nXfD3XoCPRuJM4QZAW6HSHEq3XCPu9PhhaUnUKsrWyjpmT7UFYmalYRCu+JKAA1MGfS7zclSttK9TLIwsqd5U3UfnGLpAz0XL8JeTUlTgNcag5+ATc0J3x/P6gjljjhDcwam5FnmvfeSXFyFrqA8eMhC+faRvJ7HrU9jvPtrkRt2Z/zPlROT+IvFuOa7Xnf4yrZuTwTlNOHQLktrvlcU/C4me1rEm4CWftQRlzlvGbm0SL619r9lbSsA1VQWz2IctKTyIrNaW8WI6u0IQSan3ORneaXvbTPOMT34s1DRNGzkN3D+4jIbT7BjuhriBj6m6g2bahO64Aj9f0kZKV2fpx47yRoUzay0s9CVnhOQ/1MAg318Oo5FdmRrcXbjem3n+lvvf2yIu7FyE4jEcHopO3/PsL4b0JWpc+E+iYfEaUZZIf0JrIqd8cCQxFmeWQTxvMDrVu8coqRxcdwAo3qz4CzvfTH6FhvI9B8P1v7pZhAw3ohIgHYQeCTeYame5pA+WcaulMk0NYvQxZXpzeCS1sJtI1d2EzkeCUfkUzsQKQgM7TvfG3j1/Rx2ru/RXDzfUTj1mnrv0as1qzDz2/h4WcIR5xjHzd/PiSYPxsRce/1BFr9RYS05r22XuuXr+G+T3yndLmGWB/opTT0U78Fzz4/lKcvZfgSsitsTLM/rP1/CSIuvUr/u3GZTkP6sFNx5elQP4atMn5PQ9vuCxBvY75yYFwrEf3WC9ldj0F27CfFiRNPY38LgsfZGrZOcaQaEYVPR3byOZp2GbJofV/bW4pIq9zYb0Hm75Bk9SbASfc4nL0FuEXjnKxjeqlHc3K1fsXAVxqhBU8QLD7cs1n7we2EDXKU9SAi8XB+7X3XuRtD+T5CrKVAFx3DFwjuSDgJkZbs9PrL+X+flKzerfG0OWPd7w0MLgzwneevRDWYCTQ/a7XjC1DH/Xg+Z714nxKI1TchK+GFCNOcQ6BR+4CmeYNYwvCmThpnYrZEEWUeIhpyCPhDRGQTj7Bs9xDs38i56HTkvOtKLf9fIYR+BRHT78a7tASZkLkEzPdHCLObTmCKMQ8hBqMJFMe+oe0uIzBlKkIm/21e37yNiPS3ETjo/4jAQb9v6rMaOZt0Psl9Ir4aIT4VyJlkHsHlGpfqON+u8TYgItLLEMZXQnDhw8eI2H8Jgeb7Wh1b/4x0kcZfS+CT+TaNv5nAbCwfNRsjsDJwrlarCbRac+LgUjaBtrELm4Yscnx9glKNs5ZAU9d5tcpBzozvQM5GyxAiUoDg+kDtD+eC0+HnLzTeP0mCI8S/cKNa67OFQGnJarrFBPPnd5r+PvQCCZ/Ye+/PIuLkbQTOStZqvm9q/zucOBw9k9T/PRI81QgD9i0PnNe8Jz3cr0ZE7YksFGYTuAXtSaxS0ypESuRMP+9H5vBTxGolO89i3/DqV47gpn+xSh5iIulMGb+PHGtNJ/bCjFpkrm1ExM/OVMn51A772T5f67oDmR8TNZ4/Bss0ziTN+2QduzsRvHJj7xbIxQTmj/HqXYpIOBxu3kGsprkzESsguIRoJjLn8hCmXOnl9wSx2vIPIji3FZmPMwm060uBD7VdzpzvPmROzkDo6BxkUXWXlvMSspA6Q/u5CFn4DSFws7uOQBt+PrIJWOX6S8sbB3wSMe59Z9w+MXbam8uQVdQiYjU/RyM7Jee4v4DAW059PC+PjX4ZxGrUViOT2JlXuWcXQkA6EDjd+ABhaqUeAjq3nk/FeZzyhLuEJF3zydD/taG8Znr/ywkuU5inCFhEwHx3atuOITDPqNUJ4hhmHsFNYFU0vHTBv3Bjsdc38Rz0+6Y+1xLYwy9DCMcziGvNHGQSbdL3waEx9cdgrZd/Px0TZ/aXF4rvJupJNHS5moHgglOGWq197cdbqPHW+HXQ3yXEXj7xDLK7d7jk8HCZF+YuR/AZt9Pa3UGgtZvrhd9FcBlErt8vXlt8DfuOOqY+XiTCkXgXbjitfl8JsRKZP78lmD/bCBiuu0CikiTawV5+i70+993POle312qetQRKUO7JRRhpHbGWB/6tYs7W/zNkMfiQ960KFT1749KYVrPTmneX5dxJoJVcSzBX/PmzQdO6i1W2o/o4yHnuI5pmLiIdCV+Y8S5iO7wMwe0t6Bk+gca+05BejMydNeE+jjNvnP9wH2c2evFSdIyd+aPzO9/Zq3ehPu/iaZp75TkTsRXIHMgm0FJ3dc728qtF8OlJAo353druP3j55hFrweLM+aoRyYijxzuIXdDdrmO1kMAf+qXIvF4d6o8Yf/E0VHxNentjq/C1/V1AWz86cDEazMhOLEcR2Wl+rteB/aOmm4Cs9qsUSV28tchK7A1k4l1EsINfTqy5yGgaKsy4ctujDu2RXUSMGYGm3xpK6+wry4m9dekNYoleDiGTBFQbk1hiuw1Zea4hYL5LCZivM8VYgxAmn5lkI2KoTQSmTHMQxuSu67tI8zuf4DawIZpnlvaXb+qzmGAx4hjt7xEG7i4cyfXK+XKonNMQQnyDq6PrD/3thyw+biWW+d6PEO8yAg1rZ7v5EwKfzCuRxYy/ey5Gdq6lBNr68S6fuEbruoIAlx5GcHKaF5atbfC1xfsgu/3FBFq7ud73CzXcierC2vrrEAZ4PAF+5iB4t7gRHGlw4YaGH659NFPHKnzJyASEOG5G/QQg+FSK4KyPS87+3y/3dcTkaxuBdv1JCINbiEgKdmh+NxLffeUmYi0PGtxOpe/DCY4pJmgZC3TM3LjsQCRHf/TyWBSnv5YgO9o7CLSS482fhX5aRFFvE4Lb4fzOAZ5y6by0vjXIGISGFRLrZ/tjhDnladgsZAf/sOY9GZEg7kEXL8BFIdq5joB2LkQvHtE46fr9WWJvZ0vVek8nwNl4JmJOS30NgZb6akTq9A8vv67IJmIdgUvYXERq8iditeunAZ/TOM6cbwGCPw7/613nemNwNUIHNnjlHq31vphYmrER9Rfv+sunv/udr+3vAtr6QUTY8TSYd+i70/zcDnw+TvoRiNjZxXsBIazuYof7kdWcc9YwE2EQp+hk+iyU310E19Ddo3n9iZAZgaa/LpTW2Y1+C2FSc3VynI64ZXXxrsMTJ2rYMxr3Ii8sm+DSEsd8n0RW0psITDFuRIjRylA7pmmfOFOmscjuocTrG+edaCeBg36L7IYqaGjq44tB+2mf/hAhpu7ikLFatj8Ge3WMJ3vpZyO29Pd5Yddo34cZzecQsZzTsH6IhkpQ5yDEcQmB2dg8rdOPCKwMZhHHfznxtY2/EQp7AsGxldpnOwmYfQ8SaO1q+PNeP/i4XqVjPZMAPy/VMf2sERyJd+GGr/3stOZj+lPTvql9cpoX9hsEx3xztSFe3VcjRHw7wmju0j69RPPb7uFLpvbXDGQ+/ytUvrtjuUEdUVt/7/9CL14usjDxx2UB4lbYT+OOm3zFNneM5ltl3IjMUd8qY5FfR31/Tn8He2EvI7tq/8KMBiZ6Gtdp7Pt+tt21os96YesJLh15Q+P/Pxpqn5+pfVHgjX2lG/s49Y6rhEiAsxWETMT0+7kIbXNa6ltQLfU4eR1PcFHOei/c16535ny+Ke1ChL44U9q7gbP0fbyXz2pCFiDIjn8tsX4ZLkDwf00o7nDg1tbgXcmeNmesbfEQR3sTdcHXyuXE1ail5ZdINLjpzPvm21o2qqGu8RzzvZ1Yl7A/RAjhNwmcP2TS0ElJjCmThsVcuuD1g1MKSeagfx6qqOKFdUEIcyWhi0Oa0L6xwOFxwtMJXfjQjDybZDZ2sDzxcD3UlmZrfDd1/pDgIgf91j9BeBZJtIrxjr5C4V2Bqxqpt+8zoYRAOTKFVtwl0bQLfk5vYl7dECbjm+h1ImSidwDxaWJr4zsipWqyVQwJLu4hpF1PrDnfxMboq6Zp9KKeg+Fp8wq0SaPlLPd6hBE65ad3EMUoX5vwYgJnJL2Q86VsZHfgHE+cjGhKTgmVcSdN0y41xNcMf9QRMC377+GyE7TtTkTJrEEchAmG/Zqfh6zkkzLfOHn9PU5Y2IzmZGSlPSVZXhq3ByFGi5wdG5TRan/+AHXXGko/U8f03Thj2p9AAesnBNrdzt94MbJoGO3l5zRlP2yk3g1MXJDVeHtiNYYT4dJ/kMXP4BA+POLhQyEiOh7RSF0yEB/dZ2rbpyr+3aB9F7Zk+Dmy63dHMH+m4RWXf0fEx86f/ygdU+cy1/mAf11xL+FCAGE4E4j1Kd5gTJHjiEsRxaZfE6st/kPUCiIZbhJfYW0TorsxBvVvoPF7Eqtp7jTpFxLrS/8VRBnNaUq/SRwpXZJ6NbDOoCHdGKnj1ykUHh6Xrsju3tXlcmTRE6Zr05Cd8m2Kk1fpWN1NrD+J8chO17fUcP77v+qN/S2E5p/27S8Q6Z1BNgIxliOh+O948+8SRCqRtM0EypWNmrFpvF/ECUtIjwno+Nlx0mUh1gVJ54oX/7FE9Wqt57/+djBjzOvhIEQcmI9M5Cs0/HAE0dztQlXIzvUGa+3TxpjnEdH01xHR7FcRsdqNiAhoECICWqBlfJPgYo8S/bYaIXI/tNa+aIwZoHn2Rs7qPtJyX0cQ7Glr7fe8sl9EVoRftdZOMcb8BZnAe5AdqUGUoTIR8fciRET2IoK09yFMIB25qGG+9tFCa+04fR+JiO7rkAXAz7WtpZpfqZZzFsJ4QCaA0bK+omFZ2jdjtG6zEbHgcr1J569axjWI+HQYwngus9bO0bosAX5vrX3WGPMjhPm9jRChckSE68Z0FMKAdyFiSbTNf9D++FTDTtF2fEfL/SsiNjxe63uNxnsDOVudqmP6rNfXPtyOHCeATGYQ3NqLEMovoz7IrbWjtF1uPIchZ/XtkeOE+5BdQm/t3zcRxbDTEJH5YYjo81lkAdc3VJffINKNTIQQT0MI1E8IfDJPQ4gkyPnlHETygpY/EDneyNF+PVv/p2j7JiLMZa3m1QMZ6+cRcWsW8HNr7b+MMY9Ya28wxjyCHDf9S+MXI6LQo5Ex7aZ9tkDrcx+Cv321D44E/mOtvUX7z8fXePP7DGTu7kXw3cEA5FjDWmuHafoeNIQ3CUTUmxDdlxoC72t/0Xi3a3mlCKN/1lq7KE5+aFkbrbWDEoXpTXM3art3Iefz+QhdGqvPk8jCKwXB0SVe276K4Pnt2k607j21P9xlQ68g4uneyDwAOcIaiMz5uxGR+tHIgmAQcnw0EWHkX0fm7gvIXPwnQguuRo5pshF9jIkIjt2iZTyKaI8/g+iZ/Bw5Oz8eOc7som3+tcY/HDk2MQgOVCP4/bHX5mKERi/0+vQa4JfW2kHGmP7IQm4yQofvRqRkJyGLjRuQRfuJ2i/fRKwOfqG3k72A4Gw7TetuSTsSoXXrELyoLx45Rx/A/oT9vTJo6wdZNT9D4OnsdGQSnkbs2dtrCOLlIoj2c33/G7KTCPu/XkygGbkJIaabCDQea7z3NNREAJloTlnqBWSCpRC4CXSa4asIFEBc2e7mocXICrAG0fYuQhj9VcgZ4AZty9kEmp97kEnZmUDx62K/Tfo+C/gigYLZV7QPZyKE1fWhRZjx28Q3o3F948yqnFvRJdpPn8czPdGyf4BMfGf6tpHA9nYtgT9gd241Etk5DdG+G0zs+aAjHr5LylXIJF1C4G/cafb7GtYlBBrWTrO1juCs/Q59LMJUd5FcY7iYQGPYjWc2ghuLCbSui9yYIMcVGQT+85d6dXHnzitpqBX+oX5zxxzLNK2zZOhAoCGfE2eubPbGuRphhGcjOOSsMTI1T+cD3pnMrCcwmfG1kmciu6Qcgotf3IUNi7z2zUZ23EsJTOWchvvLBD7KOyWZ31sR5at5wDFe+/Li0AenlR62mMhDmPRGD2+6QQOTwe4a12l370QWZX8nMF3K1aeaxi/w+CoyX4do/2xAmOx6AtPHVYhUZ06oLWvxcN3NAf11txj6WvhOyz1X2+zuGNjo4WeqjrEb+4+17BwCc8rlXn/kh+aUm0c+fpYTXLaSjdCJpV6bs3VMlxPM7ypE7O3P7z0E7pD3EKvtX+PR2G9pQBpcQgAAIABJREFUnhcj8zENKNXv3XXs3QUlOQRKrTMR2rUaWYB8Fgdvqom1Zshz/bhf+VpbM9b93sDgUon3CRykVCA7oRQv3hI816GKWI8i9sarEHHyxRrvi4impNOM7IzsEnYSaDw28PntEZplblIRSwh8c5VHkYmW6ZWdjRDR/yAE7mgt9yUvz1xC5ggIYV2Pp/mJKCitQ3aczqf3l/T9EtQsLtSHe7w+dLbKMRd90FBrtP4CFv2dgDDxzdoGXzO2GhHPOZvaQmRiPqXx3Zlke4SgzULF8wnGdA0N3cE6f+PrCfyNr0J2Dm968WK0fvV9iJa5lMDEpZqQW8hwWmQH9QlCeDd747nCjafGS0WY9YsIQXw3lJ+vAZ6qbXjJC8tBGH13ZJHh8G+ZluUsGRzTnUisJUMKIm0p8cbZV+hyY5ir9c8jMB1yDMJp7YZNZtxiZTZibbGQ4MKGhVq3HNTKgEDD3Z8fv0BwrITg5qcvIQzEn9/OJG6A9qXzkb+Zhg47nAKZf2+B06YuINCmXo3cMOgrTy6k4aUlZYiouoBg4V6mdSgm+QUeu4g19+yEzLl7EVrhGOpqLTfmvB+hWVuJnQOL0TlAcEHRIH+s9H0OMt98S41FBJYai0Lj68b7DB2TKQh9cpYjOQjT8/HLXbayieCyFXeRyDKvze8ii5tSgvldHYe2b0RE52tD4QtpeIHNEmTnvAihx2UEtKrcS7vCa6uj2Uu1Lb5fjzUIH8iOU68G7nNb+2lzxnqgHoJJ/BDCdHzXoWsQAjwDWe1fgIgB0xEThWpFEnfpQSmB2MlpRnZCGMBMhJAUEtIu1XjbNd6DWo93CXYPOaH65hNcBVmHrPJeUMT7mMCc4XhFxB8ixLyBAg9CMIfjnUFqu7YQ7JSfIrBzLCF0fovs7lwfbqThRR/xLhZYpH3jM50liEjpNGI1mE/Qvv2O/ndi9r8TOPd/CiEkUxHx373IDnhrnDHdq+37LiIqc6YvzsbY+RvfhIg/u3p1cZqyF8XpS2d+danmMTb0PZ7GsMMlN6bOTn86HuNHiP5dxGpdP4cw/09D5VyK520OWVzlInj3OMFlJE4K4ywZ3iDwD70TsWh4DyFac5EdnhvnSoJFisO3p5AdkbOF7aNp+6E+4DVeJYHlQAlCKN2FDbu8MXW4Xa5x+2n+X6ChdcRGBM/8m5+269jPQnbaYU9Yzke+RXaBM71nNbL79Ym3s0TZRqBNXaDj9Q7BpSXO/8HVXtp4F324y0jyvLB4F3h8gCwO/MXiHISG1BIw1KsQPCr06vIX/T6P2DlQrvV3vhJuRETuw4m91GWsjqFvqVGD7Hone2O/BBGp+6ZRt2ncOgLLEecH41tevNMRRv08wWUrzrzzh168ehe2BPO7BHFwdDnBXH4ZoYMPhfq7EKERjsamE2j7O9pdQDBXSgnouHMy8zkC87TrkEVfMcFccRdKHR+HPtwUDmvt57/+jDsMxpjzEWWXn+r/LP00ACFyhyPIdY21drUxphdyDv43RDN6R4J8OyAEbD1ybjIJEU0PQ1aExRrvqlDS1621u4wxfRFzE1evjoij/EJjTFcEmc9EJsnDyBnLCGRlegZCRHO13F9Za1eH6jcWKLPWrvXCFiD250dba/+pYdcjZ1YrrLUDvbgjgO9aa/8vTh8ehuz8x1s9O/TSTUXEm32stXkadgEw3Vq7NxR3OMKMKhACdRvCtG5EdkBpyASa5vrTa9ska+1f9H8WgLV2hzHmXITR9tfo+drnb7MPoOPzS2CitfbU0LfTrbUfJknrxnOv1rM8Tpz+1tr8UHkdrbWF4bihdIdpnluMMd2Qs/KNyK7GWmvnaj9frOEfIWfnIGLObV5e5wOnWmtvi1NOT4TYZev/u5G7kqd7cQYT3Bx1OuJIpdoY0xux3y0iwZhq+m6IO9k5Xlj9+bYXloXsFC9D7b0dbnpxnJThPGvtmjjt2eTje4L2WmRn6XDJ3ai1y4vXA6gI43ac/E5B7IU3emEDEAY4wFr7mYaNRc5WuyCmg99BGPdWRIJWpsnzkT7c5fUJieiVxjE2CQMwxrSz1laGwqYitGaLG3sNH4IoDV5njElDFiD51tqtofRdkUW3m897EGW1jwmBMeYka+0nbn4jTLbRuZyExo5EztZvCeOal7aDlnERsTTnVWTh0MeV7c+VAw3/c4zbgTGmEzI4vZCV3WqE8NSF4nVFlNl8ZFmG3A9drAg7HhHt5TSx7JHW2pWhsPHISrYWOadaGSfdnYi465uEkMpaO60pZYfya0A8/Po44qH/UwCstXXGmAxkt7DeWruzueU2sW79EbFtzGLAGNPTWluUYFy2I2LG+caYUfp9hbX2nVDenfSb6+8tyLFDPqIT8FOEUGxBduM9CXDkX9baPV5eWfGIoxKvM6y172t5I5GVfbG1dpsuCE9BpBHzrLWrVGlvErLzec9aWx3Ks6e1tkjfP7DWfi70/WQCyYdj+vnITr3RiW6MuTMOw7vBWvtIKOx2xBFJhTHGIPoU45Dd2ePW2prGykpQfh+88bTWFsSJMwv4tbX2fS/MIO32caFBm40xlyLi3MnW2qdC3y6y1r5qjBmK2AQvd3PQC1uG7Lr8co5EfCjEjJ+19q1Q/mmuXzx8yG3t+WOMmYAs0Pw5UIs4wfHDVlpr347XXs3H4dI24O3GaJ1uPPBw+3fIXPmgFdrUCaF3uXEWd+FyT0Hs25c1Id8YfDfG9Eg0HnHKOQPV1bDWTtcFzWRk7j4WnrutDi3Zph/qD7Iy/xQhpM7V52fa6b4yy9f1+58RbfCfISI3J2K+DhEfVyKivz8T51KROOX77ihPQ3aYvm/wTxCG/CSxvnmL3X9N6y45ONMvl+AijU0EF2lco98+RaQLMzS/2XhXHSKKS7ciDkXaI0T5U2Rlv43YCzc2A1/00o7Rcktdud4330NaX+2rDcgZ0y8RgvoCnn038S9NWKft3hIaF6fok4cQjQ+0L2cj563DEVFqqT4veWPvxI7PE/hTv1+/r9A8HtbfVcjucTwi4Vij7TjNq/fVyK6kmuCCjBXIbmo7smuah5wDOheZv9b8nyTwx+58JTvTnnICO+RKjeMUGL+p9d2B4NGnCG68iygtnR3CQYdXRd57ufbRLAIzo1JiLzP5gbbjNv3vfEF/Tev+pFeGM6m71QvrhOiNLEPOQ52jFdfX0wkuvpiL+uFOMn/cBTHvEFwQE7fNCdK/6r07v/kbdJyv9sJe0/7ZgoiupyN4WKLj6Mbv5/rtnjj4UEbshSmFyJGcM096Ajlaqp+3CebPJ4gkqt73gobfoXX6jGAOzEB2tZs1bLvW0bkTzkOOO8pRkT+BH/H3EVwsJKB16zWvH3v1uV7zWU+A21WKJ6sJfJqnIFYbbyKi9IU6bsuJpVWPeLTKuaadqW17luACHFfuLq/cJ3Tsr/Xq9zVtzwwCXJ9DQE+f0XrmaVmPIpJIdynSUo270SvH3WGwGKEhryBHN0/D/2fvzOP0Koq9/+2EIEHWAMqahEVFvIKETUAFRBT1veKCsogG9aJeFLzghqCiXuGKryDuiEgIclHZhLCvQYEYCJlJZjJJJiH7Shay70u/f/yqpus5c2YSkMh9rz6fz/nMM+fpc7q7uqq6u/pXVQze4nPYKz2JbvEOds5ScyESvouMETzU5xJj0KWB0dqpBFFACmcPG7hlodyFSDA92cAtNAbF92stMrkts2sDJebxMuBPVs88a+cnKSCX+f7dyrRbuadCvW+lJNLYiYL8dCR7MwVp2QNDWob+LUPmxl8ao//cmPoXSLksRbuMPmiibqb4yXroylmh3g+g3dh4CiBoGDL/LTWh+DrFFWUU5rtLY9KElZSgNVMIwBq714oWARMpCNg2ChDrXutrC0K0PxXGfhQlzOus8D5H1G6LJvRWhC9opiBOh1AWQY4YXmrvXWnf97dn+1ublqPFSxtSVH7muy1agByCJgOPlfwEnVG21ZjtI2yc+qOz/wik+TxSth8O1