Red_Neuronal_Champions.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"id":"171b0a82","metadata":{"id":"171b0a82"},"outputs":[],"source":["# Importo librerías\n","import numpy as np \n","import matplotlib.pyplot as plt\n","from sklearn.model_selection import train_test_split, GridSearchCV\n","from sklearn.tree import DecisionTreeRegressor\n","from sklearn.metrics import r2_score\n","import pandas as pd\n","from sklearn.model_selection import train_test_split\n","from sklearn.preprocessing import LabelEncoder, StandardScaler\n","from sklearn.model_selection import GridSearchCV\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.neighbors import KNeighborsRegressor\n","from sklearn.metrics import mean_absolute_error\n","import sklearn.metrics as metrics\n","from IPython.core.display import display, HTML\n","import pandas as pd\n","import seaborn as sns\n","import matplotlib.pyplot as plt\n","%matplotlib inline\n","import numpy as np\n","import warnings\n","warnings.filterwarnings('ignore')\n","from scipy.stats import shapiro\n","from sklearn.datasets import load_iris\n","from sklearn.preprocessing import StandardScaler\n","import pandas as pd\n","import numpy as np\n","import seaborn as sns\n","import matplotlib.pyplot as plt\n","from sklearn.decomposition import PCA"]},{"cell_type":"markdown","id":"5c7ed2dd","metadata":{"id":"5c7ed2dd"},"source":["### ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ###"]},{"cell_type":"markdown","id":"c8883dd3","metadata":{"id":"c8883dd3"},"source":["### 1.- Lee un fichero xxx.csv o crea uno que contenga al menos 30 filas por 10 columnas, de las cuales una columna tipo object debe tener dos opciones y otras dos columnas tipo object debe contener tres o más opciones. Al menos dos columnas debe contener nulos. ###"]},{"cell_type":"code","execution_count":null,"id":"a356e53b","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"a356e53b","outputId":"5be32967-0559-41c5-9602-0d3afb3d5331","executionInfo":{"status":"ok","timestamp":1678900264138,"user_tz":-60,"elapsed":515,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["    ID              EQUIPO        PAIS  PARTIDOS_JUGADOS  GANADOS  EMPATES  \\\n","0    1     Manchester City  INGLATERRA                38       29        6   \n","1    2           Liverpool  INGLATERRA                38       28        8   \n","2    3       Bayern Munich    ALEMANIA                38       24        5   \n","3    4           Paris S-G     FRANCIA                38       26        8   \n","4    5         Real Madrid     ESPAÃA                38       26        8   \n","5    6               Milan      ITALIA                38       26        8   \n","6    7               Inter      ITALIA                38       25        9   \n","7    8              Napoli      ITALIA                38       24        7   \n","8    9            Dortmund    ALEMANIA                38       22        3   \n","9   10             Chelsea  INGLATERRA                38       21       11   \n","10  11           Barcelona     ESPAÃA                38       21       10   \n","11  12          Leverkusen    ALEMANIA                38       19       10   \n","12  13           Tottenham  INGLATERRA                38       22        5   \n","13  14           Marseille     FRANCIA                38       21        8   \n","14  15  Atletico de Madrid     ESPAÃA                38       21        8   \n","15  16             Sevilla     ESPAÃA                38       18       16   \n","16  17            Juventus      ITALIA                38       20       10   \n","17  18              Monaco     FRANCIA                38       20        9   \n","18  19             Arsenal  INGLATERRA                38       22        3   \n","19  20              Rennes     FRANCIA                38       20        6   \n","20  21                Nice     FRANCIA                38       20        7   \n","21  22          RB Leipzig    ALEMANIA                38       17        7   \n","22  23               Betis     ESPAÃA                38       19        8   \n","23  24               Lazio      ITALIA                38       18       10   \n","24  25        Union Berlin    ALEMANIA                38       18        9   \n","25  26          Strasbourg     FRANCIA                38       17       12   \n","26  27                Roma      ITALIA                38       18        9   \n","27  28                Lens     FRANCIA                38       17       11   \n","28  29          Fiorentina      ITALIA                38       19        5   \n","29  30       Real Sociedad     ESPAÃA                38       17       11   \n","30  31            Freiburg    ALEMANIA                38       15       11   \n","31  32                Lyon     FRANCIA                38       17       11   \n","32  33          Villarreal     ESPAÃA                38       16       11   \n","33  34            Atalanta      ITALIA                38       16       11   \n","34  36      Manchester Utd  INGLATERRA                38       16       10   \n","\n","    PERDIDOS  GOLES_A_FAVOR  GOLES_EN_CONTRA  PUNTOS GANADOR CHAMPIONS  \n","0          3             99               26      93      si        si  \n","1          2             94               26      92      no        si  \n","2          5             97               37      77      si        si  \n","3          4             90               36      86      si        si  \n","4          4             80               31      86      si        si  \n","5          4             69               31      86      no        no  \n","6          4             84               32      84      no        si  \n","7          7             74               31      79      no        no  \n","8          9             85               52      69      no        no  \n","9          6             76               33      74      no        si  \n","10         7           5444               38      73      no        no  \n","11         8             80               47      64      no        no  \n","12        11             69               40      71      no        no  \n","13         9             63               38      71      no        no  \n","14         9             65               43      71      no        si  \n","15         4             53               30      70      no        no  \n","16         8             57               37      70      no        si  \n","17         9             65               40      69      no        no  \n","18        13             61               48      69      no        no  \n","19        12             82               40      66      no        no  \n","20        11             52               36      66      no        no  \n","21        10             72               37      58      si        no  \n","22        11             62               40      65      no        no  \n","23        10             77               58      64      no        no  \n","24         9             44               44      57      si        no  \n","25         9             60               43      63      no        no  \n","26        11             59               43      63      no        no  \n","27        10             62               48      62      no        no  \n","28        14             59               51      62      no        no  \n","29        10             40               37      62      no        no  \n","30         9             58               46      55      si        no  \n","31        10             66               51      61      no        no  \n","32        11             63               37      59      no        si  \n","33        11             65               48      59      no        si  \n","34        12             57               57      58      no        no  "],"text/html":["\n","  <div id=\"df-f3a12cb6-f638-40e0-a769-935562be1b54\">\n","    <div class=\"colab-df-container\">\n","      <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>EQUIPO</th>\n","      <th>PAIS</th>\n","      <th>PARTIDOS_JUGADOS</th>\n","      <th>GANADOS</th>\n","      <th>EMPATES</th>\n","      <th>PERDIDOS</th>\n","      <th>GOLES_A_FAVOR</th>\n","      <th>GOLES_EN_CONTRA</th>\n","      <th>PUNTOS</th>\n","      <th>GANADOR</th>\n","      <th>CHAMPIONS</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Manchester City</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>29</td>\n","      <td>6</td>\n","      <td>3</td>\n","      <td>99</td>\n","      <td>26</td>\n","      <td>93</td>\n","      <td>si</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>Liverpool</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>28</td>\n","      <td>8</td>\n","      <td>2</td>\n","      <td>94</td>\n","      <td>26</td>\n","      <td>92</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3</td>\n","      <td>Bayern Munich</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>24</td>\n","      <td>5</td>\n","      <td>5</td>\n","      <td>97</td>\n","      <td>37</td>\n","      <td>77</td>\n","      <td>si</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>Paris S-G</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>90</td>\n","      <td>36</td>\n","      <td>86</td>\n","      <td>si</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5</td>\n","      <td>Real Madrid</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>80</td>\n","      <td>31</td>\n","      <td>86</td>\n","      <td>si</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>6</td>\n","      <td>Milan</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>69</td>\n","      <td>31</td>\n","      <td>86</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>7</td>\n","      <td>Inter</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>25</td>\n","      <td>9</td>\n","      <td>4</td>\n","      <td>84</td>\n","      <td>32</td>\n","      <td>84</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>8</td>\n","      <td>Napoli</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>24</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>74</td>\n","      <td>31</td>\n","      <td>79</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>9</td>\n","      <td>Dortmund</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>3</td>\n","      <td>9</td>\n","      <td>85</td>\n","      <td>52</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>10</td>\n","      <td>Chelsea</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>11</td>\n","      <td>6</td>\n","      <td>76</td>\n","      <td>33</td>\n","      <td>74</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>11</td>\n","      <td>Barcelona</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>10</td>\n","      <td>7</td>\n","      <td>5444</td>\n","      <td>38</td>\n","      <td>73</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>12</td>\n","      <td>Leverkusen</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>10</td>\n","      <td>8</td>\n","      <td>80</td>\n","      <td>47</td>\n","      <td>64</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>13</td>\n","      <td>Tottenham</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>5</td>\n","      <td>11</td>\n","      <td>69</td>\n","      <td>40</td>\n","      <td>71</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>14</td>\n","      <td>Marseille</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>8</td>\n","      <td>9</td>\n","      <td>63</td>\n","      <td>38</td>\n","      <td>71</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>15</td>\n","      <td>Atletico de Madrid</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>8</td>\n","      <td>9</td>\n","      <td>65</td>\n","      <td>43</td>\n","      <td>71</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>16</td>\n","      <td>Sevilla</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>16</td>\n","      <td>4</td>\n","      <td>53</td>\n","      <td>30</td>\n","      <td>70</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>17</td>\n","      <td>Juventus</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>10</td>\n","      <td>8</td>\n","      <td>57</td>\n","      <td>37</td>\n","      <td>70</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>18</td>\n","      <td>Monaco</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>9</td>\n","      <td>9</td>\n","      <td>65</td>\n","      <td>40</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>19</td>\n","      <td>Arsenal</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>3</td>\n","      <td>13</td>\n","      <td>61</td>\n","      <td>48</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>20</td>\n","      <td>Rennes</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>6</td>\n","      <td>12</td>\n","      <td>82</td>\n","      <td>40</td>\n","      <td>66</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>21</td>\n","      <td>Nice</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>7</td>\n","      <td>11</td>\n","      <td>52</td>\n","      <td>36</td>\n","      <td>66</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>22</td>\n","      <td>RB Leipzig</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>72</td>\n","      <td>37</td>\n","      <td>58</td>\n","      <td>si</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>22</th>\n","      <td>23</td>\n","      <td>Betis</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>8</td>\n","      <td>11</td>\n","      <td>62</td>\n","      <td>40</td>\n","      <td>65</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>24</td>\n","      <td>Lazio</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>10</td>\n","      <td>10</td>\n","      <td>77</td>\n","      <td>58</td>\n","      <td>64</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>25</td>\n","      <td>Union Berlin</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>9</td>\n","      <td>9</td>\n","      <td>44</td>\n","      <td>44</td>\n","      <td>57</td>\n","      <td>si</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>26</td>\n","      <td>Strasbourg</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>12</td>\n","      <td>9</td>\n","      <td>60</td>\n","      <td>43</td>\n","      <td>63</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>27</td>\n","      <td>Roma</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>9</td>\n","      <td>11</td>\n","      <td>59</td>\n","      <td>43</td>\n","      <td>63</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>28</td>\n","      <td>Lens</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>62</td>\n","      <td>48</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>28</th>\n","      <td>29</td>\n","      <td>Fiorentina</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>5</td>\n","      <td>14</td>\n","      <td>59</td>\n","      <td>51</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>30</td>\n","      <td>Real Sociedad</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>40</td>\n","      <td>37</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>31</td>\n","      <td>Freiburg</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>15</td>\n","      <td>11</td>\n","      <td>9</td>\n","      <td>58</td>\n","      <td>46</td>\n","      <td>55</td>\n","      <td>si</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>31</th>\n","      <td>32</td>\n","      <td>Lyon</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>66</td>\n","      <td>51</td>\n","      <td>61</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>33</td>\n","      <td>Villarreal</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>11</td>\n","      <td>11</td>\n","      <td>63</td>\n","      <td>37</td>\n","      <td>59</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>34</td>\n","      <td>Atalanta</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>11</td>\n","      <td>11</td>\n","      <td>65</td>\n","      <td>48</td>\n","      <td>59</td>\n","      <td>no</td>\n","      <td>si</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>36</td>\n","      <td>Manchester Utd</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>10</td>\n","      <td>12</td>\n","      <td>57</td>\n","      <td>57</td>\n","      <td>58</td>\n","      <td>no</td>\n","      <td>no</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f3a12cb6-f638-40e0-a769-935562be1b54')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 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Al menos dos\n","# columnas debe contener nulos.\n","\n","archivo= \"Champions.csv\"\n","df = pd.read_csv(archivo, encoding='latin-1')\n","df"]},{"cell_type":"markdown","id":"97e667a7","metadata":{"id":"97e667a7"},"source":["### ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ###"]},{"cell_type":"markdown","id":"a6c3dfd9","metadata":{"id":"a6c3dfd9"},"source":["### 2.- Transforma las columnas object a categóricas y posteriormente a numéricas. Una columna categórica de dos opciones a columnas dummy y elimina dicha columna categórica. Una columna categórica de mas de dos opciones mediante cat codes. La otra columna categórica de mas de dos opciones mediante LabelEncoder. ###"]},{"cell_type":"markdown","id":"c507ef23","metadata":{"id":"c507ef23"},"source":["### 3.- Rellena los nulos ###\n"]},{"cell_type":"code","execution_count":null,"id":"9a666ce4","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9a666ce4","outputId":"8e22b1a2-5224-420f-add1-8f2dea21ecd6","executionInfo":{"status":"ok","timestamp":1678900270326,"user_tz":-60,"elapsed":281,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                   int64\n","EQUIPO              object\n","PAIS                object\n","PARTIDOS_JUGADOS     int64\n","GANADOS              int64\n","EMPATES              int64\n","PERDIDOS             int64\n","GOLES_A_FAVOR        int64\n","GOLES_EN_CONTRA      int64\n","PUNTOS               int64\n","GANADOR             object\n","CHAMPIONS           object\n","dtype: object"]},"metadata":{},"execution_count":3}],"source":["# 2.- Transforma las columnas object a categóricas y posteriormente a numéricas.\n","# Una columna categórica de dos opciones a columnas dummy y elimina dicha\n","# columna categórica. Una columna categórica de mas de dos opciones mediante\n","# cat codes. La otra columna categórica de mas de dos opciones mediante\n","# LabelEncoder.