Modelo_Decision_tree.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Modelo_Decision_tree.ipynb","provenance":[],"mount_file_id":"1xSygPwOrNWmVZdozHVHjee-WsylLWKhH","authorship_tag":"ABX9TyPelGkzLP/PtQIZVNCaK6xk"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"jgeN0haJvZc5","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"DwXzvrNDf8UI","colab_type":"text"},"source":["# Importing the libraries"]},{"cell_type":"code","metadata":{"id":"o28y6Xmqf-UC","colab_type":"code","colab":{}},"source":["import os\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import pandas as pd\n","import keras\n","\n","from tensorflow.python.keras.models import Sequential\n","from tensorflow.python.keras.layers import Dense, Dropout\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import mean_squared_error, mean_absolute_error\n","from math import sqrt"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"4Lu0BQmagAWj","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"uoTLP_-ygAwy","colab_type":"text"},"source":["# Loading the dataset"]},{"cell_type":"code","metadata":{"id":"cFm-a6UNgCTF","colab_type":"code","colab":{}},"source":["df = pd.read_csv(\"drive/My Drive/poster/sp1/normalized_energy_efficiency_dataset.csv\")"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"AvdWWPmFgN0r","colab_type":"code","outputId":"78dd2d69-5264-4222-dd02-136d5f5a27cf","executionInfo":{"status":"ok","timestamp":1587260730284,"user_tz":360,"elapsed":1379,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":419}},"source":["df"],"execution_count":0,"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>Unnamed: 0</th>\n","      <th>Relative Compactness</th>\n","      <th>Surface Area</th>\n","      <th>Wall Area</th>\n","      <th>Roof Area</th>\n","      <th>Overall Height</th>\n","      <th>Orientation</th>\n","      <th>Glazing Area</th>\n","      <th>Glazing Area Distribution</th>\n","      <th>Heating Load</th>\n","      <th>Cooling Load</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>0.98</td>\n","      <td>0.000000</td>\n","      <td>0.285714</td>\n","      <td>0.000000</td>\n","      <td>7.0</td>\n","      <td>2</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>15.55</td>\n","      <td>21.33</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>0.98</td>\n","      <td>0.000000</td>\n","      <td>0.285714</td>\n","      <td>0.000000</td>\n","      <td>7.0</td>\n","      <td>3</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>15.55</td>\n","      <td>21.33</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>0.98</td>\n","      <td>0.000000</td>\n","      <td>0.285714</td>\n","      <td>0.000000</td>\n","      <td>7.0</td>\n","      <td>4</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>15.55</td>\n","      <td>21.33</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>0.98</td>\n","      <td>0.000000</td>\n","      <td>0.285714</td>\n","      <td>0.000000</td>\n","      <td>7.0</td>\n","      <td>5</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>15.55</td>\n","      <td>21.33</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>0.90</td>\n","      <td>0.166667</td>\n","      <td>0.428571</td>\n","      <td>0.111111</td>\n","      <td>7.0</td>\n","      <td>2</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>20.84</td>\n","      <td>28.28</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","    </tr>\n","    <tr>\n","      <th>763</th>\n","      <td>763</td>\n","      <td>0.64</td>\n","      <td>0.916667</td>\n","      <td>0.571429</td>\n","      <td>1.000000</td>\n","      <td>3.5</td>\n","      <td>5</td>\n","      <td>0.4</td>\n","      <td>5</td>\n","      <td>17.88</td>\n","      <td>21.40</td>\n","    </tr>\n","    <tr>\n","      <th>764</th>\n","      <td>764</td>\n","      <td>0.62</td>\n","      <td>1.000000</td>\n","      <td>0.714286</td>\n","      <td>1.000000</td>\n","      <td>3.5</td>\n","      <td>2</td>\n","      <td>0.4</td>\n","      <td>5</td>\n","      <td>16.54</td>\n","      <td>16.88</td>\n","    </tr>\n","    <tr>\n","      <th>765</th>\n","      <td>765</td>\n","      <td>0.62</td>\n","      <td>1.000000</td>\n","      <td>0.714286</td>\n","      <td>1.000000</td>\n","      <td>3.5</td>\n","      <td>3</td>\n","      <td>0.4</td>\n","      <td>5</td>\n","      <td>16.44</td>\n","      <td>17.11</td>\n","    </tr>\n","    <tr>\n","      <th>766</th>\n","      <td>766</td>\n","      <td>0.62</td>\n","      <td>1.000000</td>\n","      <td>0.714286</td>\n","      <td>1.000000</td>\n","      <td>3.5</td>\n","      <td>4</td>\n","      <td>0.4</td>\n","      <td>5</td>\n","      <td>16.48</td>\n","      <td>16.61</td>\n","    </tr>\n","    <tr>\n","      <th>767</th>\n","      <td>767</td>\n","      <td>0.62</td>\n","      <td>1.000000</td>\n","      <td>0.714286</td>\n","      <td>1.000000</td>\n","      <td>3.5</td>\n","      <td>5</td>\n","      <td>0.4</td>\n","      <td>5</td>\n","      <td>16.64</td>\n","      <td>16.03</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>768 rows × 11 columns</p>\n","</div>"],"text/plain":["     Unnamed: 0  Relative Compactness  ...  Heating Load  Cooling Load\n","0             0                  0.98  ...         15.55         21.33\n","1             1                  0.98  ...         