wIEclxK4a+NSCndQSNqfgyaBPzehvB9JBWQZ/g+Bbnjracki3gQTWR7U7w3xtr4XB6eHWL99rC+ft1tdP06kqcXEJq9mst7HJp0WipXKwa4Q5PCTGyCpyDam2lM/rIv4oN3V/rXhuStJYzfALRTfY7C7xMp/vjOD/+FJqHplGQkE+25gRT5GU/nRdtGa/cEtMgcRkFoN1s7XAZanR/snoPLeiN95WffLeE39whpo4Qmdl03C01S6wkJdKzOXSi87XphEsWzZaY9exI6WvuePduMNgt1umqo0fA6tMCZTkmA02r1jvZ6nQcpoDRPqrMQLcgeMPpOpejTUZS4BK5Lf0VZxE9CnkX3hf61INn1RCnuwZGo4DL+OXG/tIl7NZoILg3X8/Z3McUdxYPnTw2MtgIpve3D+1owJCkSxB6E2NSUZAMb7B13UxTjQLSLWo0FD7D3TbHvPcO7tjdmu5mCVN+IhK+rSf9raBW7hkYleILV+Vb73Zl6GY3JEpZRFhVL0Q47GW2StdWFyt0h3HVmSvi+NtSb0Q4guoVEV6u4+7kOKcD/QMIZw7iuDd8nVIXD2ujj4uAwT9gxiuL65THWW8LYuxC2U1CxrWiBNtZ+c4vMVjbOjjj1MLSTKYjhiVgYWixBRhjXqCDHhPY52ns0IW49MuG3I0W/jIKynWxlO1D8Vq9HqIto7HU2noPC9TukJNdR+GsaIWlJN/dW0jkWdIu9zycYn2zcOuBubOts7D8bJomJSI5iSF2nq7um+fVre8dFaCc1F+2KRtG4C3weKfl+4RplYzubsqucTclO9UxlrJrDvYk1dPXxmxTGz92gVlDP784PrYEfPBmJj6e/9wQ0UTxgtPVF21qC66PRoc2uqhdHdF9tphFUtiJ8H21tiR4hLYEOruv8fWMp4MB1iKc6FjY17ajzbBlu9b6K4p1Q1VUjK21x18hrjeaeACcuqJpDvZ5UZ3u00FuMMB1NFO+DOKZOp0RZxMdELTHW/9ZGs2UUD45tqCQd2SLz2pau4JW+0Gr0sMo9D/Xp+ZsvtoHsQ3FL6IVWhcuQwDl6s93uNRkT/o4y2d8S6ngM+UBfWtOmWfb7+ci8uBT5b/6REv94W7TajrF5lyK0pU/6zdT7po4nTNx2b6H1dxUFaflTe190yYruP9eHenqYkHnCjYmY20coPxpNnhEVO9HoszCWs78zgO+H+y0UAd3K2tmElOoqtGPbCwntKrQq9nFxlOjZFATsZQhoN4bi+vUrNJmMD2N/BlJM6ymo2PFIIT1h3z9FyTc+moI4HY6AizEhwhA00fo4X2nv+C7iO4+6dwWyjqykoL1nopV+jFu/N1Iayygo25lG14jiv9zG6lv225loZ7qSEK+9whdzqcR+phE1P7nmnse5jrGg11ofz6BMlGOwibIij19Git69N36KdtyzKYjhZqNtFTE8AXgi/P8NK3ux9cX7vDDS0PnY/t5M2VW6D/AGCqK97t5P0SQ1LbTxLrTjfz6M3/M2ptfU8MOywA8TkaXgQUoyEpefmIzkYKPLOsqibS2wTaVv70IT3hz732XgabRDbEIy7H1bhjYCjqaeSll4u0fIDWhXvYSi66bQWdeNQlbKxyi83YwmsTihjsQ8W9Au+i+hz9FtbJW1xTPB7Yx4qyE0rdFlmNFy73C/3a7D6GyZc8+fVUgu7saSAwUdNNbGxBfxIxEobWzo3wUUX/jzKR4crdTo/Jd9XtvSFbzSFzLr7lZz/31I+Z4UGK0uzvbOyFz9ZbvOROc9p6PJ5ViKqefV4bk+dB/+sYcN+JNoQv05XcQGJ8TmNWb0Sf8qKgHxrfyZVOIYo93+BWhSGEjxiX43EtrzKekLq6EHj0Am6+g+8gV0XndWtV4a3aBORbvP34R730NnndWsOpOA28L/+yAFO5eSM3wMUvJH2Rj4uJxFfXjFL5owuuvXWLRA+iaNYV63ogivx1M/ztp/YCh3vD3vCRHup5IQAZkov4EWHNvZOx5Bi4Y9Ku37V0oyjP3RjvKrVOIqI+V2iX3vMmY7iiD3LbSY+BllZ9q3i/KHR/4K97ejksyESoITGmNBDwHeXnm3u9TF5BoHI7P5IsT7Hob1dPv/bkrii/fVtHc8nWPmH4QmwUWhzwfVPNtgoaj8VvWJ3gl5KsR7p1KSjngbL6Qx78Bg5CIZjw+cH24M/DAS8eOfKb7kZ6IjrmqylL5ooeOLto5gPpVyRwIPV+69Cpn931y533Cvi/5uhXTFefb9GLQYreq6vpilJ9x7PVpkvyvce6f1dSKa9I4Kff5hKNcPHY/93r5vjXTfx2gMTdsXnXOvq9T9FFpMDLXLFydumUqUxE7H2eUuuZ9HOvB5yiL+Cev3Zyv1DABOC/Q7FdvYbOnrHxZV7p+U0s5oFbp7rrhQbYG6OiGQU0p7IADOfeHegBxC+IX7fXLOLxjC+4voPHn/nPOe1bI1z74md+FKtLnv25T7yN/6SSndhCaPByr3/w2luezVzbMfwCI85ZeI9g/vchTrWv4G74FN1LEDcj2cnBvdiT6Qcx5SKXtwzrmlm3fthnblG+x9yzezDS8J6RzR7VvqU+XXQK990SQ9EVlsQAr8ADRhP+btr0Gb/xztShM6wjk25zzH+v5kzvkt3bSn07iE3zaJhu/iuT5U3EU345kG18ea3zeJsK/zFOiqfZvihRfzsf4uQjkYtij/dFF/T7SQeRWwIQfvkJpyKee8vivXtpdT37yUz//6idtg/Jcis9C30erxNLSj7YN2Ee46cz1wWe7shrOdK0MT8q/ZtQZT7mj1/BekVH6MXM2GodX3rsjktBGZqD+HVt77IJPUNEqAiIRW1d+0dq+ki3jeNukPREq7w5UMnUlOiV1AK/xD0Zg3CGNK6ds55+/Z+45Aq8fZubg5XI1Mbl/JObfbMx9ALkurw3sORzuyWWiHcT1aObcjlGY7Uq4DkKnKAS/YM3fFSTultJ/RYXag69FoRTwYmbj8M9hotQ5ZUr6CVt7HWNtHG336Wz82mt/sYARSGonM7K9BplQPoToHmbj9fW8FfptzvsrauM7e8Xs0aWRbCA1EK3Yflz7IT39ISuk9yKy2CI3/YIRyTQgtfCsyB//K6nA8wR9QPOyxdv8gZMLtjyav0WgCA1lP1iIrxrWI7z5E8dkG8dNsxKO/QLuhQynAprXIUrGrjd15lLC766yP49FOcgDCAHwqyzVqa6P9eygApYuRlWakjdFqxA9H2fuvQjyBteUQo9ERRq8JaPL+qv2+l7XlVCu7xGi4A7Ks9Lc2uXzvbfQ5N+f8kNHw00bX11qfBqMxnoF273PsnYOs/8uMzoOQQk+IDydbHX2RbhmE5PdidL6/s13uD74E6YQf5BLj4YvISrEgKW7C9chC8Zy10V1V56MFzCpr4+kIcLgaWeQmhD6/zeq8ze4nJJuXAwQ+/ibaPb7Z+OpOxDPJ7j9N+KSU7s85v9dpmHO+PqV0ktF7MOW442y0W/f39QAuyDnfYc/egaWK9TpSfb6ED1r7B+acx5kbWws6/78Gk71KG6OL7SJk0TwF6d75SM9NsHvXogXPBMqRnC9+9rK+uG9+QscIdfqmQT9ssc/fY1v/Sl5oYM9DCsIRzE+h88m7EMP/GE3g36cxo5MjcOeH756zeSEFFfsMUrxDkSn3y0ihfYYSqcmzK30JAVeuQwot2/uX23v8/GUpmnCq8byPtXdfQIni8wkKMvUce+fzFNDYFEpM3TrTuodS3BctPu5DpkB3c5hn/fI2XmBtXGBl3ocAVc8gxXwGJa5yG0KR/hUJx9VIYXnEqrfZdbrV+5PQrqeR6fjKQNd90NnXAkpo1EFIOG9EZ9q+IPgYMo29QHH9esH44M0UdH0TJY7xUDQJtSFTcHN4n6N6V9OI8J1Fo0fBPUiY30ZBz05BZrfz0IKuv43Jg5RodYPsfVVatyK/+cso8d4vsra5qflINJmdjSa20Yg3X4cmlZFIqext13NW3z0UpPNdSFGOoxHxfSdSxgspoKE32l+n4YeQCXcNxWVwgb37PgpCdwoCi95F4YeNSLGuoPBrppy3DgP6Wz/3o3OoztMIqSYRL86iPoLgvjRiOiJYy/uyDvHNbKiNw+8eCqOQe9BT4R33IT5bEPr8tI39A6HcBkrktYPsXjzb9jo+aX2ZQ3F9nGS0foTi+fF2G587Kv1dRsljfilaACy3v3+gMdTx/FD3e5EcfALx0oBwHUZjiFgHb02nXqb8fR+jgH7b0IJsFtJdEaX+BDpCOoOSL+FOu/coxUVvCdJzE2n0qjnOxi+62C628drH+jsXLQb+ZPQ41frwAyTf0dV0g7X5z3Sjb+z5V/Mypojtcl57pSfWv8PEHRGDPkFV4+2OpLiKPR++b0BnrGuoCQlqz46gnI+PD3U4ArkZQyDb/YjM3tWY6c9IAQyz+1Mq7XbEpfufu8AvMsZpQat/T2TyTWOmeIbliPR4rbNy64MwvIB2P582WvREQuhI7IgOfsKY1xNpLKAk0pheaXsHohVLhEAIg2r/30lB754S6N5OI7jtCGt3jJPuSPaeFARsCwLCjKG4fjVRXL98/COKuA7F6u8bQvH57EcF4UvxKHDf7MvtHcORotrV+OJJe98RRrsI3orgwK6Q2Eei3elajGfs/srIMxQk/QQCYrvC+xMoSOfRlb6PoICaxlPiP0eU7ahAO3dxW4qwJaOMLs9SELrjwrP+ni+jBXZEla/FcivTGN53PVK0n0E7pomxX+H5idXfbNyfNnq6z7C34ZnQFx+XCLKMXg1O14mRXhW6Phf63B5/C/T6FzTZ+mJsPmWB4nV4cpOGOqztEzDPj9DnqrdFXzQxuruay/ygyrWQotMcxFeXKGSBXRsoLnqL0UJ/BfUyFZHtHgbZEx05+HE09Sj15yptaqK46DVR3PZc9tyr5morvy+anEejDcRDNbKyLnzvSO5U0Td/psbLhaBvwm9bfOLuwf/+T+zjjfZ3fkrpLGDrlNJ5CJx1ORKGnsh1YHs0GXkc40/lnD+FmO23wGIzF7+AJsUDkIlsWzPR/BIx+g7AAymln6SUjkMmuWZrxwq0s3g/OlN9U0qpr92L7f6G/f0mAkfNxRLaox3cWWgH3xMg5/x9tFv4dkrpqpTS9tbG1+Wcd/ALMdj2aDX/dQQemW11XIgEfUer+1UIgPVEzvlctAu8DJ0VnYhMlcuAX6WUFgA5pfRBYExK6QdI0EcbbVanlD6CBDR+3ohWu1h7JiA07heAHe1ZKJm4tk4pDbVoUWtSSjcjH+RH0Q5xJ7TjGWu0fg3abf4bBlpMKfUCDkwptVj9rzfcQ5O974DwPk+luTOKTz5V5M7T7Jqec/6h1fc5a9MANAk5onxHZPG5FYGqZgDjQz86PoHWYxAC/Wi7/0xWist7gHEppWNTSlcCy1JKb7M+bY94E/u7vZnw/TM9pXQn4s/x9nyPlNJvgTmBtxcjK04fYFFK6QKgb0rpIaOn05CsEJAZLdraKWDHVwHb2TngGDMJb43xQ875SsRLrwn8uggYaqbsp4Bbk0JZLkOBQd6JFq+9U0oPpZTekVLa066j0ES0a0rp6ymlM+3I5y4EULrceOtJoF9K6adIwe+WUuqVle72JGCrMC4rUko32PHNn1JK/wE8mZR6dl1K6ZiU0jHAzimlB+3d3udpKaXvIP3gn55I7ptzzgdQ0gC3JYUi9jp6IQBXNbrhRrSYvi/bbIGsAa+r9PkMZE25m5I3YbHrs6DXelp/7wb2Tgr9OQ7x8bSc8wk55xOs3ECj75V2ZcTjKfDDfkkpV/cP7+uZdU7cK+f8DHL92j0pnemGnPPvcs7vs7F5GlmV3OTsfdwaAeGmoAXLAhTXf3rO+YdZ4XCnGv9AcQmcj3RvP9P5q1JK704pfRQUOc/Kb4t0VcfH+OEUJB9d6puU0sdNfsaypT9bemXwSl8Ygrlyry9a2S1BO6g90CruncBHQrm3W9m48nZU7DIknK9HwRWeozEpwXOIeZ6gEYH8ADJvX2K/XWzv9WAFQxGTfYAKKt3esT9aWfamRHl6GAmOJzLZDUOmUhIsLKeCeKSsiq+g+Kt6ooro5jCJipsD9WbIQ9DkNJSSqGCx0WEmZbczEyn0STQmuFiBue4ZjT3ZwzgkzE7XecApVm4vZGKbjJSUo/2PQZaUdmS2dtevgch1ZaZ93xkJ9uHI5NgPUw7I5HdleN/Pjfa7EZIf1NChE3rW7h9pNHBk8q+A91T6sbzmfWd2wds7oUA296CJ760UxPZoihl9ANqJePKJCZSIZVegM7+PYLsKJBfO2/ugRcuTaNFygdFuFFKsTsNmJEeXU1wGz6Ak53CE7lAb53mBHyZb3YdQ+HUuMvNfUaFXzMTV2+poRvy6GPHpAzbGh1gbf0Y5rz4oPH+C1fM9pOwHUrwtdre+7Enhr7MpRwDuofAHNGE60tzNsxGVPNTKz0GLoRfQAvUKzP83tOlse6/XMcve5xiBi5E8TCYkN7Fn90c8H/vcgbBHZtybCdnywrPHIX4/zi5Hvx8DfCGU84QpMTnQQLvaAz8ch8zeN9n37ZGOPbLyvqeQjomWps/RWWd7rIm1FBe9qzBf6krZ641eHS62SI/fjnbjNyHd8qCNz/kUXTXTruhqeg2WTKbCD1V94/rh1VX6vtzX/3pw2uZ+UkpvQObYTmjHlNJr82YiRcMzuwKLcs4ban57H9ptjc4Wc9l2Q70QU26faxCPKaUrkEn8L8iF4n7EVG8BfpFzfmMXbemN0OLV+MJ+dpPQrqhfFsq2Hwr8f1AKiSqyVsn+7PG5m0QaNW3YAe1qtkJI7ecNOBjRr35WXG3P1sh95+Du6NpFvV3SOlcSKLzYT+oG4ZtSSmwB9GwSMpf8EtG+aTOST7zE93raw9WV+/shfMaNKSB0sahdBH4Iz9Tyq/3WnHM+tOb+jmhJeKPCAAAgAElEQVQyGdxNG0ejpClLwr2DkULvk3Pe5UV1uut6NgeVfGbO+ebNfN/OCOQXZaUjoUil7CY9P1IXXitb+pNqEh3Z/V4IcPvfL+GddYloeiELxkFoAXt9znmD8dVrcs7TNvHOzab3K/X5Xz9xmxnmjpzzzHCvwZ0lyWx+JDJJ/sYZ3yaw05CZJqI356FdwJ9zcL1JKZ2cc34glcD9+yDT821oF3YKMrVfky2ZiZnSdsHcgkJbdkUo5CrCdC7aYT1YM+n3Qrukk9CO291l6uhSG7jfBAEqwlDzfKckFzVlPFFBK9qhdbgsoRU9uTE5wPhsiOnwjh0QIKm3t8dMrS05578E2rwZ7ST/LYesRVY+ImA/hMbtBav3SgS2AU0iu1PQ1FfknG8wmlyJzrrakYVjO3tmFto17oxCx04N9X4653y9fb8x5/zJSrschd8HpbC83uqYiM6zm62c5/I+Ee0KHDn9GDo/Pp5Gr4Jrcs6PB/pvZ31ZE+ruiY4M9kagqafsvmdQOj/nvDyldBWa2LbPhvi3yegzCNwTldtdCFG7zsptjc4PXZ5OQLv/+ShjU60bjbXbgXRvqNSxAjgj1NFVWx5AlpEP2Xt8R/6HnPO3Ah12RebRb+WczzH5ey+yAPwG8cTXKfrh+9kyf9li4RvIlL0d0hPz0C7uZ7lkF3w7JUxtd7pgV2vnbjnnSYRPqrgEmlw0lLN7V6FF7305598nHdWAdt4/QLvlCxG/7Yx2kYfa9yuAQbl40ByFMAlLbdJzj5CxCL+xxOo8AlnvFtlzZyHLYz+0OHtNoM1dBCS9lT+Qxqxfq9AR1TgavUnGAV+tyNh7sNwLXcleuHcCjZ4eE4Drcs7PRV2VQwIbe+4OZBK/M9DGffP3Rpucm0P5X2YdcW25z5bayv9PuZDZbzYylXoM8ogk9Vi25yJw1C+RIt0FKYmfI7OLozevRqau6ci8dgqWqACZIx3kNQ6ZdpqRaeZWBL6YCvzayr8HCeojyOT9e2vLQGv3j63cvcCH7PvxFBDaL0M/YjD+jegMKva5q7IzCIEuKDmiP4PFaac+3vO68L8nLVmPJS2hhJT8OVKYC6yv0dQ4jcbkAO00Jgf4mI3dKAyFavdjaEdH3w4IdTr69TsYAja0cUNo4x8p8bOvoyTX+JbVMRiZS69DHgcXWNunUBCnTUjRPIjMaefRCNoZgkyoy/1+6J+j8BdQUPgtaGGzgkbk+jQaAUo9EWp5JgW9Pgst2h5BJtFRlNjiK2j0ALjOynh42auQybDd2j0V8fJ8tDhYg8zyhyI+/RWNKHWPSvdHZML/rdHlVnS2+FWj+4N2fyElccV8o/eFYQxbbdx+Eep4q9cR6FDXlrfaGD1NY0z01/mYhufrdMFUa/eP0YLtBmTu/TFwYyj/IJrUZ4Z7X0X6YRWFt10XjKLogh8inphFSaAz18bqOQK/17TT5WIVjXJxOwUtPcT+32h0d4DZCntuKDLnX2A0cvP+CxR091hKCF33AHgQTfB3IP01HR17TUNxIJyGrYh/fx3a/R9Gr4co8rjK2vQjhNU5y8ZuBrIoRm+SzyC3L3/ffyGZdbCuBzLaDvHOGEoim1lIH56FFk9zEK81I6uly8oItEvvSOBCQb6vDbS5Ay0qIq1fVR2rLTavvdIT699h4nbE97spMciXoslxe0os242UEHZT6OyS4nG7W40xWtAq+llMcK0uRzy2UhCPC4GtrUwrBbU7jBJidVfkF/hq+7+dEs/YEaae4csny6WUDF/DgQFhYnu20ucloc9D0cT2aSw1HY0T2zhjxoVohfwsUpAHUo+mdheQZooLiIeUHI5Mha1oRTvYvn/B6ojJARZZnScarUdRoh45CvVDRpvmCm0cAbuc+hjR3sb20EZHkFe9DKpo6lFhTHaiER3s4zzBfrsPKcCb0M75OLTY2ogU1AoKqt/P7dZTUPiOXI8JRdynvF+Ft1toPPNdYX9fZX12F5XRiCfOoXgALKR4AHjs5yVo0dpMZ94eS1nQrEVKLmaV6/AYoCx02tHEcKe9q7c9v539dTe7ZsyNhsI3E6gkS7H374gml/H21/n1B4SEQNbnCeF/55NqTHTno2spuqAZKWy3FPWiLMaWhO/LMTR1hR+2tbH3hBStlIQUC9G57CiEKn+O4mY3Cu3Omyj8fgXFXctdt6agSWw+jXIxikZvlEvst6co6Ox2Sm6EkRU9OQpZchzdvZ6C7vbxdZ00iuLW2EzRdU7DdqdhDY+0U+RxAlqwPlppy9ZGQ5eL6Lbm332x4D7Z96HF1V32W1y0tVMW4lthWBIbl5UUWXkUTdRvoSRwaQk81Yk2gdZPoQ3fPyfuv7mDFSIaM81EprRFFKVd55JSF7fbJ1p/bjskzFcZMzvIqyPIP43+m22BEZ40wToU7QxXh3KXIcW0HyXO9hgUM/seY/xplAxfS2OfaVyh90Ir0t8bk4+MtKHRHzf6X/ZGq/s7kJKdR4mXHGnjE5uHlGyhJCoYXaFHU6h3HI0+ue1ope0ZehYQQrciQMpISrafSJt2tJq/p0ZRzAht/DUCI41Cu6kPIeE8D5lHPX72TCT085CySEjJ7Ejjznec3XPXoJ5osTQKKe632P31WIz58OxfkVJcYGP5Qbvv7nxO6+XIEnQUAsfsad/nAfdamQFWzkN6rqrwQ1Tou6PJ+680Ai8905z3pYG3Q7kWdFT0XKWO09AO02k9DE1Oo5BsOW9sg3jZ3eycb8ZR+MYzzcV2e9nplMXecLQguYji6tPD+MFl1ce0j10Tw/cJlIQwzquTjS+mUNzXFiEU+HMUANcItFubX6HN15HVo8r7HbqARpc6d7PrmBQDv2ej6UK6dkl1uZhLZ313ttF1Kdrp/zclIcqVFEveBHSEFJ+9C012j1l9hyP9daj13d0aXYdNCn1+CB25jOmCNt7H8WhRGsd5pI3JNCQbh6PF6+00xjxYXKGDy95iGn3ifRe9i9XXFy2g62Sluvg5Cy2C96dRp05AFpXHKrRuQyj8f07cf1MH69HPQ+36M42xbP/FGOMqtDNdSmd042PofCjG7fZkBJmCeLzfGKOKeDzHmObTaDU9zwRrDlJIMa7uFBpNy6vQinFHY7CVFHPqBgoitpmKL2EoO4YSuN93lWOCIDXX0c3qPIeCpt5AyRPuSUumUhDpnqjgDhRwYyJSFNcjweyNlGtMDtBMEfy+9r4xNPpEb48WFesqtJmBlOiO4X3zKAksvI29kAl9rdHbd8ILKWjqN6Ad5RVodX0p2gUOtDa1UxCn0+zdZ1fo9X17963ouGAJnVH9jsKfTCMKvw1ZHZzWM5GSeMDG2pHTV9OIXp9t75pm73FeGg2dfOZvQgDHfhXe/i6Nfq3NyI1yQ7jXH5nEHaU+0fihGS04faFzMCVl6Y1IsU80WrsV53cUK9hyCt/0R4p6fajD02Lu20Vb1lrZeUafUZSY6K+3Nk61+qfYtcqujZguQJPBzYi3BiFT//1olxd3hn4uvJKCFl9FwS14Qor7kTyPrtDaI8C1IMvEs3bvyQr9h9O4UB6GJpK46Nrexn1tHGf77WSj3wB0vLLC6nX+90V538pzO6JjgkkUD4DnrbzLx+006i+n4c6In1cF2qy3Pl5LkceTKSmSr7XrGYp8upfOahu3U0L77kELqBmVds9ALmJQFm2nGX28756UaBriO5eVhs2E3WuxNsagMz8kxGGv0npLz2v/COC01+fNjEGeSizbdyGl3D/nvHulzN6IAZ/PFeKllI7NBvKx/+sQj69GqRo/gpTJVkgx35lzfrDalmxAGLs3D7mfJKRE3mFtAa1w35xzXmugkr2yhRW0Z/tVujsbCc+dCBTyFqQEv5Rz/lFKaUzO+V+6oNMhSNEMDbeHZIHrdkfAposDDb6NJqnhyKS5MxKg1+Wch4f3jgH+I+f8SKhnJVpJn5Zz/q7d3ywUapLfb/w0tBEpnq3yi0BY1yBO5wGP5IAYDmX3yjnPSim9H8XFvnhz6wnv2JzY1N2i1w3AMyHL97W7uvYG1mf5Y/u97bJAag28HX53JPYXKz/9Muc8P6W0J5q070a8PhuZklegc8OjkFvNdOQZsSK8e1s0aS4FIeGT/McfAQZnQ6InxQo/G53ff7ir8UwpTQROzDlXfaJJKc3IOe8T/u8kf5vzSYrDMDtbDPhwfy+kC5y390ELyJ7IWnAGOj6agUKyjrNyb0dyerTze5CLHXPOz4Y6NikXxi/bZwHOdmQz+D9VPELQIuEcutFf9lwPlMXMwXxdyeMe6Lz6brs/Cx1tbAjv+j9oMzI13HO/+DdV6HAwshT0R4vgz2SF4X0dsipelruIDZ9S+hraMf+xcv9QlAjlpC4J9Xf8/K+fuKGDgciKT7012llPRabWDoRhznl8eKY3WtVORauoiER8WK/r9L5eNCJbV9uzVbeCTkyTFPihGiPdw/f58x68xSeJ2slyE7SIcde7ndji+0zIN6svm1Fvp4QnSW5O38wKLFJ9tiGJA1L2DXHSa55xlOiYbHGp7X6nhB2mzD6Kdh+30zXqtxZJn1J6B1rItaeUjkUI2PEI2dvAIzm4caWULu9qzFJKn8o5DzL0/xtRqNuqi8pd6Ihj51yDQkbK/RBk7vX45jtTk2AhFU+IsVEO7LfdoZMHQHvOuW1Tz9b0q5MrUjIvj1RJlmI/V2XvGWRuPQXJA2jx9DjwjQp9q0jsL6Dd94Cc86BKG36Ijg68nh3U5TwiKXb3yegY7b7KcweiMRleWXScnCvJcirPdTf2LzppSeoiIUhK6TFk8apFU3tb0KK6W5mqvLdDnu3/OhkYl3O+N7alTn7st80Z+4dcFu2ZbpPv1NRR18ZZSFY3sJkJerri9+7697J/XupW/f+XC6H+nkeTncdQHolMMW5Kuwed7T0O7BOeHYMUhccV/x0yr69Dpjl/39MIdTsD7QYeQTuL1chU6gjka5B57pOhjsuQmWgZ2jX3t/ueR9nTMp5l30cBF1mZA5EZ7l60yLgBmUifQav7SIcd0Kp2BZWAHjQiznsgM/69FLDJcMTgMX7vr40Goyno8vtRWryY4tLPEmdS0PpzkLl5PJqEHzb6ziCkFkRWgOHIfOV0HU+Jbd0QJz0858jkK2xcnV5n2bPPI2XmgSl+iXZ/Dgy7FYswhcylfhyRkclvMmXRezUyXT5j7xyGzhHXIBOc88gMG+O7KUcMi+37T6tjQTETullvOQUB7Mjph5Ap0lH3zwK72vNTKUCxcda+JUhBTUe89R202HRPiDspiG8PCfo5+20NBSU9jZI4xp/9b0r8+ITAOn9BO5/jKEh/R/g2U9DU05CszKJ4HsyzsoMpsufhfWMo31rPA/utFiSEAZ7s+3F0jmvtSOnRSGYeQ2f6f7F+OZBzpdHrYaP3KXV1+xgbfXzsl1p7n0FYgt9QgGrPUfi93ejzY4QNOBshnhfauEb5WWvPRu+P9RQvmNuQ7nvU6HsfhQ/XW186ZGoTejXS0GVgJkUG5lJM8N6WNd628OxB1s+Fmzn2B4dnN6AjgMdpDKxzFCVcbm90/DMZ8ddIa2OzvXulvedpxMc3EI7b7B3uNfRtGkNDr0Zy3WX/tti89kpPrFu8gyWG8r6UGMquNJ61+3+iuOEsCwOxkeLW4LGum5Ev5EgaYzKfQsjxiwTuXXQ+L+lAu6IJcAkyy9+KlMZEpJQnUH8+vzUFPPQXY8YYjD8hZT2BEnP9Qqv3Ueufuy9sixTzEoqwz6ScHXmCjBkmHDHP9u8REGQ6ZTL5CZoom0O97pq2gXKuuNHqcQCaJ1AZQGPChlGUqGPfrtB2DI0o6Rgn3ZHJjnBtpbipTLO/T1NiRM9FZrVeFNTvEKQs2mlEd38Li71t/fXz3G0p8aCbjR7tFB6ZgfhsCiXS1Hq778LfgpSnK4GhRpMJGPq/wgujgEn2/Uh7xsFGK5AJHRs7L/dhNAmMxpLqUDwhnkQTYSvKdtRmfdjW2uYo6WYKStqfvY8yOT2OJoSN1rf5FFzJRqP9sxQ09XDkFudo6sFW3xfQZLMrsu6Azs3HokWko7wHo91ZRFg7LauujBOM7j6ZzgKOsXe7LmhF1o1HKJnSmtAk0EIBcrYi2XuUgsL/LZ3RzwvQgt+9WQaiSWqwvctdntpsTCLg6RbKebu7pI5FZ+/30yg/f0aTXlfeH1tRIod9nhI9cD7FNTPK1DCr78LK9WXghdDGNiQDMygy4PIT4/rPoOIdYWP/BqRHNmfsY2x+j/e+hMbkOxPo7MY2BZ3L32VtfMbqdeDuYCt/DnBbdQ6xv9Mp/D4E6WwH19X2758T998wcYfvntwjJpDwJBq+25rYBdP3pjFg/pjwPp9Iq6jDHQnIW7s/OpanIEnd/eRNSFnOpDPAzHfmDijZQHEp2hjKrUa72kvD5f8vtjKXIIG93pjPJ9/nCL6yJlgT0EQ4rqZ/Eyv1/idSJl7vA0bTiHqPQJtxlT5GGsZ3xxV+E42I5t2xvMP215HJEc3rk3gTwU0FKYt5Ru9hNHoAfAhNVnVI+mpCkSsoaN1mxFdjA49sT4kBsKfdW4+sCv3CNQbx3mwK+t8R1pE2PZAieTrc80Xm+cYT2wSeiyjbkRRU83iKJ0QVBX2CjalnBBsdx8j66c/GZCOeXMPDqE7qYuxnVOrtSFBhfUloV9k7tOlq69vpyCIxiZBZjoKwXmrPRtr+l43JUooVaw4lfKvrAq+rLXyvS6zSVqHXdkg222hEgf/O7q0LYx/p4C5PE+P7KjR5juKS2mx/W+gsP5PQgr6DZ7GwqohnnzEa3kxJfjKZzmj03SnhiZdQ5Hm1XZl6t8ZFKFiSj/+K0Ja6REcdz3Y39pXyXT3ryXfWURI2+bi5HDpY0ucAl1MvV62j2r9o2avqh06ZF7fU9YpPrFu8g+bH7QNrf6+3awYWy9bun4ZMJz4Qi9HurCOuuL1vFySI/j5HLk9HMWuPQYEjVhgTxpi3a5HJ5TBjomcpri0upHsjAdyIVtWOtpxmjHS6lWuh+GSeG/o8jM4LhnFI2Uck6lwq7gtI6e2PJuYBSAkMtPa8EPryvD3/qUq9F1GJhWz9WUlB60elFWMeV4VmDRLCVSY0x9gYLQF+XqljKlJA0ynI5PH2TDudJ6Xo3nQ/UrrHVd65u42Po7vrELtXUHbg/xeZwmcjM/Y1BCQ5UhLPoZ3nV5AyeFvlfY7+X0xB//dHfOoIa0dOd1gZ7NnjbZynUALNXIomkZvRuel5yNridN5I8YQYjXY40ZQ5loIEd5S0P7shPNuCImSNs/Hpb2X72rO32vdVyMrzVQqa+j5r02iK58EVRsP5NMb0f47GRYgjrBNl4tvexmBthbYT0KLt5nDPU8POpcS1fpriOuS6Y56N5zwKIvoxtPCKLk8j0SZgQw2vzA1jvwaBu46guDz91H6fRtEjU5Fu+TnFJdV5eTRBfuzeGLRAdZ5dSMlnMJ2Sz+BEJMNfsTrqrHvDkJ7qF+5NR9iCqEeusDFaQ5GBS2z8rgttqXOJvANZsZ7vbuyt3jdUxt5luYoqvxVFZ4PixuZyusLaOMdo8gwlLKr3r6o7O8mK3d8a6fcO74+/27z296rolbpMMLap3OuFTKcPIdNIT7vfG5mZohvO+4y5Twrv641FyQnvHIhMTJ5s4BpkdjwdmZa+bN+foJgNh1qZQ5CiiKb2nayNb0Ur14/Y9yOQwjgfmbum1PT5JELEIrv3Q2S6f224Nxydsced7YlIkaymMUHGAUgheV/OM6GLiSsWonPSfWva9FpKAolFVBKoWJnZwPcq995rtFwV6Pr1zRz7oWjH57nS90DhKRto3c3zr0axjbExeqSLckdj/uZoErkaJTjoUSnXH+3yEjIF3lTzrn6VywP37IrMrrtQTOCHIGR+fH5He/f9yFz9dbRzdpPsTTS6HMakOmcaj0ScQV9kpv9NpZ69CO4wyGQ8Dy3uPoLMzA+jSe6z6GhqqPHIr5FVx5OWjEULw8eNH7e3d56KJrOTQj0tmGk70oASrjLK+McrbR5P5yA2rgsWYboAeZb0pnHCGmh0vYSSSGNvFGo3RmJ7u9Hs2JqxPTyMvZ9fj6MxMdFiZKVyPTIOIeXjez6ALHNPVu7vD3ytQpvPI2zJ4YQANfZ7Bx8Cx9e09w0YZiLc+77RujoBHw38LrTjK0i39QhtuY/OLpGeKOe57sbe6j2KoHcxrA4K51uVgRtodGObjDZdZ1mZtyB+HFmp9/9iga5q6FGtZydMVpzWm6OXXo7rHwJVXv3UIVtrynTrhvMS661FftpvHe4n3j5zLVmaG2M6j7Pri8h8un/Oec+X2J7+aCX6TqS4EmLGxxCTdkmj2Jf0IhJXpO4TSHwfIdufqfntipzz17t57wdyzkM2Vb+VrXX1ich+Q4Kvw1ytUomzPTbnfP/m1PO3fCoo/I+jc7fapCgvBYX8ItpR6wEQxr4DpZ42kVzD0Pvb5ZyXvYR27IAm6O2Qot8eLaxByOMlKOvUyG7ecSpyR5yIrG2gSfYA4Iu5GxR4eEcDmrrm967Q3VtlcxEzT4EDkWk1ouA7JdCpo3/4rTahSFIM/K68ZTxHwTJEQ3iZeaarT3dI+i7KvxR0/S6uh6pubNXnu9PHm1FPn6x8B13Seot+/l4rhFfqoqBZ/ToMmayeRLvfLtHYaPdwHUJy+iJnOwTYaqPEwR1O5wAcx6IJ9gW6R07Htn3Y2jeTApwZT4np/Fur90J7dg+0W/gMZpq0+7uj1eQv0K7qO5S0oh+lc1CZk63cLsj880lsN4V2YbdRzOrelzk1femJzKD/ie04rPwO1k5HeN6NVt8PUpDrf6Cy6q+8L+6yPoxMvw7++QiyErTb32uxYDRWfgw6j/oA2sFXkfjLkQlsEYbsp0TzaqLE2fbY5PdSTMH7WNsnUGIbO48spfDIerT7PxHjpS749b3I0rGagrreiBTDwwTEL12j7ocDh4Z37mf3/5OCYB6DTIqRb9wDYCzdewBMRSbH5RSU+nQMpR7e9yF7z4EIIzHY3v1Hitn9LARiOgctHH0HPAOB6LalxMR+hBLmcnckK+9DVp6O2NL23m9S0MAH2fhMsbZ/mmLFOsHoEuNa18mzo/Wnh3b/FVkTUqWOuWiH6DxyNrI0zLXxnYz0zwxkqUgoIuK1CPy1WxiL562vfUJbDkfyfRPiv4et7eMRv0SE/BzMWwbt7OdY2XVoB+o8M4kSMtlR80spcf19XIagIFDHUmTq4tA2f9ZxNjdSgIB1XhQPBtruj47mHMszmc58HY+efoAsUbsaTSajnfs0Oh97uT52HfY0JU76KYGGI5DV5DQKGM9Dpkb95x4QI+jGM2mLzWuv9MS6xTtYguxH8/QGShSxiMb+VxojI7Wjne0aCor4L0gQYxzcwxHK+iqKwI00QfGzyK6Q07F9qymxtVcYE+xCiem8NZrEp9izd1m7HqMxyP4DSClcRAkz+G2KW9xUY9a+yMWkiaI82tFZ0D0IVPMne/edaLJdYP1aZQw7j+4TV7ShFW8TBeF5L8WM7ch1T45xNSWP9N3huZEULMI6JGR+PjkITYwPIWXmiOgzrC9LKcK1hBIr3cd+hP3/KDLRTaSgsJspcbY9qcF8SkKRh5E5chwltvF9iEfGUHhkMsUtzHnpJ3RG7M5CVpClFNR1M1IY0yiI32usnUfVTLzvtrr9/2HW/4soCOZz0MKulbIAcle5bj0AEL+dgxSVo9RfjaHUQ3vG+mRHSejSarR5mO6Teky2/2+09vsk6DGxD6fE576UxtjSu9AIMrsXeK99P5JGZPJddJbnyxFPPBLGZabR7YUu2n0vmpQvt/GaTeGRVmv3GBvX/SkgxBYb79sooNNlgf6ZAo7qcH20us7AktNYXyZSYrI7Qr4JydZDSObaES81eCmgidHPzuvCH/u4nE/RIy5TyymLA392BpLvNgqSfqW14yGKW5xHYHSckI/pv9OoJ09AusblvD8FYNpkffNkK/9qbZpBcWt8Bh1reK7zsUbDbyD97jT8AdLD0fV1nr3rexQZaEaWyqec1vb8SVjo3X9O3H/bxO3I1veGexEc5cH3nXnmVb67z6WjiFfSGIJzBCVoQExQsoaStCSisat13IuUwhAMeW3PRdSjx3T+b6QAl6JJdYkJxA1owvQg+xH97juEVrTbGkVxXZlDcV9y5TGdMiE+b/V3QrFSXILiZFKXuGIpOjNspiA3vW8Oxhtuf39m9HWf6BVIkT6Csgddi87Vj0GK7N/rxjQIugfAaaIosmaKIvOxr6Kl34QWJufbsx5nu5WSDMOTGsxzetjfs6ze/cP7qklLnJfcH/0vFNTubPu7mIK6bqrQyyO/raIRJOR8OAUtbqbY/2swoBaFH9Yhvono52cQL66oo2sY+yq9RlL4+YXwfRFFfkZW6DSK7pN6tCFLTQsWE9ueO8767bvKJYSdjtG/zcaoqVLnwWjXtpai0L0vz4Sxcu+I+dR4ZYR2d3gohDpaEe83U8MjKKoalEVNi9GvByVfQnukv7WzK9fH6G3REtrhCHmnQZvVE/Es0Uuhw1ODmvDHYVya0SaihfrFgT/blRfFTcii55P5+vDdFx0OMowgyRFILp+jLK6nBFoPD2WftN92oizi20JfxkEDcn9t+N4e663ougkUGejkmRTKt8Xnt8i8tqUr+J9woQnrxxRka1RG59rfZWil6L6NA9GkNBBYEMoPQ+bjSylxcCfae6PAuUKYQSNyehnavQwM12eRwK6x90ymTMZ3UWI6T0fm8luRADsT+aTaKcg+yh9M+L8l0GQ5JTmKK48xaGfvMc37oB3ONsbwngij6mbRVeKKMUafiRSE50hkMh6BIde9jWgl7D7R7q7SK9TzbSwRBvAltNJ2H+Zq4ASPcb2QoshaQl0+9s9a+yM6+F1oglhHibO92Mo6KKantfN2GtGubYiP5v+j5e8AACAASURBVFB4xJVge4WXPgJcGu49ho4HFlNQ12MQn1TBSD+18qehxcwMlMb1XgLq3ug9h0YE80i046gqqU16AKBJ8yy0CHGUusvPXApfD0WWmgWUhC7j0SQ0ku6TenzMykynxMQeaGPpQWo8NsM2hJ2Ojd0GNAHfjSbgbZFCPxnxmCt0t4w1h7FyNHUcK0+kMTe029O2Lgl1ePvHBB6ZhmRnoY3Xlcj6coPVdzsGhEN+yYvr6B/kbApl5xiT09xn7fg4BSG/Ei0mVtsY/Rrxx+mIp91TYw2S859RUPM+LtPpPGGNpsiUb0QW+rOhvdGLYhrFFc0n80VGh5gwaJC9fyQ16Hp77k1I3zQjOf8OsmAdZ2P0u9CGE6x/7tb4QUqCn4+ihZzTcAad8zSMxlxfQ7nrka6teiZtS0hUtcXmtL/HxPk/5aIgW5dSnzzko8DV4Z4PxpRw72C0M1lMSUjxBeSKc34o9wEbxPMq9fwVxWSua98sa988tJI8wwRsK2Pehci0sxcSwgeNUbehcVf/F4Jfd+jfvxKCC1DMVhsw5YEmiqnGzOejVf6DaPK4NDzbTGcUa13iih3RRJspCE+PKjeNRuT6OAQ82gYJ9O/tfT2xHYqV+zcsEQbKlHULEuK3Vvp8PTp/foyiyD6HdgwxC9y7UOKYqyvP74yUypfQbmgk5k4TylyAJvboR3+w0WsdJcHFVVZv5JE3YOkEw719kHIdTEFdT0FKqyEanpV31P3dSEHfSsivbmXc9ScimGcixX9KzTsPR0cptR4AaHF5L1KQNyGsxWM2VhGl7gld1lMSWqynBPcYShdJPez5oxEv/sn69yuCr6zxxUzK7jMunj6DFobH2bUdUsCvRSA2kEKfhibw9RR59iuO1ePW3idDu49DMjU+1HEPmhi+EJ7dweiz0co46n6m0fhuo/NQJFcnUjww1tWMzyFIJofSOTnNj5DrmCPk+yH+O8a+b4145gajj3tqXEnjZmJnG4s/GN0GGe2ut7EaQ5GpgVbfbH/W2rk7Ojpo8KJAiyKfzKeiI7qYMGis1Xs9BV0/j85eAh53ws/rHcczA/O8CGXPs7ILKzR8HCHJnYZ+LPQriuvr/WgRc3aFt30TUfVM6lcds5f7+odDlccg+5X7fVBazReVVOAl1N9tPV21z367ADFgT8oOZgraSd2WLQmHld0r5zwr/L83nRNI7IMmnZ0Rs78N7b53Bf4z53xLUpKQdyGT3DPh2eNzzo+/iH5XExXMo5IcI6V0BVIw2yCBOhApr+OQwv785tZn7+uFhOogiq/mBkO2vybnPO1Fvm9vJPiran5roPf/9E8dgrmmTJceADVlN8XX3Sa06ArpX1PuerQIfAxNbrNyzhcmJSRpyjkf2M2zo4F35JyXhHsHo4VMn5zzLt12cjPabTRjUzziaPGU0htpTNYxIpfY+L1RzIZBL7ZdXbS1j7XtJSGp7R0vWqbq4uObnjsXgVvP2ox6T0Um9NGV+zsij4DLwr0zkb4YXinbF/hWzvmcTdRVTSTkeRkWbaqdf6/PP9zEDQ1JDb6dc/5eSuksLCEF8lfNsVx4zsttROe2DQkfsrmTWBD6i4Hf5pyHp5QOQKvHg7EYz5upDL+dc/5e5d6eaOX6TptUT0WuDg/EBBDIlJTRuXVt0ozwzsPQ6tWVx7PUJFGpCry5/Pwy5/xZczP5LPD7HDJlpZR2ypVEJPbO09F53yMmaMdgKfXQAmN4Sml/iqnuNrRjONR+H2Lv6oXAdz5+368q/5TStTnnz4a+fgHtDn6AjlDOQmbDc3POf7Fy70UxzGehxdJNaEGxPfDVnPPgkKhgK6NfbRIHe9+HENbiFLQru9L6sgbt4m7NOT+VUtoPAWL2Q1aAH1sd46zeqeGdBwP/nXN+c6CDJzkYj3aRs5A5dxba3U+yZ7dFwMvXIt/k0xHQbDUy/XoCj52Bn9kizvn4LVbuDrRrqm2juQm+ic6JHaahY5koP0/ab07DpSj7XRwnT94yCu3mRiOrzLloMXs74qMPW7nv5cZEGGeindOnAz/0sf4fgRaIF4e+XO7KOllCiwov9UTWn71RxL2n7P7uKMvdRSaT70Vm1nbKpwmNf6IRgPZRNiG31o8DjG7XIyvcMZSgTbsC9+ecb7bJ6of2nplWn1sALgpjtS3aBd+GzOXODw10TCndmHP+ZOhHB29nuUfthnjb4130QXgAX9Rej7waYoKYd6IF2KPWtxOQDA2mZD/soFd3C4/UdSKgBrc6G/cvUpIWTaXooMuzki3tjMalf7ZkJkHOjjY69kHjv9bof03O+Yau2vdyff5RJ+6mnPOAlNJ0BFJ5O1JC/4GE5vvG9F7ul0iBvN1ecTBipP+y/3+MzpYmIoG4GgEj5lmZjyJF/qeU0vuszqGYcIV2/TLnfK59H4DMke8PTd8OAbbuyTnvkVL6HEIKJ3QOeDaavD6MmGg2BRw2xN71fM75SxV6TM8597XvlyFltBGhpS9GSvoApKQ9dd8ZCMCzPdr5/AJNrCAz6H9Z2TVo9/x74PYsn/T/RpPdtsg8tZ3R312lBlpb7kRK9oWU0ilG18et7s/nnG9IKV2JUMS3IdRtH6TIsff9CCn5t6LJdz/rz21I+AYhU/hYdNzRYm39jI3bTmiifT9SZsdRTN8nIsVyADLVrUIWkAnWhstzzrdaX8bmnA8ynvsrsiQcgawQfRDe4M8UDwUPCjLIxvAtaCK7NAzdj5B1Zjejw3HoaMKtKr9GSsWDcExGJr6zkYvbDAQUakEK6zVW/0w07lhbWhFvH4A8By5Ai7sPW7sHGV0noAnia+j4og9a7Ewxep+Iztrfa2VvszreYddwNHEPQ+eP66zMu5Bp9492/+O2cO2DJoJJaJJ4g/Xjj+iM/DUInRw/CZ1R723j8gg6AtkBZWFzc+vxaMHqu8H5SLnvho5kxqaUrkM8/AzwCTR+7Ugm90T65Gy0qHRPCF9I7I348NVI58yiWL4mWdlXIRk+DMmJJ3BxIGpvo2+r0ftatID5GnJ5W4cWRz9GQYsGGM162Dh9Hu0ssXefiLA0Tse3INlxcGmysXjYnvkEkoOPI/m9AJ11D0cbiies7b9CuvOPaDxfbTQHycA6JH/TkC44Bek5kPnc6TUTbSj2A0gptdhv/W1sEpJNXzC7vvYwscfZ98XWlrFIf33caHcL2iiciuRoOxsXN/lfhhaRuyBZWIEWW8OsT39Acjsrv4QUvi/qsylb+v/vF51j4y6lMfasI0RvRyvTaZQkHDF2spfzsIkxSpMz9URKEPp2iuvKiFD2djShf9DqWVdpl3/PaPIcGq6NCKW5Fk0orUhx7IIlgLA62igoUE+acSGaeGdTXFwGIYW4jOIStA4J/ecpCTLcV9eR8lOsDdPsr7u4NCPBmUkj0vwihIhfiMB205DS2crK+PnQsUiZub/kUorvewsWkc2+d8S3tn52heyfaX2KrlVvtPF0hHWMvf12tNNeZzT/LAXd7ckUPN7xtjYGvdCCaSt05tViZVdTkluspiQPcYR1S+iDo/AXUxRldwjwQfb/svAO581EIyJ3NHY2TEnEMSX02WNgT6h5tp3C2476bQ7j0OG1EN43FCnkNsQPTYFeLhcRCNiCJroJNCbzORjJU0RO96W4IU40enqe+vmUzcgGGvl1ClLuzrN9kNysRRNmH0qMdeel+Lzz0gZKQos5FDc1H78lSDZbKElZvoz5Iod+rMLiFlBc6sYgl7rfUOR2HVrAvxDGfYP9vd7bHHgghvK9xOrZhcLj3Xoe2Fg7PzShxe4kNOkdb884buA6a+8kNGnfSeHtavz5kda+oyp0aEFyOZrixeLo+gmh3Cw6x+T4M4bapzHRx0akr+LYZ2u793lNoEMO9TxGQdf7uMSEPK5vRhNkhSIbPfgnOO1lmbin0zk8Xx1CdFTl7yUIkXk8ZsINjHZERUA8q1Erxa3kMqRs2yhoyX7WnnvCsx74pUO47P4YYE6l3a3IfLoCCfZitAvs7e0LytOV6wP2111cYvKRDUiRrqFeKXQkUUEKM7bP6TSD4uJSdffa3X7/q/3tjXZCSyjxq5dRkiCMMGE6GguoYvcHYBOU/T/Zro9Q0K7exkiHptBGn3xHosnEg7UcbuN3AI0T1mNo9zCCgu4ej8A3T1ESinh877FW/3CkgN5CyYzUDy1cfoIWThFhfQIyM3q9sylo6k0hwCdbmY8gHu0I6Vmhw3gaEdJ7IN52dzeP0+y8HZ+9DFkcxlP4uBUtxp4IbRyHFnktFPc+558xgV4T0EQZwYatFNSuJ5XwcZrkdQTenkZZ7I1Cyv50zO0q8MPYCr02IkW9nkaFPs2uJUj5T8SykNXxkv09Ek2mM2n0C59N8XqIdNzbaNAVWnwkRWbHU+T2CLQIjp4avtjoS2Nc+Ak1fX7a2jkHLY4mIwvZL4FbojyHvjk/9EB8vwx4i92LXgauA36NfJw91vyH0ELlMiT77nkwEVsgVvTc1pTMjK4L9kcLd6dXRjI5tHK1Ip3VkeiDMvHH9K/rgL7h/5ZAw42BhmMq4z6Sgq6fSdE3wxAmaLTR88HwTHscgy1xveIT6xbvoMXWrdzzQZ9GQYiOQwo4BiUYhybJ1aHcABvMVRRUdkbKYAWNQej/DSnIiJZcQIgZbO37Lp2TfZxK5/jQrjw+iBTcZIS4XYgFALDfHyRYBAKjvZvG7DauFGKKvjV0TsryBbTQibukIcgc/meKi8sEtCCITOzKqF+450jpBRTk+m+MppcG2rsFYpkJl9N1MI07kNdaG99JYwAdd626kzL5fgwpsZUUhPUytGqP+ZQd3R1jas+3elspyRT+YO2egSVxQG4i/4fGZBaOsF5BQVj7rj4qlBPRgjKzCQS49X1IoMPpaDf4KNqhXIsU2CpCMphAw8dpVMQDkAKPgTLGocmzlcLHUxHPtYc2zke8802Ka87NSMYWBHrdZu/3Be3FaDJeab95BLQTKTvqGMt7fWWcrsM8RGj0Ub6Uzm49rtBjbPF5aKH1PAXtPd7+/2wNH8fUtu5FcVy4NxLx3DosOpzd34ai5Idbv86iMfGLJ7uZUGn3HhRddWRob2zzIzY2V1We3RqdWXvCI8cTnEtj3O/rgC/X6M/90cbiVoRWX09J7TmZEu3uO0j3OW8vp+Rtd8+DnyKeupLi5jXYxn4pjbqgleJyO9zo+bpq+6yNM6kk+kALpVspE/8C4JDwzBmBhtdRYuuvRvIbx8XlawlF3xyM+NY9RzxoVIPnyBab17Z0Bf+/XMhM/m46u76cTFAIdq8nMocfZtfuXbyzIwh9pZ531ZTtVE9Nmaoi6mtCsyMwMNzfq1oH2g31w5JmhPs9kLJ1pTCLSlIWK9cfC9Bv/++AQDEXUVxc/orOuvcI5b7SRV/2pPhyOsgursQ7ZT3qjq5d1FE3+Y6h4lqFFmw9N5NPqglFvoLcWY6gksShm3fsSMVdZRPlX0z7etA5Mc2h1Cg9ahJx2H0PJ9olb3fRxhPR2WF0zbmCEv420usMGpPvfIyQzCf05VWVOv6IdotHOQ/Z94YdpJXvFFqWzgp9MpJnz9+8FbIg7FF57szNpENfgh9znUyiRfe72IzEL3bv1ei83l0fN6vNL9dFOX54P43Bgi7F3BmNZ27cFG/T6L7ormhn0VkXxNCmvZHsvqGLd7pvdadEH5SJf27Nc3U0PHxzx+WVvP4hwGkppXfQGdk6B+3O5kY0ds65rZv3eID+yTkgpVNKlwPfzo1JBP4FKcwJuaAlHbV4bbZkFt207wAEkpsZyn0l5/yjSps2J3lBbbsr79kTgb8Ozwb+6O5Thy6tKeOJISbniiuFuYMcSSOy+LUoA1cVFX4kCnpzI5ZswPp0Mo1I7odyQMx3gYB1s1Ztwg4r8zZkwn465/yQ3XOPgjY0frkrelv5vuiIZkQqCWLGZ/MmqBsT80Y4FO1UFmdDgNtvJ6Dz9m3pArlu5W5HXgsNiWmqfJ0qSVlC3fPQGV+UizWIn32sVgB/yDmPtnE8G+3W26xN6+nms5k8654HEW18DNrBbUT+05F3hqCd0p7Wj7G5MbnGvvG+8cHFaEG6R/YZqotkMpvJ7w11VH470Nr7dG5Eup+cQ3ITQ6SzKb1kblAn09llqZN8p5Teg4KsfDcHd62U0qdzztd736yNp1TeeTfi2015mNS1e1fEq4/U1Rv+70vnZEodsmJlOqHFHelf7W9N/3ujReNUOuuMhWgx12WSkK50htH1g3ThXbRFP6/0ymFLX2gyGkYJozkMmVRWIdPHv6NzoN8i8+2PKKY3j9B0MjLXTUdmmWX2Dg/tuJISu9uTCMy1+yMpMb8/gc69b0e7i5+gM8ZJCKXr7fsWMkktR6bDc6kE6rB2nY1MtxNCvY9a+86wMt7uoVbW88/WJvbogoZD7Hre/t5t7RsJ3BvK3URJGBATQyywsl7v44jJ70dmquuQCfM54N3hfYdSn0RjAloRX2e0+52NyxJ7t7dxldUxBJmwbkRKf42NQUfs51DnOchc7GeVF1FiU//Gno3j/CiWLCK84yIK+McTxHiCgwvDmMy3Z9+HFOYUGycPWNKGdvL/hUx0U5A5+f9aOz0pgo/POEq861GUxDTT7XkHIH4EmQT9f697GDJ3LqDIhYcAvQ3tjM7CsCHWzyvCbw9aG7w9vwJOruHZhUZHp+E6xOvfp+zuPLzv3XSWn8HhfXeG796PQUaDs2vut4f7ve1/DxjiyWTGUcBvzkvLrexSSqS0F2rq8JDE7ZSkM+fb/x15AkKbI27kc/aORYH+U+25c0O5TyK+j/G0r7F7n6zQ+3K0S3agZ2sYn8Whb2OtXxeFcb6RAp49xdrzqI3/JRQ96e1+PrTbj1w8udJ5yP1qV6QDPKHISkoKYZeVF+zebHTE5ZHfJiPe8fZvRHrkP4GDQp8TsuB81L6fiEBsUyk640F71zLrnycJeYqQJMTosN7K/Y6iM662d56O5Plt9v0+4CdbfF57pSfWLd7BggT2MJqOBN4BCagjP89HgrqEkoTDz5Q9iP0ApGjvNEYbSIm3+wVk9nOEdQvaQbbQiJz+kjHBN5GSeAGBOMbZ/W2tXDOanN6NlO98E5pzkTmuDxK26chEtBQFy8DqdICYt3sQWiiMpyT2+CyaDM+jZP/5s9V3DAW9Oc4YciEFXboBTZJLKW4U0Zw9DO1mBlHy7Xq909G5UDWq3KWYuRxZHJYbTZ4G/iWUey70z1HITUj4xlCPgPUkF2OMhmOpj/08Ak3yzchE2UrxKGhFvDI+jPNP0YS+gLKQW4hMt54wYrfwjjFhTJqxZA8Ub4RRyPd5NAUBPi3wxFZY8gUrs9j6ehziyTloN7qSYsZ05RuTskQQotfdinYjYyhyMcHaH8GYY9HZ6URKqFxXZNMoiuxK+/0eyiJhGmXydhq2o2OXFZQELI7srXoebGt9/Co6N3YvkB+iRV6d58GwcP+tSHH7pOMAupMpyWSa0MIhoqlXowXUqZRkJGPRGe3lgYYPIz3QTkl6MhYdJzVT8gR8ycc00NW9RGYG+s9Cm4T1FDlrp+ZYBum6NRRPhha0eHVvhp2QfhtnfZpofz3T3zsr72tG/DCF4mFyvtFlEUVPertHh3a3ItkcRYnZvjC81xOKtCEd9zRFVoYgN0QHd/a33x5Dk7/z1xQ0+T9DQfpfhCbY2+w9N6Gjken29yfWrqVW18GIRz1JyERK6FxfsE9DOv9his5YTCUDWVg0dHvk+c+Je/MmbhdMD6PpgtkTCZQLdyudhctRls0UN4e64PkR4OMIa0dLttGIlhxDQSZuiyV0QCbl9UBv+7+JRnRjLwrow7M3raG4N6wPZWNM7qrrkS9Ghlu5VyFB9uw/7vo1l0b05kT7rQFdihZAn0CC6UkE3o0lhgj1toV6JxLiOod2j6Uo7HsDLY+nMVNQayjnKGRHwC4PbYzJA0ZW+h8TdsxCwj8LAydSPA/GU+N5ENrmMbpnUBZy/n0BJUFMR2z3mrY0UbwROtyq7K8jwC+ycn0pqO0eSOk+jFDsLZTzz3kUkOERRpfapCyh7ugWNzrQoR+NE8yD6Iy6nRIqdwI6B4xIandjc1DPIIpL2zJqvBEoCVhWWV+uolF+bqMsjB61fr4dWSFiToGmQEPvn+98F1MmnWHI/BuTyfRAC4PIS1UUeDVxjNdRTdBRl3RmOyQra2h0AY1uqqMr7xlNjZxV2jQPTTL9wjUR6TOn9VYUzwfPgDeZ4JEQ3tds72in6FHXk03U60lv97hK+3sa3W9FOtHdp1rC2Eee/RBayDlafG1sWxjjjokSLXSvQnw3jEZ32FbrewvSGaviHEEj77eF9zckk6nojBYC2j+0obXa1pf7esUn1i3eQZnynkCC5sjWWUjZXUPJC9yGIT+DcG1AO91VJlBuUutBY/D8lWg1/nMKwvonaHL3LFOOllyNIhGBlMSc0L751r5LkCBfU+mLo2I9fZ2bu2K9xyJz5zJj1mVWz0i0ix2DJfYIQjWW4p84Bi0iWmpoOZuCLq0TpE9TEip4Yogp9vfKUO83TECeR2fXZ6JoRKuBb9i7RlCyp51m9PaECJPQ4uISo93F9kwfpGS8jcvQDr83xU2lmc4uWFOR8ppuf/ewsfXcwEPt3hDk1zkv0HskMr9FJP0NCFG9gpIgZo3xw+IwJq60N9iY7YEUzoE0uqadjfjI/VPfb/d3s3occOVeEHeFej+OLCi30JiUJVMQ+173SLSgaqHIxclG76UIpX4tsrR48gqPs+2m5BNDu0ci82GMeeDeCL6D6sob4QK0AFpMjecBxd+4K8+DDZSJ0PvXanRvoUw6V6BJ8QVKMplB9tsXKby0hpKa15OReN0bQx1taHEfx6/Zxm1OuDfdxmRDhV69rN9O/yaCXrJ75yJd4YFyLka6bClwWUUm70FWg5sr939iPPBza8vJSMbuD+O81O6dTPEwaUOTsE/k26GF2dVIh+wd6j2Jzq6Fo41e7lp4KwYeozPP3k5Bi6/F9F6Frp0mSrt/nH13t7orbMxc3z5rdXzW2u95KdqRzjqMzounaHUagKwEE2n0wBgOHLbF57VXemL9e1x0RgJ/HymUHqHMY8Zo7wr39jPm2YBWnr3s/q7I7OfB8/9II8L6VGPcGygrdkdLXokUx2/QKvdT1r6T0UThyNsvxfaFNkVU7J5I4URk9z1IAR1OWXX3Qq5SM9HkOwUhcSejneGdlBXyqcgkNrqmbkdvvp8QFKNS5nUmJJ4YYgjlvHAKJaHIMcgs/zO7LkII8BtozBR0NppsnqegUN9nV5coZGvjD5CbynSKm8pKNNn17Ypfwvu2xUys9v8O1q5vBXo/aO2OSPq6BDFuUj3QxmTryEvh2UOQUqh6I7wGme66RK4jE/mdod5jkWL+GvBqK7MXhkyueb4v2jVX694bHadEpHpPFMjmFLv3SaTIxlIU2VQ08RxWoeE3bMxdViajHXQVyb0pz4PrK+XjJFHn0dEW71v9D6DF2CRKMpnTaHTZ/D9IXmNyodfbb9XEMRcY7x1dod+7gIfDve+jSefYCv17AVeEe3+h3ktkZxvniMzfuWZMe2NWvJrf9rK2eoriqkfCp+jsZfMYkr3oYbIvmnA3VOrdv6bdZxtPRBfZO60ul5Uqzx6CJv0qf82iZqLE3Opq+vtxpAdOMjqfa3X9O+Uo5s+UBDi+YD8eycWzNe980R4YL8f1D4Eqr36qiFq79ykUgnRuTfljs8UhfpH19ADIFUQmYoY3olVrJxTjZrx3OzQRX4wCB+y+mc8lQmKPlNKgSpGLshDbu6MY2CeGZzeJ/NzcejdR9mwkSPsjM75jCq7IITlEN8/vRkGJTs4lxnJtkouIfEco74gQfSabgGwOMj+8c9dA4z7QdWKHLhDW03LO8yv3XouOB6Lnwbic873hXQcgJTcu5zy22pZNfVJKfXIjsrtLr4DKc5GGDTH86+TppXxC385AgLDlld/3R6C1t3XTxkeBC3POT4T7W6Fz/o/nnHvavU40q9Kmm3a+rOU29+Pv60bn7IfOq7dBO8hu9U6Vl5yP0WJ2fd24Rj1Zw0svRn4G5JybUkq9cvC+sd8OQosCeJH8lVJ6NVoMzNtk4c7PVpPJOL0PJ6DUX4o+f0mfv9cK4ZW6KKCYiKhdhHaFV4R7c71MeLYJ7XJiBJ4XkGnU42qDfBd/QEFELkQTzgp7b0RkzgT+Nbzv0+H73lZmEVr1vb6LPnmYyf4IGf4LtCL8DtrN30Ln3cvWaFfkZ3FnotXmF2jMn3s+IXCE3XOU9HgK8vO3SFH/2MochMzdv6UAhwZSgEMOBtoXma8PDLS7ztp9MyHKHTqbHYrO8/ZBxxuLrS2HVmi21H7zkJZPU/KaH4fM5B+w9lSR702U1ICOcp+OodzpjMz/PcU3+b3WnmnoTLzNvq+0cZxo75mPjiEmUFDJk5CJOXoFjEVKYE645+Fmn6PR8+AFSn7iT1A8HlYg3m6zZ2aiY6J7Kcj+RygpLY8y2i5DC5ajA208WMgCZD7d2cZjV7QDjd4DM4BzrD27IXk6qMJLHkikOqYjfEyt3MowTp8wGl2HzN0xCEonebT7dR4OT1gbPxrK+fiNDuO30Gh2IuLrCTYOs5C8OC8fi8yj0wINp1Hit2+HdurPIytZ//C+KWhCHUjhzeORPHsQml5oF74NWrwmtDO9DfFHHDuPMOdR0lznjETyMArx40aj93jgTYEOQ2vo/XvK0Y7zsYeX7R+edTqMC+1ZYrQ+mkb5eZ4CzDsIWSDPozGU6XwrtwjtrGNd4wO9DkPHLr+j4mePLDiHh7IXV/Ts4+hobqX1bz7i9bOtTNSJ7sY7PvRvltF1hLXTUemPE1DpW2xee6Un1i3eQSnke2hE1GZjqgnh3jL7e314dgpyD1uPlNQFxrxftEFyBOxwNGntHp5tReawJzBElPa0IwAAIABJREFUZlAiy63+a2k07y1EZy49rL0TKHHFL0Tm5+9hkc6Qme88NLG2WBv2QUr78Yow3GdCsJpG95o/IeF2RPQqJJwdbmhIQfRGiwNHfl5qNFllwvOY9dlzDD+KFgZPoEnjdxSXGY+6dTYl3nE/+z4k0OMZpFjPMHqdavcnAn+177cYzYYjpfooMkEORhP2VIoSuAdNao9Tkln0R0J5aGUsmtAiYxwFBX4dOm+bbjS7CinEN1p/PB76X228oqvPXch9p4mCSm6nLLwcYd1q7xsX7rWhHXcrIT82Wgj4WeOI8OzxiGf9eOgOpMzfRkH2j7d2XokU/tvs+QGIt502TyLXmlZ0NNFGCUXbHMp9jrJocpegtWgR4hiRZUj2Vto1A5m/fbGxvlLOXXVGYEE90I5vDMWDop0ij88jeXwrjefqwyghLXetjPMMo9nRYfyaKPHs70U8eL71byEF2PYM8GZK+Ny3IdP25VZmDDJjt6KkNY+F9x2HFmmLKby5GMn8eyiI9HHW52aK690kylHUAsrZ+3hr074UFHgz4u1n7f4SZPp/1MbnLmRmj7nMRyBZ/yvSEfG83sPLDq/I6ZvRJsXp0EThJZefS609Kyg6Y6O1aTKNORmett9PRfL+79aHpYFeC5AsfoaSX+JVRtsVaDHpZZdT5P4WJLefQhuRCUgeX4eOvpbaux9CvF03zs3I6vmU0dVR6SdhqPR/Ttx/28TtYT0jonZWzb2FNE6SF6JJ6MtoFVuXfMIRsO5jGEMpOqChA5Fp/z+JJv+dkCJcRVFCK0O51SYIl4ZrtTHVejSpRuUUEzE4KGdouJbb31WUYP5fNwaeQ/HdnGX3fktxQ1uGdgY7UlDSrfaONmvTDvZcb7SI8EQFnoClheIy00RJwBIBH6usb+4v2dxF/yJi2FG8VSBJk9W9G1J++yJl14aU7kMU5PtEdL7WVqljaxurTsh8SlKJRZSkII6unRjbVmmf/zbC6OWo5NmV/rSEexHRu4jiedBMcZ8bSiOCd12ou6XSluH2rHsUOL6hzcaxKdDG2+1I2xPQDvydlXLuEjSe4hL0U7Qwifwf0exuOfopwmVEfl4D7BX6to19Pw3J4Chrb0xY0YrksQlNSj8KMteDItdzKWE714f7Pn4dngeBpnVeJzPDOFRR1E2hfxGx3By+u9uh8+YoguKngkinuN5FpPm40P/mUJfzTOTZnjTqmLFoUXaH0eFPkd5ILnrSKBdOq/nU68lxlT43UeTHdUYzRWd8BC3up9TxiP3/JqPDJykL6jp6XUJJ8uP99rJNXtaeq+Z2cJT7CEpCHl80xIXquC7oGhfpbbH9W+Lqwf/yT855BBqwrVNKQy0K15qaezvbtX24eiBh7ZFzfiIr5eYYtPI9Ouc8Pef8Q7TKvh0pc/9slVK6CK3oPx3ubw+szjkvzoqCthoYmVK6xZ7pZeWagOU55+/6hZTsTkhADgPemFJ6IKU0EClI/4xD5z8n+IV2AO9BC5Rt0ST8GbR6XJxzvinnfBOa1I8E3pFz/gwCCD2D4qnPQwuewdaPa5HynJRzXmr0dvTzfVlcnP0vOmOegoBWn0ST9w52Bg6WDMPo+WXgTSmle1JKlwI5pfRBK7cvsGdK6WfAbkazSSmlbwE7JqW49OQTi20cp6Nd/XeBbyNl8BQyYY6yfi9MKZ1pUbr+Be0EtgNen5Sbd2s7Q9w657w+Ky/zIqPB3sCilNIFwNiU0qOgiHRJUelSSukOoNkiMb1gbboM7abHW7uXpZSesHH2e6NSStPQQvE64JaU0iVI2e6aUvqetWG/lNIQG//5KaULUkp72Vj5OfoANKn1yIoElRFYDKPNUBsfp83OSWlYH7DxHYoU5H3ozNLLbY8WtvcaP8zNOZ+PrC39UkrnG+1ySundKaWP+phauScq5RYCD4W+PWZ8cB1aIL8F7Zj6J+WDBp29/jDnPABN4GemlD4d2ngZslBNsvZuZ/0/HsmGj9/+KaUmtDvbOylXdY+sc/VeWTmsj0e8exVamDoNN6aUXo/ka1s7A90vKX3o/uF9Pf9fe2ceLmdR5f9PBcKWQIDAsIgEBAFlBAUBFYQgCC5MZFFAfsoyoqgogisjjoiKqKiIOqAMEgZQRBaRiMiOLCEkcO/NThJIQhayIFkIIWSt3x/fU6nTb7/dt2+SSxJ4z/O8T3dX11vLqVOnqk6dJUqPoSeZNnsaHt5kuL4BLXYPI72YydamHkGxznH1JtjIPhPPeTKEcA3ZAiHpfKQ+/TnGeDzazB7g8Y1402TgfkfHl6BrtllkPrmh4bKHa89eQWE3306eP8sM3z0xnhFjvBVJIHqFEG42XZqVntgMD6ORpO6r6FSc8LUx4kcJXxejq4mEf1zenZDy5v6Gi1eCPCSCrFHSfXyKyEaM8RbkGa2f8R4/V54MIfze4fUhh9cN6G7o7p3BuvRQolHr0l6lXjvxT/bpI/P8oqTcrdBinu6455LF7FsX8o7B7gHt92mIEc5EkyqZnB2M3R+7vGkXu519/hDtmG8EXnD5voSZQbi085BUYDbZvCbddV3o8q203XRpSUv6VLK2cvKe1Itse3k1Wuj97tPbpiaTmQuRuDZJFJKjkBHAde7dD6BFaC6SClxubZ6G7npPs2crtND9D9ohX4wYyjXoJHch0vxPJh/vwAKzIHHjlUhkdj5Zy/3H6I6znz0boXvTE6nVg3gz0kRdTvaHPhox3EfscyQ69U22vjyKmMsWNoZ3kDWs/4FOxBdTa6FwK9kMLFkenGj9/gLSjB5o795IrW/2IciaYKVmP7r32xn4aYFOPoAW74Sbe7E7yUK+Q9GJL+V7AfiI/VcWXCMtzrOROPIupHSXxnQ0oquU73nEfFPffo0kRMUAHL9DJ9FzcHRn/+1OrYXD9WgR/An5uuE56v3ZTySLiQ+zcXjAcHO2K/9Y5KjFa1MfYe/PojZIzFx0b53Ku8beHYjRptV9FLVShDeT71GT6d0ItNk8otDfY3F3uZaWHCvdg7ztfcPSN6XebruI728jvZl/kOl4Llq8vQ/5Aegw4PlkPySl/BF5/jxh/TmeWouePmTR+oNGD/sW2pbm8p8dvn6KtOKfLuS9G226/5/Le5r1/3n7fjA6kKS7+HSV2QFcUCjvDETDCwp4/S7aFH6WrJVeh9duWcu6u4L15UH3Qds0+G+7NVjPKdjdYyF9ZwrRwErytDf5b7MW6i6a1/zQiNbbbj6M2W52UtbGDdK3wSnzufRQ+F1mrtOsf/1WAdc7kk0+ujS56EIQkHXpoRBExuO/EX2voXpbCa6xA7a4d1JWw3zoumW3QlrSGF/cYls/Zgz345SYxTV4ZycaBxM6uJN364LEUGuO1CltUmt6dxAlpqKvEX3tSYn7ZfvPK5bW0WErPMPodIuSPC3jq6u4Lbx7JIVNg6X3obCgr83ndW8OZmK30xHBJzOhCWgX/Ao6mT7m8n8nxvhD+/5vSLHDO5KfhYgruTQ8Gd27bY5EJlciccrHyIoqESkBHYBOQOfFGGe5Oo+2tt0fJYZL6UVn/HvEGMeHEK6KMX7ORMyfsPJvQSeCjyHpwcUxxvlBDvbPxwInAJdEmXQlU5HnkPjJm0ENizEud/X2RqLHT6DFcAnZV/LfHV73Qsplr3YyJo3avRyFFlxh+c4Bbosu0Iqlb4jE/H5cZltbbkCn+4BOYu9Cm4Y59u5mSCIR0fidhE4k/0DjticSq25s5ZxKjjN8IJKK/DzGeEvIgS+WoRPFm6wPEy3tRVfHCUi68f2YTdTGIab/LzO/uQZJA+Yg+tySHAzhyhjjPwt42Bqd3r0JVJvvcwhhfIxxDzOH2jZa4JJgARpCCPsgqca30MnpUcNHLyQxOhbRzWkxxvH27lssz/NIMnEZZp6GTrMp0Mv0Ap2nIBw7IzrzYz8JGBQtaEoI4Uvo+mdHpGg00HAzDfhWjPHvrtzDET0dhOh5PBL3/z42MOM006DvIb8Chxb+G49OlSdQG5DitzHGhyzP7oazgTHGwW789kG84TMxB5S5DZ28X4oxDiprj+Ur0ubJ6HRapJtSUzKbp/9EUo6d0DydhKRVu1lflqD75WROl/p2FeIDOyGz2MFW5tHA54FzY4NAIc5UbOXfSCowxvryBaT8dazVdS7SZ0lz5YACriejE3wva8sfXb1XRF1Zpt8tBfqw65R/2pzYFs3n/ujgchKa9x8zXP821gYrWhnMxK7lvoXotp/150uF/p0WYxxLN8IbYeEeiCbzfWiH/RIyE0gaj7sgYv+hvfIgUsAJiOiHIHHLOPv/UnQn+TISD45F9yY9EKOdgURKR9l7+1q+mej+ZRCaPP1jjC+HEC5BYps2dAfzyxjjr20ypLbUdAkpVuwUQrgBTchFiIlujMSuv0E2reeEEK5CG5RZSLSdtEK/bX3YEynpDTJ8fTHGeEUBh39F4saLEcH3QuK7axCTSEo7B1jfbkdirbut77ch8e0DMcYYQrgCMdaNbDxSuz+KoqR9xeqdb21/xt6/Ocb4Qgghman8H2LkoLusl20cXrC0nRDT3wA4K8b4R9MlmIruNGfZ+H3Y2ri9vfNNJD49GW3GOmz8/h1N1u0RPfUmOyKZaeVNQgxhZ3tvQ6vjQ+hkmDxjBXTPnuzgp6KrhgH2335IPJs8cx1nOF+5YKGFL1rfsbYFS8P6vpmNycaImfZEG9nfxRj3s7vcB5EWcX80zn0t/xDDxTTkUvUvNg5fNbz0QQpU1yKav8Jw87jVfxASgX/B8PFLtKncCY3paKtnJrqqeBltwE4Hro0x7m3tm4Gijv0lhNAfbUoPBjAdgLei64SjDP/jrS1TDP83ATfGGNspQAjhZcNvcMm90D3nMjRnX0LjMt9wPg8x6m0NN1eh8W3UxumGk+PQAn4jCs6zpNCWRJsfN/ykwDQ/RHR2tH3fHc2dM5CSXIIbkFb8PugapRcSzW+C5uckNF6PGs76og3rI2gMZ1gZn0Y88VW0KdwLXXf9El1HnY42a5PRQvsuNIZ+w94PjWWw9G+RTT73QOPSjvjPC0jsfbS18QOIRv7P6l5KdoZ1cozx3w1fv7SyriPzgZ0ML1ta/9NmpRcK1HJtCOEmtNDPRxvD7Q0nd5DjOXzabXLbovQmEr31tT5PQvfj/ax/NyGN/XOj84HRLbC2j/zd/VBw3YmY0QiyRm3SDo5k/9+T7Elp/k68A/OPS9acTmkj0CkDajVTvUbvdDTx56D7mufIWsLJGf9laEL4tkxCC3Qyufm0/Z9sWxeSvXGNhTrf5O2IQMeQTUW+iu6Kp5I1RF9GJiJ/dWnTMa1RK2uY4XEvROTJ/KodeZ96ilpn/L+k1nwu+Rlf6UvYfr8fTfJkn/oSOtnPJt+j/sPwvnlhXJM72MkubSE6ER5LNhdJWtJtbvwSHYwg+wFPeBuJ0/R2Y5o080e6sd/Q+tmB7t1HuTruQExxHDlwwlLyHXqd72ZHr0sRc5pHNl8ciO7olpHFjL9CDNaLLCdZe5Ir0BS4ZKKji+TudpzrS9IEThrMI8i+spda/UeRNac7bMy8JUA7WkiGUxvIJFkUJD/SHYjhjnDtm+7KGObKvIGs4X40mgvJJv0kcgCWEYb/PdAiOxrR+Vy02CWb7XmITk5wdSwp0NYQKyvxjGQuNY7sIjaN3x32zC98H2T1JBzORXPsi2STzXHoEDCDTDfJFOkZsinScrRQpahak9DJdTG1/vmHGZ57YPfAmFY52ZphiKPzpDGdeOJ8sila4k2jkaRiPNm08HfWNm9V460HnnF43BPNvcQzRiJx9i2UzB977wLr629svJNp7rMNeP5fDX87kU0vJ5K9Fz5F9jveE5OYufnyAtr0pXq8tUOaK95a5plC/W1l7VqTz+teqxxYGuRVyWvUbhRNozZm7eC7EXHOjDHuGmPcFTGoE2N9fOoDECElzel02t4Q6B3kWezfQgjfQYul15yejYhiFzSZ+wJTTDJwIDp1b4FOms+ltlh7no0x9kOLxjlIgexMxDBXxLyDH2XtARhumq1YuQsRsx2HtIj3QAtQ0hDtZe967frlSDu0h9OI3jTKS1CIMSbmEmOMl6P79iOQtGGBtW9nJE6djjTCJ1r9w1y7f4528Wci7eQZMcbd0Glma7Q7vsLwPM2uQRJchibs5iGEX4QQNkda7OfHGG+PMQ7Awgk6jdw0flcgptQL+EcI4XKk/Xs3YoZp/HrYFUNPsmb+Chvjnta+DRAi5qKJ/fcoGIA2Dm9Cd2iT0SbpInvnLyGEc9FNwjeNJhK9jkAnkudjjGe450BET9817eYLELO90Wtxozu+GdauoUiK86YQwtXWh42jPFQ9ZO0BeMjEi9FE0XNjjNfHGD+CmPckJIFJmtO90ELsNWpjjHGI/ZcsCpZFeSVb4cZ+g6jrkBWufT1CCE8YXv8SQjg3hNAPSQUmWfkXogXtRLTgXejqX4Zoc3yM8Qcxxr0R7d9Mlph8Jsa4JboOuTbUar4XecZStOGINm4L0WJzJTrRpvE7DG02RyN6/jmarz9HViIJh1ugRexil29HdD2xJZk2e8YY08b8hRjjo2gReh8KQpT4w1vQgjTX2p3m6ULLGyxtaQhhtyhR8CbWNwzP0QYt8cQlSDmxd5S3s/9A+gd7I3PDc1Ggk7MQ7/qSm3sefmGfmxrf2cjxjBVoXuxNnj8bIzoO1p6L0UJ8ONrUfA1JDHYOITwZQvhcob63Ga6mxRh/gaQlyTnOCYjOe1neQ9AVRsLDXLRp3NnV87YQwsgQwpXkubKBjU90/UuwEd0N3b0zWNsPErtMoVaj9ga0Oy9q1H4DEdIv0II1jXr/uHPRTsz7X/4k2nEuQYRxHzkwwx0015z+G5oQn0ei5JR+F2Jkvn3tiPF/GYk37yaLa72t5VvJnrmeQExnMRJ/7UsOGLAzYmQvkLVsy7Tr97E+r0AipT2RaPkStGD+HInN27GTm2+zffYr9G0/nDa7pY8ke3YbS+3pzWuq74KY5gto5z8eLWA3oVPdALS7X0ZBicdwMBYLlenST7Hy2q0d423sLkrjh3bfyTNW0sxPjixS4JOPIinILtQHdtgNnTxT4IRpSOz4BNl382TEtJ4l0+v7kai6hl6tzHfbZ+rzTLSR9NrZZQpd19t/y9HpeTsbu2SimHy7L6Pg2x1pTo8zPCbN6XmIxi5FC8X77P2lhp9kUXAXFujDlTfY+unjom+O5t0Kav1av0AOZPEous54DjHmJWTN+5El+Pc0VIzq1OFwlhx7eJ7RH51QH0Mnv8FGF6Os/tTGlxF/6ePKfth/2vdRwFsLbbgazWevnT3c6OZRcqyAs9E8HlV4fx9qLRf2tLQ2dBB4FG1SUjCdF8mxA25GV1G+vL+hDaP3CfCU9X8FFjTI/TeGTIfzKfgLRzzjMjRPE884yfC3kDx/for46B/92KEN/ASX9m4bk3nUBvpYgDZlkAPC9ESSgqVWT7R8RdoegaNDS7vWyp5AnitnIfH9/YW8u6Przu5d17q7gnXhoYsatY74ZtrvTh3Jo8VzQ/u+oRHVDiX5Hi78bhoEoPC7P9rJf59a5nEv8HWXrxe6Q94CTfD9kVhxk5I6dkELSdKynUprWqNb2gT7G9n8qj86wb3H5aszn2uC95GYNioSb+/h/hvV4J2+lGiAG16voRDkwP6rYQCeTlpoY1ngiyNtvBsGACnWYePy+TVBr4U++7jlOyBHNvtSWCTs/57IR3dZWX3K8Nqk7m0Q0/0tkiQNsu912uEULAqsfe+goIlc1j50un4K2SmnCHRftPp+4/KVBZl4ADHcbyAGfR7aCJ8GPFrAWd0YUG6etldXx8nK+jhmglTy37HuezK1Klpl7AZ8cxXrbom+KOFN5IPQRGqDBm2LbSyLdFgY9xqeYen90Aa2WQCdPzX5r4Y/kw8apQFhmtE22sCUWmasS88bQTltAAoXuNil7QzMjjG+aiLQ08la1/8bY1xm2ti7oZ00McaZpo34fnRfNKakrg/GGO+17z+KMX67QZvOiDEOLKSVOdT/IHKOMizIuf6H0KTZlqzgMQ2JC1fgHN2HBsEGYuNgFw21bO3/tyANV69l+8dojlcaQSgP6LJSS7OYF7gvmiN/SwtIqedYpPQ2HU3KzXFa0sWyg5wrHIgW/HsKeQ5EYtyE14uR9vr1zfri2vN9dDLH2vMc1NDIV4E/x4IyVAjhUKR8VxooxGldj4kWrMDS9kdXFe9DG4dU73DELOeEbD1wIKKRb0YXlMW0x2dRq327qIhDa2OfGOMg18ZJiNmnsd8a+HHsxHqgCQ77IFr2bbk7dh584roY46khhLei65Q0B15E1iF/cnN0HNrUeXx/CG2wnkO0/klknTAPuDzGeLObZ88h3YZS+mrQvrrxs/QByLtXp/gKBe3/snoblRdCOAjR00uh3prkR4keUh3IydLAsjpc2qFIWjPQ0yzwRGwQvMbm3nvQHfNe1NLsX5G2/1KXf3uo47HjohyvpPIazeWydxvx5+L8Owrxyz+U1dsMEi02+O+7Mcbvd1bGasHa3jl094OY07/IbjQ3QGKqJBpO/n8vtDzXoB3jRYgxpsAVyf/y78nmHqmO5Od7gX3+2t77FfCrkjZ5951JzF7jUN/asxAp0iS/vv+NTMwusDyH2f/eJ+9j1r8XqA02UBfgxLXhLvf9NqR52tulnYNO9d9Bp/z/QYtd0pZNgSsetTYeT21Al1Pt97ZIySqJqX5JIQhFoV1HkWMEp+AfSTntRbLbywPIIvY2pOzSYTh8DEU9A4l1/4EYj8frq0jMOxnzz95Jexa59oxC4reZjkaW2TOYTHO/tN9DyYFCxtrYXUo2iUrmTKe7tImInn6AmOFOiDHOQRsEkDLRnYiWZqBrmhS3/Z2IllJ995GDJIxzOExtXOjaeBMSe45A4vvrXf8Guf5tgE6zPwDeZ/XOMRxdQ5Y0nEo2JfyOPQ9a2qnkoDFL7f370ZXFICSGvoNaf/ZnkQN2+Dk6x8bK4/u/E77d+xci6Zqnh5sQPaRAHge4/F7cfrt9fs6N1WLD109cn+t4kKXvha4dUtCSE9H1xbOd1JvKG1IobzRZ6neVjech1sfbCnV0UIhxTb0Dm0QPix0Ob7Ax8Tj0Vxxp7o00/P0PmWaPQPPzJXIwphmItqe48XsB47HUzuU2pOXfuzD2s6jnzxcUcJv6Ms768iziTYsQ3y3l7fZuUjJspwktlvH3blvX1uai+lo8huytjACSpvMccqD15P93NNq9D3dE/ywyv0hO6re3wbqLWq3RRWhRXEz25rUMiZ2nYr5z7ZmPaVyiyb4YmdmMQ+LvCViQBGv7ZmS/vhsgm8FZ6PTVTr47/znZ1/AzSAHDBxvYD03yMWQt1rFIMWu2w1eyr01a78ehxSkxh82s7IFIZOi1S5ehSfc4WfM53aFegxhi8uZ1AVqQnjGcn2/t/U9yFKtFNkn6F8Z0DNnnd5mW9DC0SRiKrg2S5mrSBn8MMfGE14TnidT6Z59qbU1j96rV5TVmU2CP8WQaSf6sp1CgOatnLllbt6fVkbSu28la1yltPIXgGFb3WLKv8jZqtcfHkyMpdeD0Duz/DiTaHu5wOIVsJZHaOMJwNMracLe18WAbu9S/tCk4lxyAJQUAeZlsUfAcBZGotX0ra3MKGtOG9BGeMrz1R0z+A+ge/i5r2yJr09cS/h1uOjy+Lf1ItGD8FW1SZyOdED/POgzvXsv9uERfnre4BSSN1TgkQl/o+jyOeh70qOH7dnLQkg4kqm/rrF4r73pX3m9xehtkq4hEu4vc5xhEt0vINFLUhL/D8JG04RM9pE3DPPKmzbctzb3x2Nxz/91tuHm2QMNp8+bnz1aGj1TeOeTIeglfyT/+8MLYfwvNVY/b0bAydsJc7PCG7quXu3e3wlkBOfpM7qATLa4wvCw0PKVnAVLArBbu1epg/S5ye7J95FR0R9bP0voaEbT5d3FO6W3QP4oW2MPs+RBa7BaR7z+XoZNOv8Izmhw8YjDZBCMx673RRJ/o6k8M4mqkTDEdMTTv5rSNWtOvZDKTTCqWo9OEDz6yiKyEVGP6gBhYMl1ZhkwpjjLCfpJsrpTKH4JObQ8gbfDULm+e8lQRr/Z5IGL0C21MUhSrF9Hd/H3UhnIchTPBQMzuFTRhh2MB7x3e/GLeTl7M2xu0pydiTHdZG9LYTULXJ88X8J6CkQwvlJfK3x6dch4nmyRtSg5QMAYnMXBtHupw+wlqGWQPK+9Z+z2QbHazh/V3B0Qns6mfB2mcn3E4XIQYZGJum5IDQ4yx32WBLLYnS1+mUh6AxQfkmUSt6VAbunec4MagB6LHl4B3WtpEZAN9JVkUO9K+X4mulTyNtCPN6dSXS5CiUdqcXorov93j1+Gmw+FmLLobbyNL5Oahk3WfBuOX+vwKLgiRo4cnDF+7oDn1fIFu0vid48o9BB0SjirwtHMQrb7o6OHdaLEZgOZFP7RQ97M6n3d1JH8Jh7lnIlqkUnS9NP597d20afgX4ol9yXOvjGbHIWW0J4r82f5L82c4psDoyisL8jLV4doHDRnpykp5ZzhePtfheAMUOyK96zc5/nke8clEi8to4FGTguJjt6xr3V3B2n484bi0N6OF6wmy/9/Z6DRwhCP6p9Dd4jCyJutdaAEbXlJucmbxdbRAHtIgzx/t+1Ajqu19W8mOQxbY7+QLfATZr++GaBJORif8uWRf3B1ku82kQT4Knbx9pKY0aaZSEv3M5fsvxCymW51nGG4OQKL7ldqliOHOtDIORIz3+2jS/xzt7tuRacc/C7gZgUlC7Hdiqt+2uk9BJ/OXcaI6y/ucTbiIGM4OiAEk5p4YwBPk027Ca3vCqyvv94hJblbAQ7s9p9gzzX7/l6ORtGB4ZvITpLE8HC0Yg8ha217rernhbLlL2wUpzSyjVov+NnKYxyesvCmY9YANXo65AAAfLUlEQVTVu7mN73LENJPG9zgbI6/QdRlajFa4Nj6MGPMT5DjR7eie21syJHrr59JmIOmG1wQ+zdo4zMr6to3bPHKcYx8L+Wnr+2/svaKv8qdSfmr9LfzM6GSY68tMJBb9Ldlm+Al0BzvK0cNgpDDn6WEs2pQuJkvklqONSNKc38FwsxG1WvPtSCx+oUsb7fGFFqW5iO6834cnMXeuZKlRwuv5BVz0MVx5a5KXrP59Xd9SNMLEh7awMS7aryeaXeBw+HzCoeXZHm0YXkX0mebeLuhQlGh2gvVhOLXi+eFo7txHnj+TydcOqbzRhqMOh6/5Ng4d1PrHH0Pt3Ott5SRvmZeSnejcA1zv8s4i+1rwzy6IfhItzsd4awmP/0m3r2vdXcHafiiIWQv/ef+/H