\n","\n","df.dtypes"]},{"cell_type":"code","execution_count":null,"id":"effb3a3b","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"effb3a3b","outputId":"f8625c19-4222-464f-e491-c4c35dca0e29","executionInfo":{"status":"ok","timestamp":1678900272397,"user_tz":-60,"elapsed":4,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                   int64\n","EQUIPO              object\n","PAIS                object\n","PARTIDOS_JUGADOS     int64\n","GANADOS              int64\n","EMPATES              int64\n","PERDIDOS             int64\n","GOLES_A_FAVOR        int64\n","GOLES_EN_CONTRA      int64\n","PUNTOS               int64\n","CHAMPIONS           object\n","GANADOR_no           uint8\n","GANADOR_si           uint8\n","dtype: object"]},"metadata":{},"execution_count":4}],"source":["# · Usamos las Dummy · #\n","\n","df_dummy=pd.get_dummies(df.GANADOR,prefix=\"GANADOR\")\n","df=pd.concat([df, df_dummy],axis=1)\n","df=df.drop([\"GANADOR\"],axis=1)\n","\n","df.dtypes"]},{"cell_type":"code","execution_count":null,"id":"6f2fc4bf","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"6f2fc4bf","outputId":"832efd87-c801-443f-9bd1-0afc1c0dbef0","executionInfo":{"status":"ok","timestamp":1678900274691,"user_tz":-60,"elapsed":393,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["    ID              EQUIPO        PAIS  PARTIDOS_JUGADOS  GANADOS  EMPATES  \\\n","0    1     Manchester City  INGLATERRA                38       29        6   \n","1    2           Liverpool  INGLATERRA                38       28        8   \n","2    3       Bayern Munich    ALEMANIA                38       24        5   \n","3    4           Paris S-G     FRANCIA                38       26        8   \n","4    5         Real Madrid     ESPAÃA                38       26        8   \n","5    6               Milan      ITALIA                38       26        8   \n","6    7               Inter      ITALIA                38       25        9   \n","7    8              Napoli      ITALIA                38       24        7   \n","8    9            Dortmund    ALEMANIA                38       22        3   \n","9   10             Chelsea  INGLATERRA                38       21       11   \n","10  11           Barcelona     ESPAÃA                38       21       10   \n","11  12          Leverkusen    ALEMANIA                38       19       10   \n","12  13           Tottenham  INGLATERRA                38       22        5   \n","13  14           Marseille     FRANCIA                38       21        8   \n","14  15  Atletico de Madrid     ESPAÃA                38       21        8   \n","15  16             Sevilla     ESPAÃA                38       18       16   \n","16  17            Juventus      ITALIA                38       20       10   \n","17  18              Monaco     FRANCIA                38       20        9   \n","18  19             Arsenal  INGLATERRA                38       22        3   \n","19  20              Rennes     FRANCIA                38       20        6   \n","20  21                Nice     FRANCIA                38       20        7   \n","21  22          RB Leipzig    ALEMANIA                38       17        7   \n","22  23               Betis     ESPAÃA                38       19        8   \n","23  24               Lazio      ITALIA                38       18       10   \n","24  25        Union Berlin    ALEMANIA                38       18        9   \n","25  26          Strasbourg     FRANCIA                38       17       12   \n","26  27                Roma      ITALIA                38       18        9   \n","27  28                Lens     FRANCIA                38       17       11   \n","28  29          Fiorentina      ITALIA                38       19        5   \n","29  30       Real Sociedad     ESPAÃA                38       17       11   \n","30  31            Freiburg    ALEMANIA                38       15       11   \n","31  32                Lyon     FRANCIA                38       17       11   \n","32  33          Villarreal     ESPAÃA                38       16       11   \n","33  34            Atalanta      ITALIA                38       16       11   \n","34  36      Manchester Utd  INGLATERRA                38       16       10   \n","\n","    PERDIDOS  GOLES_A_FAVOR  GOLES_EN_CONTRA  PUNTOS CHAMPIONS  GANADOR_no  \\\n","0          3             99               26      93        si           0   \n","1          2             94               26      92        si           1   \n","2          5             97               37      77        si           0   \n","3          4             90               36      86        si           0   \n","4          4             80               31      86        si           0   \n","5          4             69               31      86        no           1   \n","6          4             84               32      84        si           1   \n","7          7             74               31      79        no           1   \n","8          9             85               52      69        no           1   \n","9          6             76               33      74        si           1   \n","10         7           5444               38      73        no           1   \n","11         8             80               47      64        no           1   \n","12        11             69               40      71        no           1   \n","13         9             63               38      71        no           1   \n","14         9             65               43      71        si           1   \n","15         4             53               30      70        no           1   \n","16         8             57               37      70        si           1   \n","17         9             65               40      69        no           1   \n","18        13             61               48      69        no           1   \n","19        12             82               40      66        no           1   \n","20        11             52               36      66        no           1   \n","21        10             72               37      58        no           0   \n","22        11             62               40      65        no           1   \n","23        10             77               58      64        no           1   \n","24         9             44               44      57        no           0   \n","25         9             60               43      63        no           1   \n","26        11             59               43      63        no           1   \n","27        10             62               48      62        no           1   \n","28        14             59               51      62        no           1   \n","29        10             40               37      62        no           1   \n","30         9             58               46      55        no           0   \n","31        10             66               51      61        no           1   \n","32        11             63               37      59        si           1   \n","33        11             65               48      59        si           1   \n","34        12             57               57      58        no           1   \n","\n","    GANADOR_si  \n","0            1  \n","1            0  \n","2            1  \n","3            1  \n","4            1  \n","5            0  \n","6            0  \n","7            0  \n","8            0  \n","9            0  \n","10           0  \n","11           0  \n","12           0  \n","13           0  \n","14           0  \n","15           0  \n","16           0  \n","17           0  \n","18           0  \n","19           0  \n","20           0  \n","21           1  \n","22           0  \n","23           0  \n","24           1  \n","25           0  \n","26           0  \n","27           0  \n","28           0  \n","29           0  \n","30           1  \n","31           0  \n","32           0  \n","33           0  \n","34           0  "],"text/html":["\n","  <div id=\"df-1f785467-287a-4689-9634-8f8c30395289\">\n","    <div class=\"colab-df-container\">\n","      <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>EQUIPO</th>\n","      <th>PAIS</th>\n","      <th>PARTIDOS_JUGADOS</th>\n","      <th>GANADOS</th>\n","      <th>EMPATES</th>\n","      <th>PERDIDOS</th>\n","      <th>GOLES_A_FAVOR</th>\n","      <th>GOLES_EN_CONTRA</th>\n","      <th>PUNTOS</th>\n","      <th>CHAMPIONS</th>\n","      <th>GANADOR_no</th>\n","      <th>GANADOR_si</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Manchester City</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>29</td>\n","      <td>6</td>\n","      <td>3</td>\n","      <td>99</td>\n","      <td>26</td>\n","      <td>93</td>\n","      <td>si</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>Liverpool</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>28</td>\n","      <td>8</td>\n","      <td>2</td>\n","      <td>94</td>\n","      <td>26</td>\n","      <td>92</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3</td>\n","      <td>Bayern Munich</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>24</td>\n","      <td>5</td>\n","      <td>5</td>\n","      <td>97</td>\n","      <td>37</td>\n","      <td>77</td>\n","      <td>si</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>Paris S-G</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>90</td>\n","      <td>36</td>\n","      <td>86</td>\n","      <td>si</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5</td>\n","      <td>Real Madrid</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>80</td>\n","      <td>31</td>\n","      <td>86</td>\n","      <td>si</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>6</td>\n","      <td>Milan</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>26</td>\n","      <td>8</td>\n","      <td>4</td>\n","      <td>69</td>\n","      <td>31</td>\n","      <td>86</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>7</td>\n","      <td>Inter</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>25</td>\n","      <td>9</td>\n","      <td>4</td>\n","      <td>84</td>\n","      <td>32</td>\n","      <td>84</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>8</td>\n","      <td>Napoli</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>24</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>74</td>\n","      <td>31</td>\n","      <td>79</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>9</td>\n","      <td>Dortmund</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>3</td>\n","      <td>9</td>\n","      <td>85</td>\n","      <td>52</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>10</td>\n","      <td>Chelsea</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>11</td>\n","      <td>6</td>\n","      <td>76</td>\n","      <td>33</td>\n","      <td>74</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>11</td>\n","      <td>Barcelona</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>10</td>\n","      <td>7</td>\n","      <td>5444</td>\n","      <td>38</td>\n","      <td>73</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>12</td>\n","      <td>Leverkusen</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>10</td>\n","      <td>8</td>\n","      <td>80</td>\n","      <td>47</td>\n","      <td>64</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>13</td>\n","      <td>Tottenham</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>5</td>\n","      <td>11</td>\n","      <td>69</td>\n","      <td>40</td>\n","      <td>71</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>14</td>\n","      <td>Marseille</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>8</td>\n","      <td>9</td>\n","      <td>63</td>\n","      <td>38</td>\n","      <td>71</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>15</td>\n","      <td>Atletico de Madrid</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>21</td>\n","      <td>8</td>\n","      <td>9</td>\n","      <td>65</td>\n","      <td>43</td>\n","      <td>71</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>16</td>\n","      <td>Sevilla</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>16</td>\n","      <td>4</td>\n","      <td>53</td>\n","      <td>30</td>\n","      <td>70</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>17</td>\n","      <td>Juventus</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>10</td>\n","      <td>8</td>\n","      <td>57</td>\n","      <td>37</td>\n","      <td>70</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>18</td>\n","      <td>Monaco</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>9</td>\n","      <td>9</td>\n","      <td>65</td>\n","      <td>40</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>19</td>\n","      <td>Arsenal</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>22</td>\n","      <td>3</td>\n","      <td>13</td>\n","      <td>61</td>\n","      <td>48</td>\n","      <td>69</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>20</td>\n","      <td>Rennes</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>6</td>\n","      <td>12</td>\n","      <td>82</td>\n","      <td>40</td>\n","      <td>66</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>21</td>\n","      <td>Nice</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>20</td>\n","      <td>7</td>\n","      <td>11</td>\n","      <td>52</td>\n","      <td>36</td>\n","      <td>66</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>22</td>\n","      <td>RB Leipzig</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>72</td>\n","      <td>37</td>\n","      <td>58</td>\n","      <td>no</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>22</th>\n","      <td>23</td>\n","      <td>Betis</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>8</td>\n","      <td>11</td>\n","      <td>62</td>\n","      <td>40</td>\n","      <td>65</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>24</td>\n","      <td>Lazio</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>10</td>\n","      <td>10</td>\n","      <td>77</td>\n","      <td>58</td>\n","      <td>64</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>25</td>\n","      <td>Union Berlin</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>9</td>\n","      <td>9</td>\n","      <td>44</td>\n","      <td>44</td>\n","      <td>57</td>\n","      <td>no</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>26</td>\n","      <td>Strasbourg</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>12</td>\n","      <td>9</td>\n","      <td>60</td>\n","      <td>43</td>\n","      <td>63</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>27</td>\n","      <td>Roma</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>18</td>\n","      <td>9</td>\n","      <td>11</td>\n","      <td>59</td>\n","      <td>43</td>\n","      <td>63</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>28</td>\n","      <td>Lens</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>62</td>\n","      <td>48</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>28</th>\n","      <td>29</td>\n","      <td>Fiorentina</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>19</td>\n","      <td>5</td>\n","      <td>14</td>\n","      <td>59</td>\n","      <td>51</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>30</td>\n","      <td>Real Sociedad</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>40</td>\n","      <td>37</td>\n","      <td>62</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>31</td>\n","      <td>Freiburg</td>\n","      <td>ALEMANIA</td>\n","      <td>38</td>\n","      <td>15</td>\n","      <td>11</td>\n","      <td>9</td>\n","      <td>58</td>\n","      <td>46</td>\n","      <td>55</td>\n","      <td>no</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>31</th>\n","      <td>32</td>\n","      <td>Lyon</td>\n","      <td>FRANCIA</td>\n","      <td>38</td>\n","      <td>17</td>\n","      <td>11</td>\n","      <td>10</td>\n","      <td>66</td>\n","      <td>51</td>\n","      <td>61</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>33</td>\n","      <td>Villarreal</td>\n","      <td>ESPAÃA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>11</td>\n","      <td>11</td>\n","      <td>63</td>\n","      <td>37</td>\n","      <td>59</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>34</td>\n","      <td>Atalanta</td>\n","      <td>ITALIA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>11</td>\n","      <td>11</td>\n","      <td>65</td>\n","      <td>48</td>\n","      <td>59</td>\n","      <td>si</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>36</td>\n","      <td>Manchester Utd</td>\n","      <td>INGLATERRA</td>\n","      <td>38</td>\n","      <td>16</td>\n","      <td>10</td>\n","      <td>12</td>\n","      <td>57</td>\n","      <td>57</td>\n","      <td>58</td>\n","      <td>no</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1f785467-287a-4689-9634-8f8c30395289')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path 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Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                   int64\n","EQUIPO              object\n","PAIS                object\n","PARTIDOS_JUGADOS     int64\n","GANADOS              int64\n","EMPATES              int64\n","PERDIDOS             int64\n","GOLES_A_FAVOR        int64\n","GOLES_EN_CONTRA      int64\n","PUNTOS               int64\n","CHAMPIONS           object\n","GANADOR_no           uint8\n","GANADOR_si           uint8\n","dtype: object"]},"metadata":{},"execution_count":6}],"source":["df.dtypes"]},{"cell_type":"code","execution_count":null,"id":"47852e01","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"47852e01","outputId":"c4fe65ab-ddb8-4bf8-9aa5-d4543abc6ab2","executionInfo":{"status":"ok","timestamp":1678900278448,"user_tz":-60,"elapsed":3,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                   int64\n","EQUIPO                int8\n","PAIS                object\n","PARTIDOS_JUGADOS     int64\n","GANADOS              int64\n","EMPATES              int64\n","PERDIDOS             int64\n","GOLES_A_FAVOR        int64\n","GOLES_EN_CONTRA      int64\n","PUNTOS               int64\n","CHAMPIONS           object\n","GANADOR_no           uint8\n","GANADOR_si           uint8\n","dtype: object"]},"metadata":{},"execution_count":7}],"source":["df[\"EQUIPO\"]=pd.Categorical(df[\"EQUIPO\"])\n","df[\"EQUIPO\"]=df[\"EQUIPO\"].cat.codes\n","\n","df.dtypes"]},{"cell_type":"code","execution_count":null,"id":"d1291f4f","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"d1291f4f","outputId":"c512a569-fda6-4242-88fc-25a86b34d2c3","executionInfo":{"status":"ok","timestamp":1678900280459,"user_tz":-60,"elapsed":3,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                  int64\n","EQUIPO               int8\n","PAIS                int64\n","PARTIDOS_JUGADOS    int64\n","GANADOS             int64\n","EMPATES             int64\n","PERDIDOS            int64\n","GOLES_A_FAVOR       int64\n","GOLES_EN_CONTRA     int64\n","PUNTOS              int64\n","CHAMPIONS           int64\n","GANADOR_no          uint8\n","GANADOR_si          uint8\n","dtype: object"]},"metadata":{},"execution_count":8}],"source":["le = LabelEncoder()\n","\n","df.PAIS = le.fit_transform(df.PAIS.values)\n","df.PARTIDOS_JUGADOS = le.fit_transform(df.PARTIDOS_JUGADOS.values)\n","df.GANADOS = le.fit_transform(df.GANADOS.values)\n","df.EMPATES = le.fit_transform(df.EMPATES.values)\n","df.PERDIDOS = le.fit_transform(df.PERDIDOS.values)\n","df.GOLES_A_FAVOR = le.fit_transform(df.GOLES_A_FAVOR.values)\n","df.GOLES_EN_CONTRA = le.fit_transform(df.GOLES_EN_CONTRA.values)\n","df.CHAMPIONS = le.fit_transform(df.CHAMPIONS.values)\n","\n","\n","df.dtypes"]},{"cell_type":"code","execution_count":null,"id":"06787f03","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"06787f03","outputId":"c087d0b2-9332-4d21-ceba-0fe3eb900a5c","executionInfo":{"status":"ok","timestamp":1678900282761,"user_tz":-60,"elapsed":6,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index([], dtype='object')"]},"metadata":{},"execution_count":9}],"source":["df.select_dtypes(exclude=['number']).columns"]},{"cell_type":"code","execution_count":null,"id":"03d8e583","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"03d8e583","outputId":"55910fe8-d67e-4253-bbdc-f6ba5c572cc6","executionInfo":{"status":"ok","timestamp":1678900285200,"user_tz":-60,"elapsed":255,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ID                  0\n","EQUIPO              0\n","PAIS                0\n","PARTIDOS_JUGADOS    0\n","GANADOS             0\n","EMPATES             0\n","PERDIDOS            0\n","GOLES_A_FAVOR       0\n","GOLES_EN_CONTRA     0\n","PUNTOS              0\n","CHAMPIONS           0\n","GANADOR_no          0\n","GANADOR_si          0\n","dtype: int64"]},"metadata":{},"execution_count":10}],"source":["df.isnull().sum()"]},{"cell_type":"markdown","id":"05ba0997","metadata":{"id":"05ba0997"},"source":["### ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ###"]},{"cell_type":"code","execution_count":null,"id":"3b66fdbd","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3b66fdbd","outputId":"136ae741-4c6e-4c58-dfe3-cdc7111fd411","executionInfo":{"status":"ok","timestamp":1678900289778,"user_tz":-60,"elapsed":253,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['ID', 