15.55         21.33\n","2             2                  0.98  ...         15.55         21.33\n","3             3                  0.98  ...         15.55         21.33\n","4             4                  0.90  ...         20.84         28.28\n","..          ...                   ...  ...           ...           ...\n","763         763                  0.64  ...         17.88         21.40\n","764         764                  0.62  ...         16.54         16.88\n","765         765                  0.62  ...         16.44         17.11\n","766         766                  0.62  ...         16.48         16.61\n","767         767                  0.62  ...         16.64         16.03\n","\n","[768 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":61}]},{"cell_type":"code","metadata":{"id":"tYaCaZLdgODo","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"AQt6EBv2gglc","colab_type":"text"},"source":["# Creating the Decision Tree for heating load"]},{"cell_type":"code","metadata":{"id":"_AdoqImjgkmz","colab_type":"code","colab":{}},"source":["'''\n","Aqui cargamos las variables vamos a utilizar las 7 variables como variables \n","de entrenamiento y una unica variable (heating load) como la que queremos predecir\n","'''\n","X = df.iloc[:, 0:8].values\n","y = df.iloc[:, 8:9].values"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"_JKOfEWYg6Kj","colab_type":"code","colab":{}},"source":["'''\n","Partimos el dataset en training y testing con una proporción de \n","20% para testing y 80% para training\n","'''\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"pTq_KXJfg6Mp","colab_type":"code","outputId":"924c613d-7233-4463-beb5-95d17a943bda","executionInfo":{"status":"ok","timestamp":1587260730286,"user_tz":360,"elapsed":1368,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["# Verificamos el shape para ver si tenemos la cantidad correcta de variables para entrenar\n","X.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(768, 8)"]},"metadata":{"tags":[]},"execution_count":64}]},{"cell_type":"code","metadata":{"id":"vko0I0Tyg9b6","colab_type":"code","outputId":"86af76e1-97cd-4ee6-b08a-69f237d23e8e","executionInfo":{"status":"ok","timestamp":1587260730287,"user_tz":360,"elapsed":1358,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":119}},"source":["# Fitting Decision Tree Regression to the dataset\n","from sklearn.tree import DecisionTreeRegressor\n","regressor = DecisionTreeRegressor(random_state = 0)\n","regressor.fit(X_train, y_train)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                      max_features=None, max_leaf_nodes=None,\n","                      min_impurity_decrease=0.0, min_impurity_split=None,\n","                      min_samples_leaf=1, min_samples_split=2,\n","                      min_weight_fraction_leaf=0.0, presort='deprecated',\n","                      random_state=0, splitter='best')"]},"metadata":{"tags":[]},"execution_count":66}]},{"cell_type":"code","metadata":{"id":"OYbFzhywhF3Z","colab_type":"code","outputId":"bec50f82-ba5a-41af-a820-518def1ea593","executionInfo":{"status":"ok","timestamp":1587260730288,"user_tz":360,"elapsed":1354,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":187}},"source":["# Predicting the Test set results\n","y_pred = regressor.predict(X_test)\n","y_pred"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([3., 2., 2., 0., 1., 2., 2., 2., 3., 4., 0., 1., 5., 2., 5., 4., 3.,\n","       1., 4., 2., 3., 2., 3., 2., 0., 2., 4., 5., 1., 5., 5., 3., 3., 2.,\n","       3., 3., 3., 5., 1., 0., 3., 2., 1., 3., 0., 3., 5., 3., 4., 4., 2.,\n","       2., 4., 5., 4., 1., 0., 1., 4., 4., 3., 2., 3., 5., 1., 3., 2., 5.,\n","       5., 3., 3., 4., 5., 2., 4., 2., 4., 5., 4., 1., 2., 3., 1., 5., 5.,\n","       2., 5., 0., 4., 2., 2., 5., 1., 1., 1., 1., 3., 2., 0., 3., 3., 3.,\n","       0., 1., 5., 4., 5., 4., 1., 0., 5., 4., 2., 3., 3., 5., 5., 5., 5.,\n","       5., 5., 2., 1., 2., 3., 4., 4., 3., 4., 5., 1., 1., 4., 3., 5., 0.,\n","       4., 1., 5., 3., 1., 1., 4., 1., 1., 3., 1., 1., 3., 4., 5., 4., 5.,\n","       2.])"]},"metadata":{"tags":[]},"execution_count":67}]},{"cell_type":"code","metadata":{"id":"F2Vwb5kBhkhj","colab_type":"code","colab":{}},"source":["'''\n"," Creamos un dataframe que contenga los resultados reales del testing y los \n"," resultados de la prediccion que realizamos esto es para luego poder calcular\n"," el mse, rmse, mae\n","'''\n","df_heat = pd.DataFrame()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"UVqqPBkhho19","colab_type":"code","colab":{}},"source":["df_heat['original_values'] = y_test.flatten()\n","df_heat['Predicted_Values'] = y_pred"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"ms21YOVlhqth","colab_type":"code","outputId":"e00a0d92-f249-452a-d754-7b0e35b2688c","executionInfo":{"status":"ok","timestamp":1587260730289,"user_tz":360,"elapsed":1346,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":419}},"source":["df_heat"],"execution_count":0,"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>original_values</th>\n","      <th>Predicted_Values</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>3</td>\n","      <td>3.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>2.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>2.