0C7cU/0z+GYoHtvpf/lkjIDMte4ocH/iTEvQJP9RMQkipP936h3dv80tX59e9pkmmEEl8TZh+A0si3t49bHT7m0tHB7LdaHkQRhYOH9va2Mvex3nZmdpW+LNEd3xAK6IEWgKeTT/SIKZhj27lNkprKfteXtaLGeg3QHzkeLf6da0mQGMJXMADbGMQDLtwcNfKyX1JHak4KRXALsU6S5MhpBij0pRrYPFFI0WSvz476lvV+nRU+2Hjg5jUMJXn5Krcb3zcCZJXkPwRYY18ZL0Gnzg65/PagNNHEDBf/2SIpyJs6cyNK3srZ+zZ4r0B3lafakQDvbk0+pH0XOM9JJLi2yO1v/iie5ZDbp8f082nT2sPeGpD5QuwnZF2063+HSxib6ol560VHoc1Frvo4HoU3AOwtp+6FrMx+0pN3Vm6RG/SmIoRvQw/4UToWWvntnc6cJzU6nhGbt/36F35uh64O+9pQFY5qAaLMYjKlm/hi+3gPs6tJ2RdcFywvvPoo8Jfq0DZH0cLmj828W+4IkOuc2wGva6HwUJzFaG89aq/g176juMtLdbp2IAxhgnw2J3udrob5duti+lZOdxsFO/kxJ8A8ccwT260KdDU0sGuTfFmnN7oMWv66a2TUzw9iGTjYDneBm6y60YzPPAFx671bKK+TbphX6apUOC3m3MnocQIMADYX8u6NNaEOFv2b1NPhvQIv5Wsb/qjyub0ciXYlkwz/Bvicb/i1s7m5VUsZ/km2+p5Btvrd1TLkUh2ijc4Z9H0i2n98D59mtC/1pKWgJWWy8Ugzt/msYlMf15dPN6KETfNXxOgrRx1roZ1IO2xUpqLZsPkctv9mjFXy1ilvf72Z03QktHog2jMnD5Em0YBK6RubDa1HJ2nzQPfMQajVqpyFxyNfIGtCz0nf37vGF5wR0YrwPaTkmrdGDyffmBxljiFiwj7LBJDPwLxkzeZTshvFZJIo5wvK+HTGpSegUmRa0/QrP/ta345Ao7U60S74WiYaGAm+zdw8xYjuqE/ztiu7PBqM7sCVIIjEF7Xb7oAX8DHQC/QKm2erK6IPEi4nAf9Sgz9PQVUVaDD9sfS7mS9caHt9TkWhtltW1lat/aEm//OL7Hfuc0gjXhfa86tqT6k3+8O9DEpAhlidpSS+w51mXL7mxbEMi4+R97Tok8VlOllK8gk61Xov4QYerTyNRXnKB+9/k0K2DqZfApHpecfWkBfATZHqfjZQRF7p8My2vx/+zhov3OrqpY9TomupP9u63qRWL3+6+P4g2c8dY38a7vn3Z8vRFm9mEg6OtffdZG6eVtHE65su6AQ7H2/gmCU9wNHwttRK55TbWn035Gsyh/7TPYxw91I2Lw81jjh4mI2nRQvtMyoc1UiPXlzGFvqxAVwZ/QIeDGxrgazYSIRctQn5iT0qbSYFPNuhz0rifggsig2j+dLKeQAdZTyDh5iWyNU/iN5MM/96xTbJa+Ggz/FveGxA99bZ+T7exS2a0SSL4PWppcnd0jfK+Al4fQvP+EbJ1xG+NPk7t9nWtuytY248RxkGFtKVoMZhD1n6OSJT2CHlSL0Ua5de4fCuQEs4sstboaORA4r1kf8Ijkd/uF8harCcjcY/fSCxAE3KUEWsSS40hi7LvBD5s3w8EBtv3FUjs9AS1Cmfz0E79k0b8J6NF+z9sYqS7sr8j8dv5DjeeeaYJN9vaeDrZx/AodCVwC9mk7lOGq2tcGcn855+OwJNnqu8bblKf30btvWKH4e29hXwjDD8e349ae4Yg8e5ostjdK8ikzcNc930a5os94drSL7P+p3zTra8vpfZYG08qtLuN7KM7aUl3INHc/S7fvVZeijQ3GF0P9Eci0uOtDcPRne3D1GoR+zvdYWSFnM2MBj6HxMLHUe/h6QGr5yxXz1J0gn2aTO/LkF7HNS7fk8g/9e0O/7eTA/ckuhlofTu90OfPW/tTn/uWjFNSfLvI+tbX9S1pbv/K6v8WukMeTDanbLN8K2nE0j9IViTbFtHh3g6HyQf5edRqhifa8xK5Z9DG+7FivgKu21xfEj3UjYvDzYxOcHM8mtOfp/ZgMQVTWHV9GUlehF9EtHsyWjg9vtJ9uOd1EW3Gxru0lxEvmEneXKT5MZLyOZU07kejA4u33BmHmas53AxBc/l+jN9YGz8L3OLwkKwWFjfDv+VNCodTrD2DEf1vgzZHl6Hrh8muvrRIz7G+fZlaGtmB+lgYW1HQw+iWdW1tL6zd3sFyD1kHGFF4M6glaEf8B/JC+220GH7B5fOmQHVao2Qt8ZWa6TZJTjTiXIacTRQn9Xuo1cBuIytiJKW1tIttR8xxFvlkcbr9N4naSf5MoYw28l3ZfMQkFmL2y4V304QbjjNHsjLSzn4sZlLn3kv5DkGL/nEF/HvzH+/esWiSMo9sL7nI5Wt3uBlbqDPh83C0abrc8JMYylLEIF9BDONCtGG70OpLeHoV2XvOaJAvabQmszR/z5na8Ixr5wQ/Dv4dN0afsnp3c2U85b4nBbCkRbyQrIn8ILWasosKOPf1HoIYnddMTsqG92MeA4v07vKlep52+Pf0NRi7iqBgxoYFqnG/P4Vtsqjd/MzBPAda3zax7+ejzen59u40G5MOxHS9wmFSAEttTHa/i8l2vy+ijeVnUj1kbf/R5DnehtMM9+Nc4AVl+V4sGXO/wPmN4dfIwXwa4WYpOn0OLDwvIn/oK3FW6MumaCG+w/LOdvg6AM01z+umGz34tEVow/BO8uais7kytDAO3jKhLhgTeS57mko4mkX55sDj/0V0KPqqe9JGYw7a5HuaHE22eBlFnmdpkW63MRjh8Doe8bCVuhH2Th9K1pw1/az1hbXbO6hd+Z3UatSeZGkPk7Wf/YLsF9oXEbOqy+fyD8e0Rsn+hBPRFf0JP4vitabf3g3jYrIbxoVW9yDMl7gvk7yo9sZMYYx4J1Kr5PZF18atMOcjbgL1QAtMsl+ejxSENidPuNuQ6HU82cfw3ej0Mo5sUjeUbFKXTvXJUcT5hT4nacQI1+fJiJn0R+YobdaeKw1vKd8UsovKY13/+lCrNb/YcOgX6SnotOdNh+aR7fETrgejU9WokrGa59r9e+vn02T6mo8WiBGYljSZDqe4fFPRadZrdreRQ4R+2XDbjq4jihrV/W1MkgvcpYbrKdaGpG09lHyCTePyrL37o1SP/d/DxiDR+ytoAUnKXrcaroO9n/Df5mgz0U3agKXN2CAklvwbtU5UktOXV12+RegEmPwbJPe+C3GuPskuUD+LmPKtiH7noLjpuDYmu9+xZJvh/vZ7pqtnBgU3wvZ+UTO8zGLlDkQnT7u+rEDzcqKjh7TYzSLT5mxL87R5JJqf3sTyKcpdivY3GvAukWv64vB1NqLHhK9r0dz+ihv7iUYPPq24kfuU0cjHqN1cJCXcFWSN+5uRPs4IsuXObHRlkySYPcn8ZiKZ36Rrx385fKWNwrxCm1Jchgvd82e0mXgFSbmS1OrPaHOS6L+d7BMiLdL90eI+2+H1NitrMNk6IonKT+/2de21XkjXxoNEn6U+lMnaz3ULsv3fxwg75ZtXkmcAzmzI0r5OiT9h6jcSx5LDEl5DdlDyOBLVHGZPb8TUt7NJV3SE/7QR2my0uBQd/E8mM/SkYd1GrYlFT5twSwsTbkskqn2J7Jf8zWjj0042qVtgv48gn+pPIwc0SAR+vbXjAcQ8U5/vRBrM96Id/ZutzisL+YYB7yr07xQkEvRMfTC6//pfl7YnOgX6k37C8bEO13si0f3ZLt+bkYj42kJ7hqK7yURfDyCGcxq1WtKnGM5TvsdK6GNnZKKSglXsgBhHX1zoyQJ9Jv/Z96I76vML9Y4ka2encdkZMe1XUz32f1/DY6L35+xzlGvPAHQf6UNhLrfxf5VMN23IeuBZsuOKl5C04DD3bpuN/ZPUOlv5CNLSvozsG3wi9drLuxuNLDC8XomYdXFOtmFzktoTVx+0iUr1PEwLSlSU+OEnO+vo7/oyD22QfpTGBdHmUdSezM+zd4oBUN4F3Ot+v5+CRUaBlr0/9TuLfTF8/QRpsCd8He3+X2kRUpK2hELMA3SFNhG3uXD/+fgGfYweUvCmpYhfPY2u0BJutkQe1yaQ+c1g61tdHIQSfA2mECjJ9fsl63fSMZlMLf0PIF/j+Q3jg2i+eFo8kFrriJMpUfLrjmetL6rrykNhd93NdTXcSHTyXtGULBHbRmgXG+iadmTyGFamYV1kenUmSpbuTeomIPveGg1Ym4yTWiVwtCistN1dDTzvSWMt9KYa3evqQxc1YO2dVdZMXs229kA2ukNxTlQa5DsP27A1ymfpHyK7wb3Knn9YWp3FReFdb/Pt7X5rbO7XQJ877cv6SpvWt8NK0ms2F4X/amiWTix3GpTRMr5WF7esYjAZutmyoqautU0Ia/PBORlpltaFd49Zw3XUlVf2PuV2v43ePcZ9T1FziqfzDd333kikVUqU1Dpq8VGDmmrAttJnmthLtoqbNTCmraa1OvZdzkfWAPea3XUasE3GZTISBbc0LqvblxJG3dJGDJ24Wsl3FtIJOcGe92Ca9s3ah6QMG5bMn1K/DK32eTX70mp5q5WvFTpek3OKcquFMq3tZmaXLdHh6uCrAZ10+i7Zkuh5GlhWdOfTgzc2hFbSSgK1N3r3gFWto0E9ZeXVvR9jnBdjfLzFd1emxxjH29eVkXRCCKcDs0II40MIH0Yn+Z8Aw0MIn3T5Dg4hjAW+F0I4KIRwLxJ99QROiTG+JcY4I4SQzGoutchanYFv352xQYS1Jv1b02PaalqrY78q+W5A1yg/Q6ZatyJJx4ZIpFgGK8uMMe4C/C7GuGsaF/trBdJsXu02hhB2DCFch5QB/wWMCiFMCSF8D0Vk+gQ6Jd/QoL0Ab2kxHzHGITHGW+0ZEmNc3lk/YoxTYozLin2JMU6PMd5X8n6r41cGrfalrrwGtNlqvaszL1Z3Th3jfiaaPY9MswMxmg0hvD2EMB54KoQw2SKbFaElOuwKvlrM28q7lyF9gevRdcRFMcbdkPTxZ2Xvr1Ho7p3BuvaQ/WAnhZVkTzgIsycseecs926d7TNw3arWgcTcpyIllLPQPehvkE3l1l1o41VlbXH/D6NWyzI9K7VYLd9IdAec7Cl3QzvKpFWZ2pLcMx5JrbnNfsBjrrxkstGZyUxpu93/f2uUr2xcGo1VkzE9FeklXI7uVT9P7amxK2P/VaTIlaJzvd3SPtLV8iytqImdNGAPIgcZKaWRZnhFd3Sr3UbLN4GsAJXMxnqhID1XdTK2Tce+lfFcFRppMH8OQYqiP8VO4eQ5eTYNJByd9aUzXJfRZqu46aTPnfKhVvHVAg4vcvnKrBZWWkfQwMS1kznVdC63SO9J16OM3jvjQZ5nrPQXj2nLu3xtzcpZE88bIR730Bjjgfb9s2jy7YgYzSDgLUiccwtSqto3xni8xYD9I3ILeY97dxPkjnQmulcLSInmTqtyUKt1WJvuQcpCiy1/b6Sx+CukeXtaCOGqBm28w3W1D1poD0eKTaC7RayNxyAt4Ijc+nk4L8a4pbWnI8b4zhDCDmiB2DGEMBrz3Yy0ll+xPv/B0t8WY3ybw3lbjHG/ku87o/vtZP+ZfJ8Ha/cDADHGAZbf929jdK9/ODrZPxJjHODGZRukSDUIKcKdbf3fB9kYX46Uts5B96I/Qjvms5G4673kON/t6CQ6D5nJvZWujf0ctGufj3bkByHPTxORNv7sJuV9GIsBb+1JaSMsfRByoXmCjUvPGOMeRiNHIKWubRA9PFmGV8PthVbuhkjM15U2lvV5eyQqHBRj/HEI4akY4/5W19Mxxr1KxhQaj33ZvP0LUugaFGP8cUl5ndFI2ftDY4wHhhD2R5vOs9E99Q6G7yfJc/IIa+PpXexLGa4fRH4VXkTzcrmVPx2ZjDYrr1G9ZX0u8qFGNNLqnLoDzeGHY4xnhhBOQZu076N5dbrl29z6dIvV1x9ZweyPNvMLY4zvcn05DGmCN6Kvsrl8FtL3mWA4a4SvQ5DyWz903XQv0m5/EfHe2Yi2D0c87uUY40dcTPMynrGS3pH52O0rByOEUTHGf6c7obt3Bmv7oTzk3FhyhKi0C0wmLB2UOPN377ahhW8iWWt0KVkzuWEdqR6yFvdnkdnLhVbPArJXrLHkCFylvpEp12CdgRjBPYX0JVbfYSU4KtpSX4JOGEk7erK18W6Hr+EOX8cWyhtVhn+X1mb1DCy0+zDqtY3L+jch5aM86ldKG40UYUaSHT6MJzt8SPlGIkaTzIUeIkd38pHFWh37VN4oakOHbooW4M7KuweZ4KS0WYjRT6RWA3Y8ptltZXl8TWiEV8s/Etn3+nCWXWljsc/3IVvosdSal9WYsTUZ0+LY181b+14MFdkyjTR4v4w/jCDTko8BEKg1tWy1L2W4Pofs4S3FuE+xqc/tpLyuzIsaPkRjGml1Tv0BLcYvoU3pXxB/uNaehlYL5Ih7w8hml6k9k2hOX2VzeRxSvHy4gIexri+Nwvl2WL1HoQU4vTsJ+IC924xnDEAbmxp/8ZRYEnXLuvZaLJ5r86FEoxbzO2yEORApX7WTwyGmwRmOFFfGuHfLwg0ubqUOSx+D+Ta2esYicfmb0A41icdvJTvXSG3sg8yRFpED0c8yYnu/5U22l0XN1qm0oGlpk+O/bFL0Rso/KYTfDq4tA9AOeFihrBrCpdxkplTz1uq+BDGEUwr5bnL5ysa0LBRgmcOHlG8ktSEDU/jJFLa0zO691bH34UTbm9RbVt7EMtw0GLei/+wD7N3HyHbbjd4tiyvdahvL+rwzMhdaRIl5WWdj38q8dfQ5cxVppA/wY7JL0xTV6jJ0Gkz5RpEtNRaQ5+QmOLFoF/pShuu0mKeY4Q9ZeRcV6aEL86cVXldKIw3eLZtT6TDRjm1qXL7RNLFaoDZk6GGIv/RAi+lYmtNX2VxOeFhQwEPZZsxvQtqpxeE4964f34Y8o6x/r+Wz1hfWbu9g9vU7iWy/3Acxl8Vke8LFRsyHOmJJ764ML2fpvY1Ik9boshbrmIjE2IckojTimYhEUtPQAvm/Vn47tb6Rk4e2D7j+bY9sHZMDiSnuv6bavNT7Ok/P/tQ6fCjz0zyRkshpXRybmvahzcqPkT31HfZ7Y8s31+UrG9PJ1IcCvBndVXeQNxyTyf7FU76vIGb9Ijls6WR7Xl2FsX8CMYsOsmequvY1KG9KK2PnxuW+knF5HJ3am737BGbytwptrOuzy9eq9UBntFk3xpZ+O1owVoVG7kaLhJcITSU76Un5zrP3lqCTcZqTI3EOWLrQlzJcjyRLNLaidnPydLPymsyfsj434kM1NNLg3Tp6QPMkLWILkPlnyrekFXqgXFvc96VsTtXNZXtvD0vzeCjbhNSF87X0txXopi6YDCU8o5P+taT5vlrrWndXsK4+NojvINsTtmzKhLN9prnJUrGO7RpMkB2Rc4AOZNr1cXIc7RrfyE36M65RW5qkLyd7eXqw8CwqyX8OLdhftkq4aQKTQzYW8XwB2kz1RQyuaTg9CjbpiGldjzZFTTcc1qcv0om9ZitjjxaSOvt4SkKHdlZeC32+iAZ2sZ3QZmm0sVVpYyP8F8e5wTtdCpGImLIf45ZpxOZIozaOK/x+CzmYT82c7GpfynCNNoujkdj5afJisS05tn1LuGlxXtTwoS6+6/GdNjXT6GRT0wTXF5Wkfa4THHY6l8l8ZDL1PLYunK+nd/duy4eUJv07q5i2pp9uLfz18DQanLVRD9ohf7Mw8bZDDgLuW4U6RyHFqzpCo+CNyNJaIsgu5Luo8Hss9bGpTzcG99xq4LbLDh/W9YcWtY3XhaeMUa9GWatMI2t6/qyBvuyNi3G/vjzooLGjfW+4qWEVNek7qXuV53JXeHln9SAFwy3se6dWP2v6ed1rlb+eIISwFVKU+xjS9AWJDe8AfhxjnNuFsg5BmpUPxxivKfn/2Bjj7ZbvQCRevKeT8jrNZ3mvizGeWpL+U+CeWLCpDSF8CPh1jPGtrfTt9Qatai+vbQghHAjEGOOwEMLbkZezp2OMf1+DdawyjazJ+VNBc2iiSf9BFGTp4q7wjHUNkqVNjHFZI6ufbq2/WrhfHxBCOCPGOLDJ/62a1yTzmDPQpGuar4Xy1sii01n/Xs8QQmhDSo1XI3O+gDS9TwaIMf5z7bVO0Aqjfg3asMo08kamr+6AEMJIFG9gY6R/sxPSxzgMiaB/TQOesT5ACGFsNBNYb/JqvztijO/s1gZ095G+el6bh058etO6eU3Sep3SSr4WymvJZGZ1+/d6fuiCL++12MY6kydL35RCzOJubMPq+LV/w9JXN41FmSZ9+uxoxjPWh4cSJTb7vgcFS5vueDbs6kJfwdqDEMKIRn+hu7pm0MNEhT2QpOUFV97u7vtbTQy0HYpX/gJAjHFhCGFZs/Ia5Hs3UsS5APhGjLEjhLAolpwSV7N/r1uIMa4ALgsh3Gyfs2Cdm7vLotyOvhJCeDbG+BJAjHFRCGHFmqpkdWikoq/XFJaEEDaLMb6C7olBPKMfwncznrE+wJnA5SGE7yBHPY+HEKYi7fMzu7vydW3yV9ActgOORuYLHgJy4tAM+iC3gwGI5hltO2RWczXy4gQKMr85Oj1tHULYIcrneG9q/QTXlVeWr4uLzur073UPMcZpwCdCCB9Fp9p1CcoYNSGEPsgn+pqC1aGRir5eOzg0xrgYVvIAEM/4J5r/S5rwlnUeYozzgdNDCFsgHwAbAtNijLNei/qrhXv9gr+hSF4dxT9CCA81ezEq0ETxnb8h0eYxMcbnLPnN9t8fY4ynuOw1ASnKyivL5/K3suiscv/eSBBjvJPsEnJdgTJGDXJte9oarGd1aKSir9cIEi0U0nZpkL1RsJt1HkyyNPy1rrdSTqugggoqqKCC9Qje6GE9K6igggoqqGC9gmrhrqCCCiqooIL1CKqFu4IK1gEIISwPIXSEEEaFEG4OIWy2GmVdG0L4uH2/2pyhNMrbP4TwvlWoY3IIYZtC2sAQwlmFtGNDCHe10tYKKqigNagW7goqWDdgUYzxnVFxfJeggAorIYSwSoqkMcYzY4xjmmTpD3R54W4AK53CODiZ+vjvFVRQwWpAtXBXUMG6B48g2/r+IYRHzPvcmBDCBiGES0MIw0III9LpNgh+E0IYF0K4j+zOkxDCQyGEd9v3D4UQ2kIIw0MI94cQdkEbhPPstP/+EMK2IYRbrY5hIYSD7d2+IYR7QgijQwhXU26+cz+wl5kaEkLoBRwJ3B5C+K6VNyqEcFUIoe59f4oPIbw7aXqHEHqFEK4JIQwNIbSHED62RrBcQQXrKVQLdwUVrENgJ+sPI09koDCrX4kx7gF8BpgfYzwAxVX+bAhhV2RKsycK5HAqJSfoEMK2KIrTCTHGfYFPxBgnA78FLrPT/iPA5fb7ABSL/Wor4kLg0Rjj3shN5c7FOswBy63AiZb0H8BDZjLzmxjjASZR2BQ4pgtouQB4IMrF7uHApbYpqKCCNyRUdtwVVLBuwKYhhGRf/Ajwe7QAD40xTrL0o4B93J1wHxTd7VDgRls4nw8hPFBS/ntQQJlJADHGOQ3acSTwdncg3sIcZBwKHG/v3hlCaBSQ40bgZ2gDcDIKxQhweAjhm8hvwNYomtegBmUU4ShgQAjh6/Z7E7RxGNvi+xVU8LqCauGuoIJ1AxbFQmACWzwX+iTgyzHGuwv5PrIG29EDeE+M8dWStrQCg4EdQgj7oo3HySGETYArkD/nqSGE76HFtwjLyFJA/39AkoJxLfeiggpex1CJyiuoYP2Bu4EvhBB6AoQQ9jCR8cPASXYHvgMSJxdhCHCoidYJIWxt6QuQi9sE9wBfTj9CCGkz8TBwiqV9GNiqrIFRHp1uAv4PuMs2AGkR/ped3htpkU8mu0s9odDvL6d78RDCuxq8X0EFbwioFu4KKlh/4GoU3rMthDAK+B2Smv0FmGD/XQc8XnzRAjp8DrgthDAcLa4gcfVxSTkNOAd4tym/jSFrt1+EFv7RSGQ+pUk7bwT2tU9ijPPQ/footAgPa/DeRShww5PAcpf+A+Q6dYTV/4MmdVdQweseKpenFVRQQQUVVLAeQXXirqCCCiqooIL1CKqFu4IKKqigggrWI6gW7goqqKCCCipYj6BauCuooIIKKqhgPYJq4a6gggoqqKCC9QiqhbuCCiqooIIK1iOoFu4KKqigggoqWI+gWrgrqKCCCiqoYD2C/w95OhVr+JSocgAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 