'EQUIPO', 'PAIS', 'PARTIDOS_JUGADOS', 'GANADOS', 'EMPATES',\n","       'PERDIDOS', 'GOLES_A_FAVOR', 'GOLES_EN_CONTRA', 'PUNTOS', 'CHAMPIONS',\n","       'GANADOR_no', 'GANADOR_si'],\n","      dtype='object')"]},"metadata":{},"execution_count":11}],"source":["df.columns\n"]},{"cell_type":"code","execution_count":null,"id":"5e4e8793","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5e4e8793","outputId":"09f5eddb-2d9c-42e5-878c-330c38fc05f0","executionInfo":{"status":"ok","timestamp":1678900293207,"user_tz":-60,"elapsed":232,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 35 entries, 0 to 34\n","Data columns (total 10 columns):\n"," #   Column            Non-Null Count  Dtype\n","---  ------            --------------  -----\n"," 0   ID                35 non-null     int64\n"," 1   PAIS              35 non-null     int64\n"," 2   PARTIDOS_JUGADOS  35 non-null     int64\n"," 3   GANADOS           35 non-null     int64\n"," 4   EMPATES           35 non-null     int64\n"," 5   PERDIDOS          35 non-null     int64\n"," 6   GOLES_A_FAVOR     35 non-null     int64\n"," 7   GOLES_EN_CONTRA   35 non-null     int64\n"," 8   PUNTOS            35 non-null     int64\n"," 9   CHAMPIONS         35 non-null     int64\n","dtypes: int64(10)\n","memory usage: 2.9 KB\n"]}],"source":["numerics = ['int16','int32','int64','float16','float32','float64']\n","variables_numericas = df.select_dtypes(include=numerics)\n","variables_numericas.info()"]},{"cell_type":"markdown","id":"2e8d65d5","metadata":{"id":"2e8d65d5"},"source":["### 7.- Normaliza los datos numéricos y divídelos en train y test"]},{"cell_type":"code","execution_count":null,"id":"c8e035f7","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":244},"id":"c8e035f7","outputId":"eebc87e1-1281-475e-ba86-c5a4d82e1724","executionInfo":{"status":"error","timestamp":1678900297057,"user_tz":-60,"elapsed":681,"user":{"displayName":"Carlos Germán Sellers Mendo","userId":"10483787242844398475"}}},"outputs":[{"output_type":"error","ename":"NameError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m<ipython-input-13-4968608e7490>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CHAMPIONS'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mcorrelaciones_target\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmatriz_correlaciones\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mindices_inversos\u001b[0m \u001b[0;34m=\u001b[0m  \u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcorrelaciones_target\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margsort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mdiccionario\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mNameError\u001b[0m: name 'matriz_correlaciones' is not defined"]}],"source":["X = df.drop('CHAMPIONS', axis=1)\n","Y = df['CHAMPIONS']\n"]},{"cell_type":"code","execution_count":null,"id":"19cf438b","metadata":{"id":"19cf438b"},"outputs":[],"source":["obj_escalar = StandardScaler()\n","X_estandarizado = obj_escalar.fit_transform(X)\n","\n","X_train, X_test, Y_train, Y_test = train_test_split(X_estandarizado, Y, test_size=0.2, random_state=0)"]},{"cell_type":"code","source":["X_train"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ayG10G4j6_KC","outputId":"7b8e5efb-8885-4ad0-a301-223409d2f89d"},"id":"ayG10G4j6_KC","execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[-1.48081501, -1.28719181, -1.48824711,  0.        ,  0.90834052,\n","        -1.5468686 , -1.13857457,  1.61607216, -0.40435899,  0.73995597,\n","        -2.        ,  2.        ],\n","       [-0.59401515, -0.29704426, -1.48824711,  0.        , -0.36333621,\n","         0.61874744, -0.15055531,  0.78222657,  0.90203159, -0.55000559,\n","         0.5       , -0.5       ],\n","     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0.18562423, -1.46791432,  1.0601751 , -1.05755428,  1.43455066,\n","         0.5       , -0.5       ],\n","       [ 0.58838467, -0.49507377,  1.36592543,  0.        , -0.68125539,\n","         0.61874744,  0.50812419,  0.64325231,  1.99069041, -0.55000559,\n","         0.5       , -0.5       ],\n","       [-1.28374838,  0.89113279, -0.77470398,  0.        ,  1.54417889,\n","        -0.24749898, -1.46791432,  0.78222657, -1.27528604,  1.63300629,\n","        -2.        ,  2.        ],\n","       [ 0.09571808, -1.68325082,  0.6523823 ,  0.        ,  0.59042134,\n","        -1.9799918 ,  1.49614344, -0.60751607,  1.11976335, -0.05386653,\n","         0.5       , -0.5       ],\n","       [ 0.39131804,  0.79211803, -1.48824711,  0.        , -0.99917458,\n","        -0.68062218,  0.50812419,  0.22632952, -0.40435899, -1.14537247,\n","        -2.        ,  2.        ],\n","       [ 0.1942514 ,  1.0891623 , -0.06116084,  0.        , -0.04541703,\n","        -1.11374539,  1.16680369,  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2.32760098,\n","        -2.        ,  2.        ]])"]},"metadata":{},"execution_count":330}]},{"cell_type":"markdown","id":"9d2478af","metadata":{"id":"9d2478af"},"source":["### ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ###"]},{"cell_type":"markdown","source":["---\n","---\n","#Redes Neuronales keras\n","---\n","---\n"],"metadata":{"id":"J4i52yGg58w1"},"id":"J4i52yGg58w1"},{"cell_type":"code","source":["import numpy as np\n","from keras.models import Sequential\n","from keras.layers import Dense"],"metadata":{"id":"GVE-iVfT6EQD"},"id":"GVE-iVfT6EQD","execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Crea el modelo de red neuronal\n","model = Sequential()\n","model.add(Dense(3, input_dim=12, activation='relu'))\n","model.add(Dense(2, activation='relu'))\n","model.add(Dense(1, activation='sigmoid'))"],"metadata":{"id":"6DoqV0Mj6QVc"},"id":"6DoqV0Mj6QVc","execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Compila el modelo\n","model.compile(loss='mean_squared_error', optimizer='sgd', metrics=['accuracy'])"],"metadata":{"id":"iRm9Ojz66Q2j"},"id":"iRm9Ojz66Q2j","execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Entrena el modelo\n","model.fit(X_train, Y_train, epochs=1000)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"eDudM-WZ6ROl","outputId":"6a03e596-f9c8-4bbd-fc35-76df8960fc7f"},"id":"eDudM-WZ6ROl","execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/1000\n","1/1 [==============================] - 0s 469ms/step - loss: 0.3054 - accuracy: 0.6429\n","Epoch 2/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.3049 - accuracy: 0.6429\n","Epoch 3/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.3045 - accuracy: 0.6429\n","Epoch 4/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.3041 - accuracy: 0.6429\n","Epoch 5/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.3036 - accuracy: 0.6429\n","Epoch 6/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.3032 - accuracy: 0.6429\n","Epoch 7/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.3027 - accuracy: 0.6429\n","Epoch 8/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.3023 - accuracy: 0.6429\n","Epoch 9/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.3019 - accuracy: 0.6429\n","Epoch 10/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.3014 - accuracy: 0.6429\n","Epoch 11/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.3010 - accuracy: 0.6429\n","Epoch 12/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.3005 - accuracy: 0.6429\n","Epoch 13/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.3001 - accuracy: 0.6429\n","Epoch 14/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2996 - accuracy: 0.6429\n","Epoch 15/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2992 - accuracy: 0.6429\n","Epoch 16/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2987 - accuracy: 0.6429\n","Epoch 17/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2983 - accuracy: 0.6429\n","Epoch 18/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2978 - accuracy: 0.6429\n","Epoch 19/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2974 - accuracy: 0.6429\n","Epoch 20/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2969 - accuracy: 0.6429\n","Epoch 21/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2964 - accuracy: 0.6429\n","Epoch 22/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2960 - accuracy: 0.6429\n","Epoch 23/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2955 - accuracy: 0.6429\n","Epoch 24/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2951 - accuracy: 0.6429\n","Epoch 25/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2946 - accuracy: 0.6429\n","Epoch 26/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2941 - accuracy: 0.6429\n","Epoch 27/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2937 - accuracy: 0.6429\n","Epoch 28/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2932 - accuracy: 0.6429\n","Epoch 29/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2928 - accuracy: 0.6429\n","Epoch 30/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2923 - accuracy: 0.6429\n","Epoch 31/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2918 - accuracy: 0.6429\n","Epoch 32/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2914 - accuracy: 0.6429\n","Epoch 33/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2909 - accuracy: 0.6429\n","Epoch 34/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2904 - accuracy: 0.6429\n","Epoch 35/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2899 - accuracy: 0.6429\n","Epoch 36/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2894 - accuracy: 0.6429\n","Epoch 37/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2889 - accuracy: 0.6429\n","Epoch 38/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2884 - accuracy: 0.6429\n","Epoch 39/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2879 - accuracy: 0.6429\n","Epoch 40/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2873 - accuracy: 