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>149</th>\n","      <td>4</td>\n","      <td>4.0</td>\n","    </tr>\n","    <tr>\n","      <th>150</th>\n","      <td>5</td>\n","      <td>5.0</td>\n","    </tr>\n","    <tr>\n","      <th>151</th>\n","      <td>4</td>\n","      <td>4.0</td>\n","    </tr>\n","    <tr>\n","      <th>152</th>\n","      <td>5</td>\n","      <td>5.0</td>\n","    </tr>\n","    <tr>\n","      <th>153</th>\n","      <td>2</td>\n","      <td>2.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>154 rows × 2 columns</p>\n","</div>"],"text/plain":["     original_values  Predicted_Values\n","0                  3               3.0\n","1                  2               2.0\n","2                  2               2.0\n","3                  0               0.0\n","4                  1               1.0\n","..               ...               ...\n","149                4               4.0\n","150                5               5.0\n","151                4               4.0\n","152                5               5.0\n","153                2               2.0\n","\n","[154 rows x 2 columns]"]},"metadata":{"tags":[]},"execution_count":70}]},{"cell_type":"code","metadata":{"id":"ZLZIWSqGhr_z","colab_type":"code","outputId":"35f9a101-51a9-42c3-f775-915dfdc2acbb","executionInfo":{"status":"ok","timestamp":1587260730290,"user_tz":360,"elapsed":1342,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["'''\n","Todos los calculos que se van a realizar posteriormente \n","nos ayudaran a poder ver el performance del modelo\n","'''\n","\n","# Calculamos el Mean squared Error\n","mse_heat = mean_squared_error(df_heat['original_values'], df_heat['Predicted_Values'])\n","mse_heat"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.006493506493506494"]},"metadata":{"tags":[]},"execution_count":71}]},{"cell_type":"code","metadata":{"id":"6-L3RDPRht4i","colab_type":"code","outputId":"6b0dd775-b52c-4260-b4b1-86a6610dd69e","executionInfo":{"status":"ok","timestamp":1587260730812,"user_tz":360,"elapsed":1859,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["# Calculamos el Mean Absolute Error\n","mae_heat = mean_absolute_error(df_heat['original_values'], df_heat['Predicted_Values'])\n","mae_heat"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.006493506493506494"]},"metadata":{"tags":[]},"execution_count":72}]},{"cell_type":"code","metadata":{"id":"YmKRrtkxhveM","colab_type":"code","outputId":"35356c8b-fb98-4ce3-8d83-6463cd6a7b57","executionInfo":{"status":"ok","timestamp":1587260730813,"user_tz":360,"elapsed":1854,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["# Calculamos el Root Mean Squared Error \n","root_mean_squared_error = sqrt(mse_heat)\n","root_mean_squared_error"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.08058229640253803"]},"metadata":{"tags":[]},"execution_count":73}]},{"cell_type":"code","metadata":{"id":"dRvXujaakdZh","colab_type":"code","outputId":"0c6c1674-38f2-4274-9f11-a80864bffefb","executionInfo":{"status":"ok","timestamp":1587260731212,"user_tz":360,"elapsed":2238,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":638}},"source":["'''\n","Esta grafica nos ayudara a poder visualizar los resultado de nuestro \n","modelo, tenemos dos graficas una que tiene una linea (azul) que esta \n","representa los valores predichos esta nos ayuda a poder ver las predicciones\n","y ver como es su comportamiento.\n","\n","En la segunda grafica podemos observar las predicciones pero ahora en un \n","scatterplot y esto nos ayudara a confirmar si estamos haciendo \n","overfitting y si que tanto se alinean nuestras predicciones \n","con el valor real.\n","'''\n","fig = plt.figure(figsize=(15,10))\n","ax = fig.add_subplot(111)\n","ax.scatter(np.arange(0, y_test.size), y_test, color = 'red')\n","ax.plot(np.arange(0, y_test.size), y_pred, color = 'blue')\n","plt.title('Predicciones heating Load Vs Valores Reales')\n","plt.xlabel('Edificio')\n","plt.ylabel('Heating Load')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Heating Load')"]},"metadata":{"tags":[]},"execution_count":76},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"V1VVObB0iP1n","colab_type":"code","outputId":"215848be-4e68-451a-fd07-0a1a2dd35f3b","executionInfo":{"status":"ok","timestamp":1587260731213,"user_tz":360,"elapsed":2233,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/","height":638}},"source":["fig = plt.figure(figsize=(15,10))\n","ax = fig.add_subplot(111)\n","ax.scatter(np.arange(0, y_test.size), y_test, color = 'red')\n","ax.scatter(np.arange(0, y_test.size), y_pred, color = 'blue')\n","plt.title('Predicciones heating Load Vs Valores Reales')\n","plt.xlabel('Edificio')\n","plt.ylabel('Heating Load')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Heating