576x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7mfhOlkm9Ntu","executionInfo":{"status":"ok","timestamp":1625477774799,"user_tz":-330,"elapsed":18,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"eec7a4e4-b801-434b-ca8e-d8f89512119d"},"source":["expected"],"execution_count":100,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 4.59000015,  4.86999989,  4.42999983,  5.65999985,  4.38000011,\n","        4.28999996,  6.48999977,  4.96000004,  9.27999973,  7.21999979,\n","       10.06999969,  3.93000007,  4.67000008,  4.6500001 , 12.97000027,\n","        5.05000019,  8.81000042,  5.36000013,  5.78000021,  4.30999994,\n","        6.3499999 , 16.11000061,  4.13999987,  5.38000011,  4.80999994,\n","        6.78000021,  5.28000021, 10.09000015,  4.96000004,  3.41000009,\n","        5.09000015,  4.84000015,  4.30999994,  4.82999992,  4.23999977,\n","        4.67999983,  5.19999981,  4.19999981,  5.51999998,  4.94999981,\n","        5.03000021,  4.82999992,  4.9000001 ,  4.30999994,  4.05000019,\n","        3.02999997,  4.17999983,  6.48000002, 11.59000015,  3.83999991,\n","        4.03999996, 12.73999977,  4.84000015,  6.13999987,  5.53000021,\n","        3.61999989,  5.19999981,  4.38999987,  7.90999985,  4.40999985,\n","        4.98000002,  4.4000001 ,  5.11000013,  4.86999989,  3.79999995,\n","        4.84000015,  4.38999987,  9.77000046,  4.46999979,  4.30999994,\n","        5.73999977,  4.42999983,  5.46999979,  7.4000001 ,  4.80999994,\n","        4.80999994,  4.40999985,  5.01999998,  7.51000023,  5.11999989,\n","        9.36999989])"]},"metadata":{"tags":[]},"execution_count":100}]},{"cell_type":"markdown","metadata":{"id":"F45ifwjCOujT"},"source":["## Elastic Net"]},{"cell_type":"markdown","metadata":{"id":"eK7CRvfiwUok"},"source":["### DBSCAN outlier detector ( didnt work)\n"]},{"cell_type":"code","metadata":{"id":"veGv1QnYwTTm","executionInfo":{"status":"ok","timestamp":1625477774800,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["from sklearn.cluster import DBSCAN\n","from sklearn.preprocessing import StandardScaler"],"execution_count":101,"outputs":[]},{"cell_type":"code","metadata":{"id":"NfRodBDBwheG","executionInfo":{"status":"ok","timestamp":1625477774800,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dbscan_dataset = dataset[[\"stab.glu\"]]\n","dbscan_dataset = StandardScaler().fit_transform(dbscan_dataset)"],"execution_count":102,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5n8Ma_9JxNtC","executionInfo":{"status":"ok","timestamp":1625477774801,"user_tz":-330,"elapsed":17,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"ce61b364-3732-4fc4-9ef6-5a07c6700103"},"source":["db = DBSCAN(eps=32, min_samples=5).fit(dbscan_dataset)\n","core_samples_mask = np.zeros_like(db.labels_, dtype=bool)\n","core_samples_mask[db.core_sample_indices_] = True\n","labels = db.labels_\n","\n","n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n","n_noise_ = list(labels).count(-1)\n","\n","print('Estimated number of clusters: %d' % n_clusters_)\n","print('Estimated number of noise points: %d' % n_noise_)"],"execution_count":103,"outputs":[{"output_type":"stream","text":["Estimated number of clusters: 1\n","Estimated number of noise points: 0\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BC2MnAoz_R58","executionInfo":{"status":"ok","timestamp":1625477774801,"user_tz":-330,"elapsed":15,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"42afb4e8-dd7c-4950-ced2-6cf02e323ba8"},"source":["dataset[\"stab.glu\"].head()"],"execution_count":104,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0   -0.498023\n","1   -0.123024\n","2   -0.244575\n","3   -0.220006\n","4   -0.294119\n","Name: stab.glu, dtype: float64"]},"metadata":{"tags":[]},"execution_count":104}]},{"cell_type":"code","metadata":{"id":"JB38Mm4a2rnC","executionInfo":{"status":"ok","timestamp":1625477774801,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset[\"labels\"]=db.labels_"],"execution_count":105,"outputs":[]},{"cell_type":"code","metadata":{"id":"vRc_dN2_CT2W","executionInfo":{"status":"ok","timestamp":1625477774802,"user_tz":-330,"elapsed":13,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset = dataset[dataset.labels != -1]"],"execution_count":106,"outputs":[]},{"cell_type":"code","metadata":{"id":"oLrdJGcvCY-g","executionInfo":{"status":"ok","timestamp":1625477774802,"user_tz":-330,"elapsed":13,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset.drop(columns=[\"labels\"],inplace=True)"],"execution_count":107,"outputs":[]},{"cell_type":"code","metadata":{"id":"KyORftmPOgCb","executionInfo":{"status":"ok","timestamp":1625477774803,"user_tz":-330,"elapsed":13,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":[""],"execution_count":107,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"HWy-qu28OtuV","executionInfo":{"status":"ok","timestamp":1625477795943,"user_tz":-330,"elapsed":21153,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"74d41b71-2b01-4f91-b3d2-46ac90deca62"},"source":["# Elastic Net\n","from numpy import arange\n","from sklearn.linear_model import ElasticNet\n","elasticNet_reg = ElasticNet()\n","params_elastic = {'alpha':[1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 0.0, 1.0, 10.0, 100.0] , \"l1_ratio\": arange(0, 1, 0.01)}\n","elasticNet_GS = GridSearchCV(elasticNet_reg, param_grid=params_elastic, n_jobs=-1)\n","elasticNet_GS.fit(x_train,y_train)\n","print(elasticNet_GS.best_params_)\n","elastic_best_model = elasticNet_GS.best_estimator_\n","elastic_best_model.fit(x_train,y_train)"],"execution_count":108,"outputs":[{"output_type":"stream","text":["{'alpha': 0.1, 'l1_ratio': 0.87}\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["ElasticNet(alpha=0.1, copy_X=True, fit_intercept=True, l1_ratio=0.87,\n","           max_iter=1000, normalize=False, positive=False, precompute=False,\n","           random_state=None, selection='cyclic', tol=0.0001, warm_start=False)"]},"metadata":{"tags":[]},"execution_count":108}]},{"cell_type":"code","metadata":{"id":"aa7CPEmBPnGS","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477795943,"user_tz":-330,"elapsed":14,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"6feb0056-23b4-4f69-8d1e-b173b59614d0"},"source":["y_elastic_pred= elastic_best_model.predict(x_test)\n","print(metrics(y_test,y_elastic_pred))"],"execution_count":109,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7971281815865165 |\n","|     MSE      | 1.0945577863746094 |\n","|     MAE      | 0.7784078975580234 |\n","|     RMSE     | 1.046211157641998  |\n","|     MAD      | 1.1846899174892236 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"KbD-okRpZghk","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477795944,"user_tz":-330,"elapsed":12,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"a9a5f4c2-22c2-4b59-f175-95c3617e9dd2"},"source":["Ensemble_Weighted_average_prediction_2 = y_Ridge_GS_pred*0.25 + y_lasso_GS_pred*0.5 + y_elastic_pred *0.25\n","print(metrics(y_test,Ensemble_Weighted_average_prediction_2))"],"execution_count":110,"outputs":[{"output_type":"stream","text":["+--------------+--------------------+\n","| Error Metric |       Value        |\n","+--------------+--------------------+\n","|   r2_score   | 0.7994852045218843 |\n","|     MSE      | 1.0818409002800011 |\n","|     MAE      | 0.7650261458309053 |\n","|     RMSE     | 1.0401158109941417 |\n","|     MAD      | 1.2659342369487183 |\n","+--------------+--------------------+\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"TUZoQnscexPf","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477796808,"user_tz":-330,"elapsed":875,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"961cadfa-0400-4116-a1e8-caa209ced1b0"},"source":["# add every model's prediction into list\n","predictions = []\n","#predictions.append(y_Ridge_GS_pred)\n","predictions.append(y_rf)\n","predictions.append(y_lasso_GS_pred)\n","predictions.append(y_XGBReg_pred)\n","predictions.append(y_elastic_pred)\n","#starting Value\n","starting_values = [0.5]*len(predictions)\n","cons = ({'type':'eq','fun':lambda w: 1-sum(w)})\n","#our weights are bound between 0 and 1\n","bounds = [(0,1)]*len(predictions)\n","res = minimize(rmse_loss_func, starting_values, method='Powell', bounds=bounds, constraints=cons)\n"],"execution_count":111,"outputs":[{"output_type":"stream","text":["5.793921704669504 [0.5 0.5 0.5 0.5]\n","5.793921704669504 [0.5 0.5 0.5 0.5]\n","11.576753314743831 [1.5 0.5 0.5 0.5]\n","3.8731186056400277 [-1.118034  0.5       0.5       0.5     ]\n","1.4306215031977847 [-0.64715025  0.5         0.5         0.5       ]\n","1.4306215031977847 [-0.64715025  0.5         0.5         0.5       ]\n","1.878702101415088 [-0.20897786  0.5         0.5         0.5       ]\n","2.283827660312799 [-0.82701183  0.5         0.5         0.5       ]\n","1.0360681896271378 [-0.48286608  0.5         0.5         0.5       ]\n","1.0369520789076683 [-0.46896065  0.5         0.5         0.5       ]\n","1.0392642405322532 [-0.49269474  0.5         0.5         0.5       ]\n","1.0360681896271378 [-0.48286608  0.5         0.5         0.5       ]\n","5.970400790204453 [-0.48286608  1.5         0.5         0.5       ]\n","9.623156384462133 [-0.48286608 -1.118034    0.5         0.5       ]\n","1.0360681896271378 [-0.48286608  0.5         0.5         0.5       ]\n","3.810477569725116 [-0.48286608 -0.11803397  0.5         0.5       ]\n","2.461827830616052 [-0.48286608  0.881966    0.5         0.5       ]\n","1.0617314191789429 [-0.48286608  0.46398295  0.5         0.5       ]\n","1.0382966786543952 [-0.48286608  0.51549101  0.5         0.5       ]\n","1.035867114122053 [-0.48286608  0.50341931  0.5         0.5       ]\n","1.0358670868860838 [-0.48286608  0.50346105  0.5         0.5       ]\n","1.0358671087095246 [-0.48286608  0.50349566  0.5         0.5       ]\n","1.0358670868860838 [-0.48286608  0.50346105  0.5         0.5       ]\n","5.9783316162551134 [-0.48286608  0.50346105  1.5         0.5       ]\n","9.570222138735001 [-0.48286608  0.50346105 -1.118034    0.5       ]\n","1.0358670868860838 [-0.48286608  0.50346105  0.5         0.5       ]\n","3.775858838569233 [-0.48286608  0.50346105 -0.11803397  0.5       ]\n","2.478819989296999 [-0.48286608  0.50346105  0.881966    0.5       ]\n","1.059977707800409 [-0.48286608  0.50346105  0.46094684  0.5       ]\n","1.0378301484659684 [-0.48286608  0.50346105  0.51004383  0.5       ]\n","1.0358555237834857 [-0.48286608  0.50346105  0.49911908  0.5       ]\n","1.0358554750381626 [-0.48286608  0.50346105  0.49916628  0.5       ]\n","1.0358554943919653 [-0.48286608  0.50346105  0.49917462  0.5       ]\n","1.0358554967181792 [-0.48286608  0.50346105  0.49915123  0.5       ]\n","1.0358554750381626 [-0.48286608  0.50346105  0.49916628  0.5       ]\n","6.0627956924006385 [-0.48286608  0.50346105  0.49916628  1.5       ]\n","9.72914188681842 [-0.48286608  0.50346105  0.49916628 -1.118034  ]\n","1.0358554750381626 [-0.48286608  0.50346105  0.49916628  0.5       ]\n","3.8394045203843725 [-0.48286608  0.50346105  0.49916628 -0.11803397]\n","2.5040723568560663 [-0.48286608  0.50346105  0.49916628  0.881966  ]\n","1.0616086766193693 [-0.48286608  0.50346105  0.49916628  0.46163901]\n","1.0381439888487418 [-0.48286608  0.50346105  0.49916628  0.51206761]\n","1.0358506973916433 [-0.48286608  0.50346105  0.49916628  0.50048005]\n","1.0358506567240442 [-0.48286608  0.50346105  0.49916628  0.50052892]\n","1.0358506571510673 [-0.48286608  0.50346105  0.49916628  0.50052363]\n","1.0358506572617974 [-0.48286608  0.50346105  0.49916628  0.50053421]\n","5.8151086319529846 [-1.46573216  0.50692211  0.49833257  0.50105784]\n","1.0358506567240442 [-0.48286608  0.50346105  0.49916628  0.50052892]\n","5.910454151450028 [0.51713392 0.50346105 0.49916628 0.50052892]\n","9.50007065538517 [-2.10090008  0.50346105  0.49916628  0.50052892]\n","1.0358506567240442 [-0.48286608  0.50346105  0.49916628  0.50052892]\n","3.7592239068971485 [-1.10090006  0.50346105  0.49916628  0.50052892]\n","2.4461402905190908 [-0.10090008  0.50346105  0.49916628  0.50052892]\n","1.0602158658039171 [-0.51983248  0.50346105  0.49916628  0.50052892]\n","1.0379261875066157 [-0.4696202   0.50346105  0.49916628  0.50052892]\n","1.0357950033514496 [-0.48106527  0.50346105  0.49916628  0.50052892]\n","1.0357949750878999 [-0.48102295  0.50346105  0.49916628  0.50052892]\n","1.0357949801716508 [-0.48104138  0.50346105  0.49916628  0.50052892]\n","1.0357949811505769 [-0.48100452  0.50346105  0.49916628  0.50052892]\n","1.0357949750878999 [-0.48102295  0.50346105  0.49916628  0.50052892]\n","5.999304671777026 [-0.48102295  1.50346105  0.49916628  0.50052892]\n","9.593949346778963 [-0.48102295 -1.11457295  0.49916628  0.50052892]\n","1.0357949750878999 [-0.48102295  0.50346105  0.49916628  0.50052892]\n","3.7821953412156706 [-0.48102295 -0.11457292  0.49916628  0.50052892]\n","2.4884524429623265 [-0.48102295  0.88542705  0.49916628  0.50052892]\n","1.0598434409719741 [-0.48102295  0.46386543  0.49916628  0.50052892]\n","1.0376950165797132 [-0.48102295  0.51268926  0.49916628  0.50052892]\n","1.035756315602897 [-0.48102295  0.50189464  0.49916628  0.50052892]\n","1.0357562754042393 [-0.48102295  0.50194277  0.49916628  0.50052892]\n","1.0357562788798165 [-0.48102295  0.50195795  0.49916628  0.50052892]\n","1.0357562796767228 [-0.48102295  0.50192759  0.49916628  0.50052892]\n","1.0357562754042393 [-0.48102295  0.50194277  0.49916628  0.50052892]\n","5.978362958420621 [-0.48102295  0.50194277  1.49916628  0.50052892]\n","9.570159068499246 [-0.48102295  0.50194277 -1.11886772  0.50052892]\n","1.0357562754042393 [-0.48102295  0.50194277  0.49916628  0.50052892]\n","3.7757788093002436 [-0.48102295  0.50194277 -0.11886769  0.50052892]\n"],"name":"stdout"},{"output_type":"stream","text":["/usr/local/lib/python3.7/dist-packages/scipy/optimize/_minimize.py:522: RuntimeWarning: Method Powell cannot handle constraints nor bounds.\n","  RuntimeWarning)\n"],"name":"stderr"},{"output_type":"stream","text":["2.4788205145262387 [-0.48102295  0.50194277  0.88113228  0.50052892]\n","1.0598684487708447 [-0.48102295  0.50194277  0.46010493  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0.34185727  0.4040508   0.56107752]\n","1.029797543550932 [-0.28598997  0.34182335  0.4040313   0.56109018]\n","1.0297975473799452 [-0.28596404  0.34180199  0.40401902  0.56109816]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"2MbOHYYAe6_l","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625477796809,"user_tz":-330,"elapsed":11,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"710c9427-d64b-4730-8fe1-94a93b1ef12d"},"source":["print('Ensamble Score: {best_score}'.format(best_score=res['fun']))\n","print('Best Weights: {weights}'.format(weights=res['x']))"],"execution_count":112,"outputs":[{"output_type":"stream","text":["Ensamble Score: 1.02979753839725\n","Best Weights: [-0.28597314  0.34180949  0.40402333  0.56109536]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"IxwFArsKWlZX","executionInfo":{"status":"ok","timestamp":1625483296276,"user_tz":-330,"elapsed":771,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["dataset_copy = dataset"],"execution_count":115,"outputs":[]},{"cell_type":"code","metadata":{"id":"oOiNiOcKWmuR","executionInfo":{"status":"ok","timestamp":1625484644812,"user_tz":-330,"elapsed":762,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}}},"source":["x_train,x_test,y_train,y_test = train_test_split(dataset_copy,y,test_size=0.2,random_state = 42, shuffle = True)"],"execution_count":148,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":225},"id":"diVAAqaZW9SW","executionInfo":{"status":"ok","timestamp":1625484645585,"user_tz":-330,"elapsed":4,"user":{"displayName":"Atharv Jairath","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GimYmfxjyVhkyags-cPXU89M7YrR7p8lIrOncB55kc=s64","userId":"02765993908853204784"}},"outputId":"310c6cee-585f-4d98-a89b-b102428c3188"},"source":["x_train.head()"],"execution_count":149,"outputs":[{"output_type":"execute_result","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>id</th>\n","      <th>chol</th>\n","      <th>stab.glu</th>\n","      <th>hdl</th>\n","      <th>ratio</th>\n","      <th>glyhb</th>\n","      <th>location</th>\n","      <th>age</th>\n","      <th>gender</th>\n","      <th>height</th>\n","      <th>weight</th>\n","      <th>frame</th>\n","      <th>bp.1s</th>\n","      <th>bp.1d</th>\n","      <th>bp.2s</th>\n","      <th>bp.2d</th>\n","      <th>waist</th>\n","      <th>hip</th>\n","      <th>time.ppn</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>353</th>\n","      <td>40501</td>\n","      <td>206.0</td>\n","      <td>83</td>\n","      <td>68.0</td>\n","      <td>3.0</td>\n","      <td>4.88</td>\n","      <td>Louisa</td>\n","      <td>52</td>\n","      <td>male</td>\n","      <td>69.0</td>\n","      <td>153.0</td>\n","      <td>small</td>\n","      <td>140.0</td>\n","      <td>98.0</td>\n","      <td>142.0</td>\n","      <td>102.0</td>\n","      <td>36.0</td>\n","      <td>40.0</td>\n","      <td>195.0</td>\n","    </tr>\n","    <tr>\n","      <th>233</th>\n","      <td>17751</td>\n","      <td>196.0</td>\n","      <td>115</td>\n","      <td>62.0</td>\n","      <td>3.2</td>\n","      <td>4.34</td>\n","      <td>Louisa</td>\n","      <td>50</td>\n","      <td>male</td>\n","      <td>67.0</td>\n","      <td>140.0</td>\n","      <td>medium</td>\n","      <td>176.0</td>\n","      <td>110.0</td>\n","      <td>150.0</td>\n","      <td>102.0</td>\n","      <td>35.0</td>\n","      <td>37.0</td>\n","      <td>60.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1003</td>\n","      <td>78.0</td>\n","      <td>93</td>\n","      <td>12.0</td>\n","      <td>6.5</td>\n","      <td>4.63</td>\n","      <td>Buckingham</td>\n","      <td>67</td>\n","      <td>male</td>\n","      <td>67.0</td>\n","      <td>119.0</td>\n","      <td>large</td>\n","      <td>110.0</td>\n","      <td>50.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>33.0</td>\n","      <td>38.0</td>\n","      <td>480.0</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>1045</td>\n","      <td>194.0</td>\n","      <td>81</td>\n","      <td>36.0</td>\n","      <td>5.4</td>\n","      <td>5.28</td>\n","      <td>Louisa</td>\n","      <td>36</td>\n","      <td>male</td>\n","      <td>64.0</td>\n","      <td>126.0</td>\n","      <td>medium</td>\n","      <td>110.0</td>\n","      <td>76.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>30.0</td>\n","      <td>34.0</td>\n","      <td>120.0</td>\n","    </tr>\n","    <tr>\n","      <th>131</th>\n","      <td>12004</td>\n","      <td>188.0</td>\n","      <td>77</td>\n","      <td>45.0</td>\n","      <td>4.2</td>\n","      <td>4.79</td>\n","      <td>Louisa</td>\n","      <td>31</td>\n","      <td>female</td>\n","      <td>67.0</td>\n","      <td>227.0</td>\n","      <td>medium</td>\n","      <td>122.0</td>\n","      <td>70.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>47.0</td>\n","      <td>53.0</td>\n","      <td>140.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        id   chol  stab.glu   hdl  ratio  ...  bp.2s  bp.2d  waist   hip  time.ppn\n","353  40501  206.0        83  68.0    3.0  ...  142.0  102.0   36.0  40.0     195.0\n","233  17751  196.0       115  62.0    3.2  ...  150.0  102.0   35.0  37.0      60.0\n","3     1003   78.0        93  12.0    6.5  ...    NaN    NaN   33.0  38.0     480.0\n","18    1045  194.0        81  36.0    5.4  ...    NaN    NaN   30.0  34.0     120.0\n","131  12004  188.0        77  45.0    4.2  ...    NaN    NaN   47.0  53.0     140.0\n","\n","[5 rows x 19 columns]"]},"metadata":{"tags":[]},"execution_count":149}]},{"cell_type":"code","metadata":{"id":"Z-OUyIVibybL"},"source":[""],"execution_count":null,"outputs":[]}]}