0.6429\n","Epoch 41/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2868 - accuracy: 0.6429\n","Epoch 42/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2862 - accuracy: 0.6429\n","Epoch 43/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2857 - accuracy: 0.6429\n","Epoch 44/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2851 - accuracy: 0.6429\n","Epoch 45/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2846 - accuracy: 0.6429\n","Epoch 46/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2841 - accuracy: 0.6429\n","Epoch 47/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2836 - accuracy: 0.6429\n","Epoch 48/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2831 - accuracy: 0.6429\n","Epoch 49/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2826 - accuracy: 0.6429\n","Epoch 50/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2821 - accuracy: 0.6429\n","Epoch 51/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2816 - accuracy: 0.6429\n","Epoch 52/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2810 - accuracy: 0.6429\n","Epoch 53/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2805 - accuracy: 0.6429\n","Epoch 54/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2800 - accuracy: 0.6429\n","Epoch 55/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2795 - accuracy: 0.6429\n","Epoch 56/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2790 - accuracy: 0.6429\n","Epoch 57/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2785 - accuracy: 0.6429\n","Epoch 58/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2780 - accuracy: 0.6429\n","Epoch 59/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2775 - accuracy: 0.6429\n","Epoch 60/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2770 - accuracy: 0.6429\n","Epoch 61/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2765 - accuracy: 0.6429\n","Epoch 62/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2759 - accuracy: 0.6429\n","Epoch 63/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2754 - accuracy: 0.6429\n","Epoch 64/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2749 - accuracy: 0.6429\n","Epoch 65/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2744 - accuracy: 0.6429\n","Epoch 66/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2739 - accuracy: 0.6429\n","Epoch 67/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2734 - accuracy: 0.6429\n","Epoch 68/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2729 - accuracy: 0.6429\n","Epoch 69/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2724 - accuracy: 0.6429\n","Epoch 70/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2719 - accuracy: 0.6429\n","Epoch 71/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2714 - accuracy: 0.6429\n","Epoch 72/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2709 - accuracy: 0.6429\n","Epoch 73/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2704 - accuracy: 0.6429\n","Epoch 74/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.2698 - accuracy: 0.6429\n","Epoch 75/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2693 - accuracy: 0.6429\n","Epoch 76/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2688 - accuracy: 0.6429\n","Epoch 77/1000\n","1/1 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114/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2497 - accuracy: 0.6429\n","Epoch 115/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2492 - accuracy: 0.6429\n","Epoch 116/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2486 - accuracy: 0.6429\n","Epoch 117/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2481 - accuracy: 0.6429\n","Epoch 118/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2476 - accuracy: 0.6429\n","Epoch 119/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2471 - accuracy: 0.6429\n","Epoch 120/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2466 - accuracy: 0.6429\n","Epoch 121/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2461 - accuracy: 0.6429\n","Epoch 122/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2456 - accuracy: 0.6429\n","Epoch 123/1000\n","1/1 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[==============================] - 0s 16ms/step - loss: 0.2353 - accuracy: 0.6429\n","Epoch 151/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2350 - accuracy: 0.6429\n","Epoch 152/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2346 - accuracy: 0.6429\n","Epoch 153/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2343 - accuracy: 0.6429\n","Epoch 154/1000\n","1/1 [==============================] - 0s 26ms/step - loss: 0.2339 - accuracy: 0.6429\n","Epoch 155/1000\n","1/1 [==============================] - 0s 29ms/step - loss: 0.2336 - accuracy: 0.6429\n","Epoch 156/1000\n","1/1 [==============================] - 0s 23ms/step - loss: 0.2333 - accuracy: 0.6429\n","Epoch 157/1000\n","1/1 [==============================] - 0s 26ms/step - loss: 0.2330 - accuracy: 0.6429\n","Epoch 158/1000\n","1/1 [==============================] - 0s 31ms/step - loss: 0.2328 - accuracy: 0.6429\n","Epoch 159/1000\n","1/1 [==============================] - 0s 21ms/step - loss: 0.2325 - accuracy: 0.6429\n","Epoch 160/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.2323 - accuracy: 0.6429\n","Epoch 161/1000\n","1/1 [==============================] - 0s 28ms/step - loss: 0.2320 - accuracy: 0.6429\n","Epoch 162/1000\n","1/1 [==============================] - 0s 18ms/step - loss: 0.2318 - accuracy: 0.6429\n","Epoch 163/1000\n","1/1 [==============================] - 0s 27ms/step - loss: 0.2315 - accuracy: 0.6429\n","Epoch 164/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2313 - accuracy: 0.6429\n","Epoch 165/1000\n","1/1 [==============================] - 0s 36ms/step - loss: 0.2310 - accuracy: 0.6429\n","Epoch 166/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.2308 - accuracy: 0.6429\n","Epoch 167/1000\n","1/1 [==============================] - 0s 21ms/step - loss: 0.2305 - accuracy: 0.6429\n","Epoch 168/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2303 - accuracy: 0.6429\n","Epoch 169/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2300 - accuracy: 0.6429\n","Epoch 170/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2298 - accuracy: 0.6429\n","Epoch 171/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2295 - accuracy: 0.6429\n","Epoch 172/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2293 - accuracy: 0.6429\n","Epoch 173/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2290 - accuracy: 0.6429\n","Epoch 174/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2288 - accuracy: 0.6429\n","Epoch 175/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2286 - accuracy: 0.6429\n","Epoch 176/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2283 - accuracy: 0.6429\n","Epoch 177/1000\n","1/1 [==============================] - 0s 33ms/step - loss: 0.2281 - accuracy: 0.6429\n","Epoch 178/1000\n","1/1 [==============================] - 0s 27ms/step - loss: 0.2278 - accuracy: 0.6429\n","Epoch 179/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2276 - accuracy: 0.6429\n","Epoch 180/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2274 - accuracy: 0.6429\n","Epoch 181/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2271 - accuracy: 0.6429\n","Epoch 182/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2269 - accuracy: 0.6429\n","Epoch 183/1000\n","1/1 [==============================] - 0s 21ms/step - loss: 0.2266 - accuracy: 0.6429\n","Epoch 184/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2263 - accuracy: 0.6429\n","Epoch 185/1000\n","1/1 [==============================] - 0s 22ms/step - loss: 0.2261 - accuracy: 0.6429\n","Epoch 186/1000\n","1/1 [==============================] - 0s 36ms/step - loss: 0.2258 - accuracy: 0.6429\n","Epoch 187/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2255 - accuracy: 0.6429\n","Epoch 188/1000\n","1/1 [==============================] - 0s 28ms/step - loss: 0.2253 - accuracy: 0.6429\n","Epoch 189/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2250 - accuracy: 0.6429\n","Epoch 190/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2248 - accuracy: 0.6429\n","Epoch 191/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2245 - accuracy: 0.6429\n","Epoch 192/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2242 - accuracy: 0.6429\n","Epoch 193/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2240 - accuracy: 0.6429\n","Epoch 194/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.2237 - accuracy: 0.6429\n","Epoch 195/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2235 - accuracy: 0.6429\n","Epoch 196/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2232 - accuracy: 0.6429\n","Epoch 197/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2230 - accuracy: 0.6429\n","Epoch 198/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2227 - accuracy: 0.6429\n","Epoch 199/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2225 - accuracy: 0.6429\n","Epoch 200/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2222 - accuracy: 0.6429\n","Epoch 201/1000\n","1/1 [==============================] - 0s 25ms/step - loss: 0.2220 - accuracy: 0.6429\n","Epoch 202/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2217 - accuracy: 0.6429\n","Epoch 203/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2215 - accuracy: 0.6429\n","Epoch 204/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2212 - accuracy: 0.6429\n","Epoch 205/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2210 - accuracy: 0.6429\n","Epoch 206/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2207 - accuracy: 0.6429\n","Epoch 207/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2205 - accuracy: 0.6429\n","Epoch 208/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2202 - accuracy: 0.6429\n","Epoch 