Load')"]},"metadata":{"tags":[]},"execution_count":77},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA3UAAAJcCAYAAABe2o1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3debhdaV0n+u+vkiohjGLFAagkKOpt4AqSKCBiF2grIIMPaiutgDhEq1DQ1qugPoq21dq2rThioyJgAiiDijQ4g1RdLmCKQURAECokFIPIWAVVSOW9f+yV4iR1zsk+5+xhved8Ps+zn5y99hp+633ftc/+Zq21T7XWAgAAQJ/OW3YBAAAAbJ5QBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gDmoKqeUVU/N/x8v6p66xbX96aqungmxc1AVbWquvOCtvXSqnrMIrY1D1V1VVV9zbLrWEtVXVxVJ5ddx7ysPBYBtiuhDtixhg/bn6iqa6rqfcOHv1vOejuttctba1+8xXXctbX28hmVNFpV9eSqOrJyWmvtQa21Z85hW0sNM1X1xKp6xSrTL6yqT1bV3aZcz82q6sNV9YBVXvuVqnr+LOqdp6EvTg3H4seq6q1V9dhl1wXQC6EO2Oke2lq7ZZJ7JjmU5CfPnqGqdi+8KnaCI0m+oqrudNb0b03yxtbaP06zktbadUn+MMmjV06vql1JHplk5oH4rG3MytXDsXjrJD+U5Heqakv/GQKwUwh1AElaa+9O8tIkd0tuvLzwcVX1tiRvG6Y9pKpeP5wVeWVVfcnp5avqS6vqtcNZhj9McrMVr51xRqiqLqqqF1bVv1bVv1XVb6x47Xuq6s3Dev6pqu45TL/xEr6q+oyqekpVXT08nlJVn7FyW1X1w1X1/qp6z8ozHsOyv1RV7xrOTv52Vd18eO3CqnrxsH8frKrLq2q93xNfU1VvG+b/zaqqFdv5zmE/PlRVf1FV+1e89qtVdaKqPlpVV1bV/YbpD0zy40m+ZThj84Zh+sur6ruHn7+jqq4Y9uFDVfXOqnrQinXfqapeMbTfXw91nXHmbxpV9R+G7X64Jpe+PmzFa19fVa8b6j9RVU8+a9lHVdXxoW9/Yq1ttNZOJvnbJI8666VHJ3nWsK47V9XfVdVHquoDw9hazTOTfGNV7Vkx7esy+T3/0qp67Ipx9Y6q+t5N7vszquqpVfWSqro2yf2r6vZV9YJhPL+zqh6/Yv4vr6pjQ1u9r6p+ea3trmiX1lp7SZIPJvmSYT3n1eTM5r8M7fpHVXW7Fdt5XlW9d2inV1TVXdfZv/WO4x+rqnfXp88WfvW56gUYA6EOIJOgleTBSV63YvI3JLlXkrtU1ZcmeXqS703yWUn+d5IXDSHpgiR/kuQPktwuyfOSfOMa29mV5MVJjic5kOQOSZ47vPbNSZ6cyYf6Wyd5WJJ/W2U1P5Hk3knukeTuSb48Z55h/NwktxnW/V1JfrOqPnN47ReSfNGw7J2HeX5qeO2Hk5xMsjfJ52QSsNpq+zF4SJIvy+SD93/OJESkqh4+LPuIYV2XJ3nOiuX+ftj+7ZI8O8nzqupmrbU/T/Lfk/xha+2WrbW7r7HdeyV5a5ILk/xikt9bESifneQ1mfTRk3PTwHROVXV+kj9L8pdJPjvJDyQ5Wp8+a3RtJn102yRfn+SSqvqGYdm7JHnqsN3bD3XccZ3NPXNljcM27jHsR5L8t6GOzxzW8+urraS19sok78mkzU97VJJnt9Y+leT9mfTXrZM8Nsmv1PAfBhvc9yT5L0kuS3KrJK8c5n9DJmPpq5P8YFV93TDvryb51dbarZN8QZI/WqctTtdw3hAkL0zy9mHyD2RyPP7HTNr1Q0l+c8ViL03yhUPNr01ydI11r3ccf3GS70/yZa21W2Uynq86V70Ao9Ba8/Dw8NiRj0w+sF2T5MOZhKzfSnLz4bWW5AEr5n1qkv921vJvzeRD5lcluTpJrXjtlUl+bvj54iQnh5/vk+Rfk+xepZ6/SPKEdWr9muHnf0ny4BWvfV2Sq1Zs6xMr15/JB/p7J6lMAskXrHjtPkneOfz8s0n+NMmdp2i7luQrVzz/oyRPHH5+aZLvWvHaeUk+nmT/Guv6UJK7Dz8/OcmRs15/eZLvHn7+jiRvX/HanqGWz02yL8mnkuxZ8fqRs9e34rUb++Ws6fdL8t4k562Y9pwkT15jPU9J8ivDzz+V5LkrXrtFkk+e7rtVlt2T5KNJvmJ4flmSP13x+rOSPC3JHafok59M8pfDz7ce2vxL15j3T06PtbPG57r7nuQZSZ614rV7JXnXWet+UpLfH35+RZKfSXLhOWq/OMmpTI7F65PckOQHV7z+5iRfveL55yX596x+HN12GBO3WVHz6WNxveP4zpkcK1+T5PxztbeHh4fHmB7O1AE73Te01m7bWtvfWru0tfaJFa+dWPHz/iQ/PFyy9eGq+nCSizI5a3D7JO9ura08q3V8je1dlOR4m5w9We21f5mi5tuftf7jw7TT/u2s9X88yS0zOWu2J8mVK/bhz4fpSfI/Mzkz8pfDJXpPPEcd711lG8mkrX51xTY+mEmgvEOSVNWPDJcCfmR4/TaZnJWZ1o3bba19fPjxlpm0wQdXTEvO7MNp3T7JidbaqRXTjq+o/15V9bLhcsOPJPm+FfXffuU2W2vXZvWzrSvrf16SRw9nG78tw6WXgx/NpO1eM1wK+Z3r1P0HGS6HTPJNSf6ltfa6oeYHVdWranJZ7YczOSu9Wpuvu++Ds4+L2591XPx4Jmd6k8mZ4i9K8paq+vuqesg69V/dWrttJoH015Ks/OKX/Un+eMU23pxJ8PucqtpVVb8wXJr50Xz67Npq+7fmcdxae3uSH8zkPxbeX1XPHdoSYPSEOoC1rQxpJ5JcNgTA0489rbXnZHLZ2x1WXAKYTM4areZEkn21+pevnMjkErVzuTqTD6crt3X1FMt9IJOzeHddsQ+3aZMvp0hr7WOttR9urX1+Jpd+/tdN3lN0Isn3ntVWN2+tvbIm98/9aCaXa37m8CH+I5kEl2T9yz3P5T1JbnfWfWUXbWI9Vye5qM68n3BfkncPPz87yYuSXNRau02S386n63/Pym0OtXzWObb3zEza4z9lcknjn51+obX23tba97TWbp/JJYO/VWv8KYnW2vFMLnX99kwuvXzmUMNnJHlBkl9K8jlDm79kRc0b2ffkpsfFO8/q61u11h481PS21tojM7ks8n8keX5V3WK9xmitXZ/kx5L836cvax2286CztnOzNrkX9r8keXgmZ9huk8llzVlj/9Y7jtNae3Zr7SszOb7aUDPA6Al1ANP5nSTfN5ylqaq6RU2+MONWSf6/TC77e3xVnV9Vj8jkPrfVvCaTD/6/MKzjZlV13+G1303yI1V1cNjGnWvFF4ys8JwkP1lVe6vqwkwu+Tvnl4EMZ19+J5P7qT47SarqDqfvfxq+QOLOQzj9SCZnQk6tucK1/XaSJ53+soqqus1wv2AyCS2fynAJalX9VCZnZk57X5IDtf4XtKy1f8eTHEvy5Kq6oKruk+Sh51pu6IMbH5n00ceT/OjQnxcP63nuin34YGvtuqr68kxCxWnPT/KQqvrK4V7Ln825f9densllh0/L5NLNT66o7Zur6vQ9eR/KJGis1yfPzOS+sPvm0/eVXZDkMzJp80/V5ItlvnaN5V99jn0/22uSfKwmXzBy8+Gs2d2q6suG+r+9qvYOY+/DwzLnHFNDG/yvfPp+z99Octnp42EY+w8fXrtVJpds/lsmZ6L/+zqrXvM4rqovrqoHDCH4ukz+A2Qz4x9g4YQ6gCm01o4l+Z4kv5HJh+u3Z3J/1+kPoI8Ynn8wybckeeEa67khkw/Jd07yrky+mORbhteel8k9Vc9O8rFM7nu63Sqr+blMwss/JHljJl8MMe0fV/6xofZXDZeq/XWS01+C8YXD82syCaq/1Vp72ZTrvVFr7Y8zOcPx3GEb/5jk9DdU/kUml3z+cyaX9V2XMy/ne97w779V1Ws3uu1MLl+8TyYf8H8uk6/6v36d+e+QyYf3lY+LMumjB2VydvO3kjy6tfaWYZlLk/xsVX0sk9Bx45d/tNbelORxmfThezIZK+v+Lbzhst1nZXJ26FlnvfxlSV5dVddkcnbwCa21d6yzuhdkMmb+prX2nmH9H0vy+KHOD2USQl+0Ri2fPMe+nz3/DZl8Acs9krxzWOZ3MzljliQPTPKmof5fTfKtZ13ivJ6nZ3JW+6HDsi/K5NLgjyV5VSb38yWTNjueydnEfxpeW9V6x3EmwfcXhn14byZnF580Za0AS1Vn3gICANtHTf4EwFtaaz+97FoAYF6cqQNg26iqL6uqL6jJ1+I/MJN7rf5k2XUBwDytdqM+APTqczO59PWzMrns8ZLT3wAJANuVyy8BAAA65vJLAACAjo3q8ssLL7ywHThwYNllAAAALMWVV175gdba3o0sM6pQd+DAgRw7dmzZZQAAACxFVR3f6DIuvwQAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMfmGuqq6qqqemNVvb6qjs1zW2zN0UuvyIHdJ3NencqB3Sdz9NIrtjTfdraVthpT+42plmmMqd4x1bIVs96PRYz5RbT9qts4ejQ5cCA577zJv0ePzn2bY3pf3i5jfiuW1R/L6t+zp11615dPNUbH/rtvWj0eVz2281aM6T1yFFprc3skuSrJhdPOf/DgwcbiHbnk8rYn17Sk3fjYk2vakUsu39R829lW2ur8fKJdkOtG0X699eWY6h1TLVsx6/1YxJhfRNuvuY1dj2pnTtzT2pEjc9vmtG231DbpbMxvxbJ+Ty6rf1cbf8mpc84z7bSxj58ej6uddpxu98+uSY61jeaujS6woZULdV3Yv+vEWW/ck8f+XSc2Nd92ttW2Gkv79daXY6p3TLVsxaz3YxFjfhFtv+Y28s5VJu6f6zbH8r68Xcb8Vizr9+Qy+3fejzGPnx6Pq512nG73z66bCXU1WW4+quqdST6UpCX53621p60yz+Ekh5Nk3759B48fPz63eljdeXUqbZUrcSuncqqdt+H5trOtttVqltF+vfXlmOodUy1bMev9WMSYX0Tbr7uN7DprYiWnTs1tm6tZxvvydhnzW7Gs35PL7N95G/P46fG42mnH6Xb/7FpVV7bWDm1kmXnvzVe21u6Z5EFJHldVX3X2DK21p7XWDrXWDu3du3fO5bCafbuunmr6tPNtZ1ttq42sc55668sx1TumWrZi1vuxiDG/iLZfcxt51yoT9811m9PMu9Q26WzMb8Wyfk8us3/nbczjp8fjaqcdpz673tRcQ11r7d3Dv+9P8sdJvnye22NzLjt8Vfbk2jOm7cm1uezwVZuabzvbSludn+tyQa4/57KL0FtfjqneMdWyFbPej0WM+UW0/Zrb2PVTZ864Z09y2WVz2+a0bbfUNulszG/Fsn5PLqt/Vxt/k4uu1p9n2mljHz89Hlc77Tj12XUVG71ec9pHklskudWKn1+Z5IHrLeOeuuU5csnlbf+uE61yQ9u/68SaN5BOO992tpW2GlP7jamWaYyp3jHVshWz3o9FjPlFtP2q2zhyZHIPXdXk3xl9Scp62xzT+/J2GfNbsaz+WFb/nj3tkru8bKoxOvbffdPq8bjqsZ23YkzvkbOWMd1TV1Wfn8nZuSTZneTZrbV1/1vz0KFD7dgxf/kAAADYmTZzT93ueRXTWntHkrvPa/0AAADM/4tSAAAAmCOhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY3MPdVW1q6peV1Uvnve2drqjl16RA7tP5rw6lQO7T+bopVeMfrvLqnlaY6+Pm1qtzxYxRmc9Vma9Hz0aU78dPZocOJCcd97k36NHN7FDS7bTxs8ijOn9Yafbynvm2Punx893y6plTDUvXGttro8k/zXJs5O8+FzzHjx4sLE5Ry65vO3JNS1pNz725Jp25JLLR7vdZdU8rbHXx02t1mfn5xPtglw31zE667Ey6/3o0SLeW6ae70hre/a0M+fbM5neC+9nszem94ed3pdbec8ce//0+PluWbWMqeatSnKsbTRzbXSBDa08uWOSv0nyAKFuvvbvOnHGID792L/rxGi3u6yapzX2+riptfps3mN01mNl1vvRo0W8t0w93/412n7/DHd4zryfzd7Y3h92cl9u5T1z7P3T4+e7ZdUyppq3ajOhribLzUdVPT/Jzye5VZIfaa09ZJV5Dic5nCT79u07ePz48bnVs52dV6fSVrmatnIqp9r8rrLdynaXVfO0xl4fN7VWn61mlmN01mNl1vvRo0W8t0w933mTjwY3ma+SU6fWLWU0vJ/N3tjeH3ZyX27lPXPs/dPj57tl1TKmmreqqq5srR3ayDJz28OqekiS97fWrlxvvtba01prh1prh/bu3Tuvcra9fbuu3tD0MWx3WTVPa+z1cVMb6ZtZjtFZj5VZ70ePFvHeMvV8+9bYzhrTx8j72eyN7f1hJ/flVt4zx94/PX6+m7VlHWu9mWdsvW+Sh1XVVUmem+QBVXVkjtvb0S47fFX25Nozpu3Jtbns8FWj3e6yap7W2Ovjplbrs/NzXS7I9WdMm/UYnfVYmfV+9GgR7y1Tz3dZsmfPmdvYs2cyvRfez2ZvTO8PO70vt/KeOfb+6fHz3bJqGVPNS7HR6zU380hycdxTN3dHLrm87d91olVuaPt3nVjYjaFb2e6yap7W2Ovjplbrs0WM0VmPlVnvR4/G1G9Hjkzuoaua/NvTl6ScttPGzyKM6f1hp9vKe+bY+6fHz3fLqmVMNW9FxnZP3WlVdXHWuKdupUOHDrVjx47NvR4AAIAx2sw9dbvnVcxKrbWXJ3n5IrYFAACwk/T1VTAAAACcQagDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOjY3EJdVd2sql5TVW+oqjdV1c/Ma1vzcvTSK3Jg98mcV6dyYPfJHL30imWXdKMx15bMvr5p1zf2dlnNajVvZX+3sr6t1DzL5bZzf8/aItpqEeNnu/bldt2veZj1GN1J42wt27UNxvR+Zruz3+52GKNL0VqbyyNJJbnl8PP5SV6d5N7rLXPw4ME2FkcuubztyTUtaTc+9uSaduSSy5dd2qhra2329U27vrG3y2pWq/n8fKJdkOs2tb+rLTvt+rZS8zTrm3U/9tjfs7aItlrE8TzrMToWxuj0Zj1GF/FeOHbb9Vgb0/vZImreadv1vjmR5FjbaPba6AKbeSTZk+S1Se613nxjCnX7d504Y0CdfuzfdWLZpY26ttZmX9+06xt7u6xmrZq3sr+bXd9Waz7X+mbdjz3296wtoq0WdTxvx740Rqc3jzG6U8bZWrbrsTam97NF1LzTtut9c2Izoa4my81HVe1KcmWSOyf5zdbaj60yz+Ekh5Nk3759B48fPz63ejbivDqVtsrVqZVTOdWWeyvimGtLZl/ftOsbe7usZq2aVzPt/k5r3v2x2eW2c3/P2iLaalHH82p670tjdHrzGKPT2q79sV2PtTG9n03LdqffrvfNiaq6srV2aCPLzLV1Wms3tNbukeSOSb68qu62yjxPa60daq0d2rt37zzL2ZB9u67e0PRFGnNtyezrm3Z9Y2+X1Wyktmn3dx7bnma5c61v1v3YY3/P2iLaalHH8yy3MRbG6PTmMUa3uu3ebddjbUzvZ9Oy3em3631z8xYSeVtrH07ysiQPXMT2ZuGyw1dlT649Y9qeXJvLDl+1nIJWGHNtyezrm3Z9Y2+X1axW8/m5Lhfk+jOmTbu/qy077fq2UvM065t1P/bY37O2iLZaxPE86zE6Fsbo9GY9RhfxXjh22/VYG9P72bRsd/x9tC1s9HrNaR9J9ia57fDzzZNcnuQh6y0zpnvqWpvcrLl/14lWuaHt33ViVDdpjrm21mZf37TrG3u7rGa1mreyv1tZ31ZqnuVy27m/Z20RbbWI8bNd+3K77tc8zHqM7qRxtpbt2gZjej+z3dlvdzuM0a3KmO6pq6ovSfLMJLsyOSP4R621n11vmUOHDrVjx47NpR4AAICx28w9dbvnVUxr7R+SfOm81g8AAMCC7qkDAABgPoQ6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADq2e60XquoR6y3YWnvh7MsBAABgI9YMdUkeOvz72Um+IsnfDs/vn+SVSYQ6AACAJVsz1LXWHpskVfWXSe7SWnvP8PzzkjxjIdUBAACwrmnuqbvodKAbvC/JvjnVAwAAwAasd/nlaX9TVX+R5DnD829J8tfzKwkAAIBpnTPUtda+f/jSlPsNk57WWvvj+ZYFAADANKY5U3f6my59MQoAAMDInPOeuqq6d1X9fVVdU1WfrKobquqjiygOAACA9U3zRSm/keSRSd6W5OZJvjvJb86zKAAAAKYzTahLa+3tSXa11m5orf1+kgfOtywAAACmMc09dR+vqguSvL6qfjHJezJlGAQAAGC+pglnjxrm+/4k1ya5KMk3zrMoAAAApjPNnzQ4Ppyp25fkBUne2lr797lXBgAAwDmdM9RV1cVJnpnkqiSV5KKqekxr7RXzLQ0AAIBzmeaeuv+V5Gtba29Nkqr6oiTPSXJwnoUBAABwbtPcU3f+6UCXJK21f05y/vxKAgAAYFrTnKk7VlW/m+TI8PzbkhybX0kAAABMa5pQd0mSxyV5/PD88vjj4wAAAKMwzbdfXp/kl4dHkqSq/t8k951jXQAAAExhs39EfN9MqwAAAGBTNhvq2kyrAAAAYFPWvPyyqh6x1ktJbj6fcgAAANiI9e6pe+g6r7141oUAAACwcWuGutbaYxdZCAAAABu32XvqAAAAGAGhDgAAoGNCHQAAQMfO+cfH1/gWzI8keWNr7f2zLwkAAIBpnTPUJfmuJPdJ8rLh+cVJrkxyp6r62dbaH8ypNgAAAM5hmlC3O8l/aK29L0mq6nOSPCvJvZK8IolQBwAAsCTT3FN30elAN3j/MO2DSf59PmUBAAAwjWnO1L28ql6c5HnD828cpt0iyYfnVhkAAADnNE2oe1wmQe6+w/NnJXlBa60luf+8CgMAAODczhnqhvD2/OEBAADAiJzznrqqekRVva2qPlJVH62qj1XVRxdRHAAAAOub5vLLX0zy0Nbam+ddDAAAABszzbdfvk+gAwAAGKdpztQdq6o/TPInSa4/PbG19sK5VQUAAMBUpgl1t07y8SRfu2JaSyLUAQAALNk033752EUUAgAAwMatGeqq6kdba79YVb+eyZm5M7TWHj/XygAAADin9c7Unf5ylGOLKAQAAICNWzPUtdb+bPjx46215618raq+ea5VAQAAMJVp/qTBk6acBgAAwIKtd0/dg5I8OMkdqurXVrx06ySfmndhAAAAnNt699Rdncn9dA9LcuWK6R9L8kPzLAoAAIDprHdP3RuSvKGqnt1a+/cF1gQAAMCUpvnj4weq6ueT3CXJzU5PbK19/tyqAgAAYCrTfFHK7yd5aib30d0/ybOSHJlnUQAAAExnmlB389ba37+hjm4AABbbSURBVCSp1trx1tqTk3z9fMsCAABgGtNcfnl9VZ2X5G1V9f1J3p3klvMtCwAAgGlMc6buCUn2JHl8koNJvj3JY+ZZFAAAANM555m61trfJ0lVnWqtPXb+JQEAADCtc56pq6r7VNU/JXnL8PzuVfVbc68MAACAc5rm8sunJPm6JP+W3Pj3675qnkUBAAAwnWlCXVprJ86adMMcagEAAGCDpvn2yxNV9RVJWlWdn8kXp7x5vmUBAAAwjWnO1H1fkscluUMmf87gHsNzAAAAlmyab7/8QJJvW0AtAAAAbNCaoa6qfj1JW+v11trj51IRAAAAU1vvTN2xFT//TJKfnnMtAAAAbNCaoa619szTP1fVD658DgAAwDhM9ScNss5lmAAAACzPtKEOAACAEVrvi1I+lk+fodtTVR89/VKS1lq79byLAwAAYH3r3VN3q0UWAgAAwMa5/BIAAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjs0t1FXVRVX1sqr6p6p6U1U9YV7bWqSjl16RA7tP5rw6lQO7T+bopVesOm2W69rs+rdq7Ntd1nzLor7ZGtOxNmuL2I8xtdVYjvEe233sx8GYahm73tpqLMctO9O2HFettbk8knxeknsOP98qyT8nuct6yxw8eLCN2ZFLLm97ck1L2o2P8/OJdkGuO2PanlzTjlxy+UzWtdn1z2Nfx7TdZc23LOqbrVkey2OziL4YU3+P5Rjvsd3HfhyMaZyNXW9tNZbjlp2ph3GV5FjbaPba6AKbfST50yT/ab15xh7q9u86ccYAWO+xf9eJma1rM+uf176OZbvLmm9Z1DdbszyWx2YRfTGm/h7LMd5ju4/9OBjTOBu73tpqLMctO1MP42ozoa4my81XVR1I8ookd2utffSs1w4nOZwk+/btO3j8+PG517NZ59WptCmvWK2cyqm29rwbWddm1r9Va9U3lu0ua75lUd9szfJYHptF9MWY+nssx3iP7T7242BM42zsemursRy37Ew9jKuqurK1dmgjy8y98qq6ZZIXJPnBswNdkrTWntZaO9RaO7R37955l7Ml+3ZdPbN5N7KueSy/2fWPZbvLmm9Z1DdbszyWx2YRfTGm/h7LMd5ju4/9OBjTOBu73tpqLMctO9N2HVdzDXVVdX4mge5oa+2F89zWIlx2+KrsybVnTDs/1+WCXH/GtD25Npcdvmom69rs+rdqtfrGtN1lzbcs6putWR7LY7OIvhhTf4/lGO+x3cd+HIxpnI1db201luOWnWnbjquNXq857SNJJXlWkqdMu8zY76lrbXJz5f5dJ1rlhrZ/14l25JLLV502y3Vtdv1bNfbtLmu+ZVHfbI3pWJu1RezHmNpqLMd4j+0+9uNgTLWMXW9tNZbjlp1p7OMqY7qnrqq+MsnlSd6Y5NQw+cdbay9Za5lDhw61Y8eOzaUeAACAsdvMPXW751VMa+2KTM7WAQAAMCfj+IoXAAAANkWoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADo2NxCXVU9vareX1X/OK9t9ObopVfkwO6TOa9O5cDukzl66RU7qo6x7P88bJd9m+V+bJc22Ypp22BMbTWmWsZus221Xdp4tf3YyrQxWUR9Y2+DZRh7m4xpLG9lu1vZj2UtyxRaa3N5JPmqJPdM8o/TLnPw4MG2XR255PK2J9e0pN342JNr2pFLLt8RdYxl/+dhu+zbLPdju7TJVkzbBmNqqzHVMnabbavt0sar7cf5+US7INdtatqY2mARfbRdxsEsjb1Nph3zY/9MtZX9WNayO1GSY22D2asmy81HVR1I8uLW2t2mmf/QoUPt2LFjc6tnmQ7sPpnjN9zxJtP37zqZqz510+nbrY6x7P88bJd9m+V+bJc22Ypp22BMbTWmWsZus221Xdp4rf3YirG0wSL6aLuMg1kae5tsZMyP+TPVVvZjWcvuRFV1ZWvt0IaWWXaoq6rDSQ4nyb59+w4eP358bvUs03l1Km2Vq10rp3KqLe7WxmXVMZb9n4ftsm+z3I/t0iZbMW0bjKmtxlTL2G22rbZLG6+1H1sxljZYRB9tl3EwS2Nvk42M+TF/ptrKfixr2Z1oM6Fu6S3WWntaa+1Qa+3Q3r17l13O3OzbdfWGpm+3Osay//OwXfZtlvuxXdpkK6ZtgzG11ZhqGbvNttV2aeN51DuWNlhEH22XcTBLY2+TjdQx5s9UW9mPZS3LdJYe6naKyw5flT259oxpe3JtLjt81Y6oYyz7Pw/bZd9muR/bpU22Yto2GFNbjamWsdtsW22XNl5tP87Pdbkg129q2pjaYBF9tF3GwSyNvU2mHfNj/0y1lf1Y1rJMaaM34W3kkeRAfFHKjY5ccnnbv+tEq9zQ9u86sbQbQZdVx1j2fx62y77Ncj+2S5tsxbRtMKa2GlMtY7fZttoubbzafmxl2pgsor6xt8EyjL1NxjSWt7LdrezHspbdaTKmL0qpquckuTjJhUnel+SnW2u/t94y2/mLUgAAAM5lM/fU7Z5XMa21R85r3QAAAEy4pw4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOCXUAAAAdE+oAAAA6JtQBAAB0TKgDAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMfmGuqq6oFV9daqentVPXGe2xqbo5dekQO7T+a8OpUDu0/m6KVX7Og6xka7TG/ebbXT+mKn7S/LsZ3H2az3bUxtNaZaWA5jgE1rrc3lkWRXkn9J8vlJLkjyhiR3WW+ZgwcPtu3gyCWXtz25piXtxseeXNOOXHL5jqxjbLTL9ObdVjutL3ba/rIc23mczXrfxtRWY6qF5TAGOC3JsbbB7FWT5Wavqu6T5Mmtta8bnj9pCJE/v9Yyhw4daseOHZtLPYt0YPfJHL/hjjeZvn/XyVz1qZtO3+51jI12md6822qn9cVO21+WYzuPs1nv25jaaky1sBzGAKdV1ZWttUMbWmaOoe6bkjywtfbdw/NHJblXa+37z5rvcJLDSbJv376Dx48fn0s9i3RenUpb5crWyqmcaou7jXEsdYyNdpnevNtqp/XFTttflmM7j7NZ79uY2mpMtbAcxgCnbSbULX2EtNae1lo71Fo7tHfv3mWXMxP7dl29oenbvY6x0S7Tm3db7bS+2Gn7y3Js53E2630bU1uNqRaWwxhgK+YZ6t6d5KIVz+84TNv2Ljt8Vfbk2jOm7cm1uezwVTuyjrHRLtObd1vttL7YafvLcmzncTbrfRtTW42pFpbDGGBLNnoT3rSPJLuTvCPJnfLpL0q563rLbJcvSmltcrPr/l0nWuWGtn/XiaXd5DqWOsZGu0xv3m210/pip+0vy7Gdx9ms921MbTWmWlgOY4DWRvZFKUlSVQ9O8pRMvgnz6a21y9abf7t8UQoAAMBmbOaeut3zKiZJWmsvSfKSeW4DAABgJ1v6F6UAAACweUIdAABAx4Q6AACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGNCHQAAQMeEOgAAgI4JdQAAAB0T6gAAADom1AEAAHRMqAMAAOiYUAcAANAxoQ4AAKBjQh0AAEDHhDoAAICOVWtt2TXcqKr+NcnxZdexiguTfGDZRZBEX4yN/hgPfTEe+mJc9Md46Itx0R/jcXZf7G+t7d3ICkYV6saqqo611g4tuw70xdjoj/HQF+OhL8ZFf4yHvhgX/TEes+gLl18CAAB0TKgDAADomFA3nactuwBupC/GRX+Mh74YD30xLvpjPPTFuOiP8dhyX7inDgAAoGPO1AEAAHRMqAMAAOiYULeOqnpgVb21qt5eVU9cdj07TVVdVFUvq6p/qqo3VdUThum3q6q/qqq3Df9+5rJr3SmqaldVva6qXjw8v1NVvXo4Rv6wqi5Ydo07QVXdtqqeX1Vvqao3V9V9HBfLU1U/NLxH/WNVPaeqbubYWJyqenpVvb+q/nHFtFWPh5r4taFf/qGq7rm8yrefNfrifw7vVf9QVX9cVbdd8dqThr54a1V93XKq3r5W648Vr/1wVbWqunB47tiYo7X6oqp+YDg+3lRVv7hi+oaPDaFuDVW1K8lvJnlQkrskeWRV3WW5Ve04n0ryw621uyS5d5LHDX3wxCR/01r7wiR/MzxnMZ6Q5M0rnv+PJL/SWrtzkg8l+a6lVLXz/GqSP2+t/V9J7p5JnzgulqCq7pDk8UkOtdbulmRXkm+NY2ORnpHkgWdNW+t4eFCSLxweh5M8dUE17hTPyE374q+S3K219iVJ/jnJk5Jk+H3+rUnuOizzW8NnL2bnGblpf6SqLkrytUnetWKyY2O+npGz+qKq7p/k4Unu3lq7a5JfGqZv6tgQ6tb25Une3lp7R2vtk0mem0nDsyCttfe01l47/PyxTD643iGTfnjmMNszk3zDcircWarqjkm+PsnvDs8ryQOSPH+YRV8sQFXdJslXJfm9JGmtfbK19uE4LpZpd5KbV9XuJHuSvCeOjYVprb0iyQfPmrzW8fDwJM9qE69Kctuq+rzFVLr9rdYXrbW/bK19anj6qiR3HH5+eJLnttaub629M8nbM/nsxYyscWwkya8k+dEkK78t0bExR2v0xSVJfqG1dv0wz/uH6Zs6NoS6td0hyYkVz08O01iCqjqQ5EuTvDrJ57TW3jO89N4kn7Oksnaap2TyS+DU8Pyzknx4xS9rx8hi3CnJvyb5/eFS2N+tqlvEcbEUrbV3Z/K/q+/KJMx9JMmVcWws21rHg9/ty/WdSV46/KwvlqCqHp7k3a21N5z1kv5YvC9Kcr/hUv2/q6ovG6Zvqi+EOkavqm6Z5AVJfrC19tGVr7XJ3+TwdznmrKoekuT9rbUrl10L2Z3knkme2lr70iTX5qxLLR0XizPcq/XwTML27ZPcIqtc7sTyOB7Goap+IpPbKo4uu5adqqr2JPnxJD+17FpIMvl9frtMbjH6f5L80XAV1KYIdWt7d5KLVjy/4zCNBaqq8zMJdEdbay8cJr/v9CUBw7/vX2t5Zua+SR5WVVdlcinyAzK5r+u2wyVniWNkUU4mOdlae/Xw/PmZhDzHxXJ8TZJ3ttb+tbX270lemMnx4thYrrWOB7/bl6CqviPJQ5J8W/v0H0jWF4v3BZn8B9Qbht/nd0zy2qr63OiPZTiZ5IXDJa+vyeRKqAuzyb4Q6tb290m+cPgGswsyuWHxRUuuaUcZ/rfi95K8ubX2yyteelGSxww/PybJny66tp2mtfak1todW2sHMjkW/ra19m1JXpbkm4bZ9MUCtNbem+REVX3xMOmrk/xTHBfL8q4k966qPcN71un+cGws11rHw4uSPHr4pr97J/nIiss0mYOqemAml+4/rLX28RUvvSjJt1bVZ1TVnTL5go7XLKPGnaK19sbW2me31g4Mv89PJrnn8HvFsbF4f5Lk/klSVV+U5IIkH8gmj43d55php2qtfaqqvj/JX2TybWZPb629acll7TT3TfKoJG+sqtcP0348yS9kcor6u5IcT/Kfl1QfyY8leW5V/VyS12X48g7m7geSHB3+w+kdSR6byX/SOS4WrLX26qp6fpLXZnJp2euSPC3J/4ljYyGq6jlJLk5yYVWdTPLTWfv3xEuSPDiTLx74eCbHDjOyRl88KclnJPmr4cqyV7XWvq+19qaq+qNM/hPkU0ke11q7YTmVb0+r9Udrba33IsfGHK1xbDw9ydOHP3PwySSPGc5kb+rYqE+fBQcAAKA3Lr8EAADomFAHAADQMaEOAACgY0IdAABAx4Q6AACAjgl1AGwLVXVDVb1+xeOJq8xzcVW9ePj5Yafnqaq9VfXqqnpdVd2vql5SVbddZ1vfV1WPnt/eAMD0/EkDALaFqrqmtXbLc8xzcZIfaa095Kzp35rka1pr3z3HEgFgLpypA2Bbq6oHVtVbquq1SR6xYvp3VNVvVNU9kvxikocPZ/huXlVXVdWFw3yPrqp/qKo3VNUfDNOeXFU/Mvx8j6p61TDPH1fVZy5hNwHYwYQ6ALaLm591+eW3VNXNkvxOkocmOZjkc89eqLX2+iQ/leQPW2v3aK194vRrVXXXJD+Z5AGttbsnecIq231Wkh9rrX1Jkjcm+emZ7xkArGP3sgsAgBn5RGvtHisnDGfh3tlae9vw/EiSwxtY5wOSPK+19oEkaa198Kz13ybJbVtrfzdMemaS522yfgDYFGfqAAAAOibUAbCdvSXJgar6guH5Ize4/N8m+eaq+qwkqarbrXyxtfaRJB+qqvsNkx6V5O8CAAvk8ksAtoubV9XrVzz/89baE6vqcJL/U1UfT3J5kltNu8LW2puq6rIkf1dVNyR5XZLvOGu2xyT57arak+QdSR67lZ0AgI3yJw0AAAA65vJLAACAjgl1AAAAHRPqAAAAOibUAQAAdEyoAwAA6JhQBwAA0DGhDgAAoGP/P0Ihc/ZFfByqAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 1080x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"AiCem-PYk_sW","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"k6C_zXSypKCG","colab_type":"text"},"source":["# Creating the Decision Tree for cooling load"]},{"cell_type":"code","metadata":{"id":"8V28NsEkpLgV","colab_type":"code","colab":{}},"source":["'''\n","Aqui cargamos las variables vamos a utilizar las 7 variables como variables \n","de entrenamiento y una unica variable (cooling load) como la que queremos predecir\n","'''\n","X_cooling= df.iloc[:, 0:8].values\n","y_cooling = df.iloc[:, 9:10].values"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"lfMnah2gpNar","colab_type":"code","colab":{}},"source":["'''\n","Partimos el dataset en training y testing con una proporción de \n","20% para testing y 80% para training\n","'''\n","X_train_cooling, X_test_cooling, y_train_cooling, y_test_cooling = train_test_split(X_cooling, y_cooling, test_size = 0.2, random_state = 0)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"f_SM94iKpO5x","colab_type":"code","outputId":"50c129c0-d493-48af-c899-8134da0678a7","executionInfo":{"status":"ok","timestamp":1587260731216,"user_tz":360,"elapsed":2225,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["# Verificamos el shape para ver si tenemos la cantidad correcta de variables para entrenar\n","X_cooling.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(768, 8)"]},"metadata":{"tags":[]},"execution_count":80}]},{"cell_type":"code","metadata":{"id":"2uPBwjtMpRK0","colab_type":"code","outputId":"6365fd8e-eafe-469d-f57f-baf0452d4475","executionInfo":{"status":"ok","timestamp":1587260731218,"user_tz":360,"elapsed":2219,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["# Fitting Decision Tree Regression to the dataset\n","from sklearn.tree import DecisionTreeRegressor\n","cooling_regressor = DecisionTreeRegressor(random_state = 0)\n","cooling_regressor.fit(X_train_cooling, y_train_cooling)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                      max_features=None, max_leaf_nodes=None,\n","                      min_impurity_decrease=0.0, min_impurity_split=None,\n","                      min_samples_leaf=1, min_samples_split=2,\n","                      min_weight_fraction_leaf=0.0, presort='deprecated',\n","                      random_state=0, splitter='best')"]},"metadata":{"tags":[]},"execution_count":82}]},{"cell_type":"code","metadata":{"id":"bR4_dU7Xp3jm","colab_type":"code","outputId":"67476c7f-ea31-4399-a9a1-d1f64b0eb827","executionInfo":{"status":"ok","timestamp":1587260731219,"user_tz":360,"elapsed":2215,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["# Predicting the Test set results\n","y_pred_cooling = cooling_regressor.predict(X_test_cooling)\n","y_pred_cooling"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([15.16 , 10.46 , 35.48 , 17.41 , 32.26 , 28.83 , 28.15 , 29.49 ,\n","       28.4  , 22.8  ,  6.366, 42.62 , 11.34 , 42.74 , 41.09 , 25.37 ,\n","       10.68 , 29.14 , 14.61 , 12.45 , 12.91 , 32.69 , 10.66 , 40.19 ,\n","        6.01 , 14.7  , 13.   , 14.19 , 10.7  , 39.83 , 12.59 , 13.01 ,\n","       41.3  , 12.93 , 28.57 , 36.95 , 14.22 , 36.95 , 17.14 , 10.54 ,\n","       11.59 , 39.86 , 14.58 , 26.   , 19.68 , 24.31 , 10.67 , 12.95 ,\n","       28.05 , 32.15 , 32.49 , 13.   , 32.46 , 14.92 , 36.95 , 10.36 ,\n","       15.55 , 26.97 , 38.33 , 14.47 , 15.09 , 12.35 , 32.21 , 10.37 ,\n","       12.41 , 11.98 , 39.04 , 11.14 , 27.03 , 39.81 , 32.82 , 10.68 ,\n","       24.37 , 17.23 , 15.32 , 25.98 , 32.82 , 39.01 , 32.82 , 14.51 ,\n","       36.57 , 29.01 , 11.68 , 13.99 , 28.91 , 25.98 , 24.04 , 29.9  ,\n","       13.04 , 17.23 , 14.4  , 27.03 , 12.43 , 24.59 , 39.97 , 16.76 ,\n","       29.67 , 14.71 ,  7.1  , 36.86 , 36.97 , 23.75 , 19.95 , 32.12 ,\n","       10.37 , 28.4  , 41.09 , 13.02 , 12.41 , 15.55 , 18.19 , 32.46 ,\n","       32.74 , 15.12 , 12.1  , 15.12 , 13.18 , 36.71 , 27.03 , 39.72 ,\n","       35.73 , 12.3  , 12.63 , 36.57 , 12.41 , 40.4  , 14.44 , 28.15 ,\n","       12.3  , 31.81 , 32.94 , 24.59 , 35.89 , 11.98 , 36.06 ,  7.18 ,\n","       28.91 , 24.59 , 32.38 , 14.07 , 17.52 , 19.36 , 28.05 , 10.8  ,\n","       37.12 , 16.55 , 29.87 , 36.13 , 12.85 , 13.91 , 28.15 , 11.42 ,\n","       13.99 , 14.66 ])"]},"metadata":{"tags":[]},"execution_count":83}]},{"cell_type":"code","metadata":{"id":"0yVncrrNqGKk","colab_type":"code","colab":{}},"source":["'''\n"," Creamos un dataframe que contenga los resultados reales del testing y los \n"," resultados de la prediccion que realizamos esto es para luego poder calcular\n"," el mse, rmse, mae\n","'''\n","df_cooling = pd.DataFrame()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"pfF5Mtr8qcxH","colab_type":"code","colab":{}},"source":["df_cooling['original_values'] = y_test_cooling.flatten()\n","df_cooling['Predicted_Values'] = y_pred_cooling"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"iNvNr99iqd3W","colab_type":"code","outputId":"d6cbdeb3-f9f4-48a8-c952-1d836d0dfbfd","executionInfo":{"status":"ok","timestamp":1587260731220,"user_tz":360,"elapsed":2207,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["df_cooling"],"execution_count":0,"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>original_values</th>\n","      <th>Predicted_Values</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>15.18</td>\n","      <td>15.16</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>10.32</td>\n","      <td>10.46</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>37.26</td>\n","      <td>35.48</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>16.95</td>\n","      <td>17.41</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>32.26</td>\n","      <td>32.26</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>149</th>\n","      <td>14.33</td>\n","      <td>13.91</td>\n","    </tr>\n","    <tr>\n","      <th>150</th>\n","      <td>28.15</td>\n","      <td>28.15</td>\n","    </tr>\n","    <tr>\n","      <th>151</th>\n","      <td>11.33</td>\n","      <td>11.42</td>\n","    </tr>\n","    <tr>\n","      <th>152</th>\n","      <td>13.86</td>\n","      <td>13.99</td>\n","    </tr>\n","    <tr>\n","      <th>153</th>\n","      <td>14.34</td>\n","      <td>14.66</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>154 rows × 2 columns</p>\n","</div>"],"text/plain":["     original_values  Predicted_Values\n","0              15.18             15.16\n","1              10.32             10.46\n","2              37.26             35.48\n","3              16.95             17.41\n","4              32.26             32.26\n","..               ...               ...\n","149            14.33             13.91\n","150            28.15             28.15\n","151            11.33             11.42\n","152            13.86             13.99\n","153            14.34             14.66\n","\n","[154 rows x 2 columns]"]},"metadata":{"tags":[]},"execution_count":86}]},{"cell_type":"code","metadata":{"id":"vzxDgyLFqfOm","colab_type":"code","outputId":"81f498fc-2945-4adc-fa33-411483ab1f58","executionInfo":{"status":"ok","timestamp":1587260731220,"user_tz":360,"elapsed":2204,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["'''\n","Todos los calculos que se van a realizar posteriormente \n","nos ayudaran a poder ver el performance del modelo\n","'''\n","\n","# Calculamos el Mean squared Error\n","mse_cooling = mean_squared_error(df_cooling['original_values'], df_cooling['Predicted_Values'])\n","mse_cooling"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.40367503896103873"]},"metadata":{"tags":[]},"execution_count":87}]},{"cell_type":"code","metadata":{"id":"5S0gFwULqhNm","colab_type":"code","outputId":"bb895d4c-282d-4be2-f145-659ea7488aad","executionInfo":{"status":"ok","timestamp":1587260731221,"user_tz":360,"elapsed":2201,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["# Calculamos el Mean Absolute Error\n","mae_cooling = mean_absolute_error(df_cooling['original_values'], df_cooling['Predicted_Values'])\n","mae_cooling"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.39996103896103896"]},"metadata":{"tags":[]},"execution_count":88}]},{"cell_type":"code","metadata":{"id":"buyuUxwTqicU","colab_type":"code","outputId":"f45fef30-7330-4579-ee91-9e5808eec9ad","executionInfo":{"status":"ok","timestamp":1587260731221,"user_tz":360,"elapsed":2197,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["# Calculamos el Root Mean Squared Error \n","root_mean_squared_error = sqrt(mse_cooling)\n","root_mean_squared_error"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.6353542625661992"]},"metadata":{"tags":[]},"execution_count":89}]},{"cell_type":"code","metadata":{"id":"9tf5394_qkHb","colab_type":"code","outputId":"8e58202c-6624-46fa-a5bf-6af1b078d5a7","executionInfo":{"status":"ok","timestamp":1587260731612,"user_tz":360,"elapsed":2584,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["'''\n","Esta grafica nos ayudara a poder visualizar los resultado de nuestro \n","modelo, tenemos dos graficas una que tiene una linea (azul) que esta \n","representa los valores predichos esta nos ayuda a poder ver las predicciones\n","y ver como es su comportamiento.\n","\n","En la segunda grafica podemos observar las predicciones pero ahora en un \n","scatterplot y esto nos ayudara a confirmar si estamos haciendo \n","overfitting y si que tanto se alinean nuestras predicciones \n","con el valor real.\n","'''\n","fig = plt.figure(figsize=(15,10))\n","ax = fig.add_subplot(111)\n","ax.scatter(np.arange(0, y_test_cooling.size), y_test_cooling, color = 'red')\n","ax.plot(np.arange(0, y_test_cooling.size), y_pred_cooling, color = 'blue')\n","plt.title('Predicciones cooling Load Vs Valores Reales')\n","plt.xlabel('Edificio')\n","plt.ylabel('Cooling Load')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Cooling Load')"]},"metadata":{"tags":[]},"execution_count":90},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"Kr_P30VQrPBX","colab_type":"code","outputId":"46aaa8c1-85d3-49f9-f7ac-f29664dd09c1","executionInfo":{"status":"ok","timestamp":1587260731946,"user_tz":360,"elapsed":2914,"user":{"displayName":"Miguel Angel Porras Melgar","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi9s0abNCSnAJqo2FKE7O0MdOUsS5V-jXzMwRks6A=s64","userId":"11974207524380260029"}},"colab":{"base_uri":"https://localhost:8080/"}},"source":["fig = plt.figure(figsize=(15,10))\n","ax = fig.add_subplot(111)\n","ax.scatter(np.arange(0, y_test_cooling.size), y_test_cooling, color = 'red')\n","ax.scatter(np.arange(0, y_test_cooling.size), y_pred_cooling, color = 'blue')\n","plt.title('Predicciones cooling Load Vs Valores Reales')\n","plt.xlabel('Edificio')\n","plt.ylabel('Cooling Load')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Cooling Load')"]},"metadata":{"tags":[]},"execution_count":91},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x720 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"xVxdGTB8rWEZ","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}