209/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2200 - accuracy: 0.6429\n","Epoch 210/1000\n","1/1 [==============================] - 0s 25ms/step - loss: 0.2197 - accuracy: 0.6429\n","Epoch 211/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2195 - accuracy: 0.6429\n","Epoch 212/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2192 - accuracy: 0.6429\n","Epoch 213/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2190 - accuracy: 0.6429\n","Epoch 214/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2187 - accuracy: 0.6429\n","Epoch 215/1000\n","1/1 [==============================] - 0s 30ms/step - loss: 0.2185 - accuracy: 0.6429\n","Epoch 216/1000\n","1/1 [==============================] - 0s 23ms/step - loss: 0.2183 - accuracy: 0.6429\n","Epoch 217/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2180 - accuracy: 0.6429\n","Epoch 218/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2178 - accuracy: 0.6429\n","Epoch 219/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2175 - accuracy: 0.6429\n","Epoch 220/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2173 - accuracy: 0.6429\n","Epoch 221/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2171 - accuracy: 0.6429\n","Epoch 222/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2168 - accuracy: 0.6429\n","Epoch 223/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2166 - accuracy: 0.6429\n","Epoch 224/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2163 - accuracy: 0.6429\n","Epoch 225/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2161 - accuracy: 0.6429\n","Epoch 226/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2159 - accuracy: 0.6429\n","Epoch 227/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2156 - accuracy: 0.6429\n","Epoch 228/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2154 - accuracy: 0.6429\n","Epoch 229/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2152 - accuracy: 0.6429\n","Epoch 230/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2149 - accuracy: 0.6429\n","Epoch 231/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2147 - accuracy: 0.6429\n","Epoch 232/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.2145 - accuracy: 0.6429\n","Epoch 233/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2142 - accuracy: 0.6429\n","Epoch 234/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.2140 - accuracy: 0.6429\n","Epoch 235/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2138 - accuracy: 0.6429\n","Epoch 236/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.2136 - accuracy: 0.6429\n","Epoch 237/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2134 - accuracy: 0.6429\n","Epoch 238/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2133 - accuracy: 0.6429\n","Epoch 239/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2131 - accuracy: 0.6429\n","Epoch 240/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2130 - accuracy: 0.6429\n","Epoch 241/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2128 - accuracy: 0.6429\n","Epoch 242/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2127 - accuracy: 0.6429\n","Epoch 243/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2126 - accuracy: 0.6429\n","Epoch 244/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2125 - accuracy: 0.6429\n","Epoch 245/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2124 - accuracy: 0.6429\n","Epoch 246/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2122 - accuracy: 0.6429\n","Epoch 247/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2121 - accuracy: 0.6429\n","Epoch 248/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2120 - accuracy: 0.6429\n","Epoch 249/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2119 - accuracy: 0.6429\n","Epoch 250/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2118 - accuracy: 0.6429\n","Epoch 251/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2116 - accuracy: 0.6429\n","Epoch 252/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2115 - accuracy: 0.6429\n","Epoch 253/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2114 - accuracy: 0.6429\n","Epoch 254/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2113 - accuracy: 0.6429\n","Epoch 255/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2112 - accuracy: 0.6429\n","Epoch 256/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2110 - accuracy: 0.6429\n","Epoch 257/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2109 - accuracy: 0.6429\n","Epoch 258/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2108 - accuracy: 0.6429\n","Epoch 259/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2107 - accuracy: 0.6429\n","Epoch 260/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2105 - accuracy: 0.6429\n","Epoch 261/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2104 - accuracy: 0.6429\n","Epoch 262/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2103 - accuracy: 0.6429\n","Epoch 263/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2102 - accuracy: 0.6429\n","Epoch 264/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2101 - accuracy: 0.6429\n","Epoch 265/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2099 - accuracy: 0.6429\n","Epoch 266/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2098 - accuracy: 0.6429\n","Epoch 267/1000\n","1/1 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[==============================] - 0s 11ms/step - loss: 0.2068 - accuracy: 0.6429\n","Epoch 295/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2067 - accuracy: 0.6429\n","Epoch 296/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.2066 - accuracy: 0.6429\n","Epoch 297/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2065 - accuracy: 0.6429\n","Epoch 298/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2064 - accuracy: 0.6429\n","Epoch 299/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2063 - accuracy: 0.6429\n","Epoch 300/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2062 - accuracy: 0.6429\n","Epoch 301/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2062 - accuracy: 0.6429\n","Epoch 302/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2061 - accuracy: 0.6429\n","Epoch 303/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2060 - accuracy: 0.6429\n","Epoch 304/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2059 - accuracy: 0.6429\n","Epoch 305/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2058 - accuracy: 0.6429\n","Epoch 306/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2057 - accuracy: 0.6429\n","Epoch 307/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2056 - accuracy: 0.6429\n","Epoch 308/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2055 - accuracy: 0.6429\n","Epoch 309/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2054 - accuracy: 0.6429\n","Epoch 310/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2053 - accuracy: 0.6429\n","Epoch 311/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2052 - accuracy: 0.6429\n","Epoch 312/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2051 - accuracy: 0.6429\n","Epoch 313/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2050 - accuracy: 0.6429\n","Epoch 314/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2050 - accuracy: 0.6429\n","Epoch 315/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2049 - accuracy: 0.6429\n","Epoch 316/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2048 - accuracy: 0.6429\n","Epoch 317/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2047 - accuracy: 0.6429\n","Epoch 318/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2046 - accuracy: 0.6429\n","Epoch 319/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2045 - accuracy: 0.6429\n","Epoch 320/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.2044 - accuracy: 0.6429\n","Epoch 321/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2043 - accuracy: 0.6429\n","Epoch 322/1000\n","1/1 [==============================] - 0s 30ms/step - loss: 0.2042 - accuracy: 0.6429\n","Epoch 323/1000\n","1/1 [==============================] - 0s 18ms/step - loss: 0.2041 - accuracy: 0.6429\n","Epoch 324/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2040 - accuracy: 0.6429\n","Epoch 325/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2040 - accuracy: 0.6429\n","Epoch 326/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.2039 - accuracy: 0.6429\n","Epoch 327/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2038 - accuracy: 0.6429\n","Epoch 328/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.2037 - accuracy: 0.6429\n","Epoch 329/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2036 - accuracy: 0.6429\n","Epoch 330/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2035 - accuracy: 0.6429\n","Epoch 331/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2034 - accuracy: 0.6429\n","Epoch 332/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2033 - accuracy: 0.6429\n","Epoch 333/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2032 - accuracy: 0.6429\n","Epoch 334/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2032 - accuracy: 0.6429\n","Epoch 335/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2031 - accuracy: 0.6429\n","Epoch 336/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2030 - accuracy: 0.6429\n","Epoch 337/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2029 - accuracy: 0.6429\n","Epoch 338/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2028 - accuracy: 0.6429\n","Epoch 339/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2027 - accuracy: 0.6429\n","Epoch 340/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2026 - accuracy: 0.6429\n","Epoch 341/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2025 - accuracy: 0.6429\n","Epoch 342/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2024 - accuracy: 0.6429\n","Epoch 343/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2023 - accuracy: 0.6429\n","Epoch 344/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2022 - accuracy: 0.6429\n","Epoch 345/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2021 - accuracy: 0.6429\n","Epoch 346/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2020 - accuracy: 0.6429\n","Epoch 347/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2019 - accuracy: 0.6429\n","Epoch 348/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2017 - accuracy: 0.6429\n","Epoch 349/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2016 - accuracy: 0.6429\n","Epoch 350/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2015 - accuracy: 0.6429\n","Epoch 351/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2014 - accuracy: 0.6429\n","Epoch 352/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2013 - accuracy: 0.6429\n","Epoch 353/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2012 - accuracy: 0.6429\n","Epoch 354/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.2011 - accuracy: 0.6429\n","Epoch 355/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2010 - accuracy: 0.6429\n","Epoch 356/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2009 - accuracy: 0.6429\n","Epoch 357/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.2008 - accuracy: 0.6429\n","Epoch 358/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2007 - accuracy: 0.6429\n","Epoch 359/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2006 - accuracy: 0.6429\n","Epoch 360/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2005 - accuracy: 0.6429\n","Epoch 361/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2004 - accuracy: 0.6429\n","Epoch 362/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2003 - accuracy: 0.6429\n","Epoch 363/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2002 - accuracy: 0.6429\n","Epoch 364/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.2001 - accuracy: 0.6429\n","Epoch 365/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.2000 - accuracy: 0.6429\n","Epoch 366/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1999 - accuracy: 0.6429\n","Epoch 367/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1998 - accuracy: 0.6429\n","Epoch 368/1000\n","1/1 [==============================] - 0s 19ms/step - loss: 0.1997 - accuracy: 0.6429\n","Epoch 369/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1997 - accuracy: 0.6429\n","Epoch 370/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1996 - accuracy: 0.6429\n","Epoch 371/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1995 - accuracy: 0.6429\n","Epoch 372/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1994 - accuracy: 0.6429\n","Epoch 373/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1993 - accuracy: 0.6429\n","Epoch 374/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.1992 - accuracy: 0.6429\n","Epoch 375/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1991 - accuracy: 0.6429\n","Epoch 376/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1990 - accuracy: 0.6429\n","Epoch 377/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1990 - accuracy: 0.6429\n","Epoch 378/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1989 - accuracy: 0.6429\n","Epoch 379/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1988 - accuracy: 0.6429\n","Epoch 380/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1987 - accuracy: 0.6429\n","Epoch 381/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1986 - accuracy: 0.6429\n","Epoch 382/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1985 - accuracy: 0.6429\n","Epoch 383/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1984 - accuracy: 0.6429\n","Epoch 384/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1984 - accuracy: 0.6429\n","Epoch 385/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1983 - accuracy: 0.6429\n","Epoch 386/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1982 - accuracy: 0.6429\n","Epoch 387/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1981 - accuracy: 0.6429\n","Epoch 388/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1980 - accuracy: 0.6429\n","Epoch 389/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1979 - accuracy: 0.6429\n","Epoch 390/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1978 - accuracy: 0.6429\n","Epoch 391/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1978 - accuracy: 0.6429\n","Epoch 392/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1977 - accuracy: 0.6429\n","Epoch 393/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1976 - accuracy: 0.6429\n","Epoch 394/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1975 - accuracy: 0.6429\n","Epoch 395/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1974 - accuracy: 0.6429\n","Epoch 396/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1973 - accuracy: 0.6429\n","Epoch 397/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1972 - accuracy: 0.6429\n","Epoch 398/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.1972 - accuracy: 0.6429\n","Epoch 399/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1971 - accuracy: 0.6429\n","Epoch 400/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1970 - accuracy: 0.6429\n","Epoch 401/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1969 - accuracy: 0.6429\n","Epoch 402/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1968 - accuracy: 0.6429\n","Epoch 403/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1968 - accuracy: 0.6429\n","Epoch 404/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1967 - accuracy: 0.6429\n","Epoch 405/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1966 - accuracy: 0.6429\n","Epoch 406/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1965 - accuracy: 0.6429\n","Epoch 407/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1964 - accuracy: 0.6429\n","Epoch 408/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1964 - accuracy: 0.6429\n","Epoch 409/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.1963 - accuracy: 0.6429\n","Epoch 410/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1962 - accuracy: 0.6429\n","Epoch 411/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1961 - accuracy: 0.6429\n","Epoch 412/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1960 - accuracy: 0.6429\n","Epoch 413/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1960 - accuracy: 0.6429\n","Epoch 414/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1959 - accuracy: 0.6429\n","Epoch 415/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1958 - accuracy: 0.6429\n","Epoch 416/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1957 - accuracy: 0.6429\n","Epoch 417/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1956 - accuracy: 0.6429\n","Epoch 418/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1955 - accuracy: 0.6429\n","Epoch 419/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1955 - accuracy: 0.6429\n","Epoch 420/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1954 - accuracy: 0.6429\n","Epoch 421/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1953 - accuracy: 0.6429\n","Epoch 422/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1952 - accuracy: 0.6429\n","Epoch 423/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1952 - accuracy: 0.6429\n","Epoch 424/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1951 - accuracy: 0.6429\n","Epoch 425/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1950 - accuracy: 0.6429\n","Epoch 426/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1949 - accuracy: 0.6429\n","Epoch 427/1000\n","1/1 [==============================] - 0s 20ms/step - loss: 0.1949 - accuracy: 0.6429\n","Epoch 428/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1948 - accuracy: 0.6429\n","Epoch 429/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1947 - accuracy: 0.6429\n","Epoch 430/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1946 - accuracy: 0.6429\n","Epoch 431/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1946 - accuracy: 0.6429\n","Epoch 432/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.1945 - accuracy: 0.6429\n","Epoch 433/1000\n","1/1 [==============================] - 0s 18ms/step - loss: 0.1944 - accuracy: 0.6429\n","Epoch 434/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1943 - accuracy: 0.6429\n","Epoch 435/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1943 - accuracy: 0.6429\n","Epoch 436/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1942 - accuracy: 0.6429\n","Epoch 437/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1941 - accuracy: 0.6429\n","Epoch 438/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1940 - accuracy: 0.6429\n","Epoch 439/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1940 - accuracy: 0.6429\n","Epoch 440/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1939 - accuracy: 0.6429\n","Epoch 441/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1938 - accuracy: 0.6429\n","Epoch 442/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1937 - accuracy: 0.6429\n","Epoch 443/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1937 - accuracy: 0.6429\n","Epoch 444/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1936 - accuracy: 0.6429\n","Epoch 445/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1935 - accuracy: 0.6429\n","Epoch 446/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1934 - accuracy: 0.6429\n","Epoch 447/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1934 - accuracy: 0.6429\n","Epoch 448/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1933 - accuracy: 0.6429\n","Epoch 449/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1932 - accuracy: 0.6429\n","Epoch 450/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1932 - accuracy: 0.6429\n","Epoch 451/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1931 - accuracy: 0.6429\n","Epoch 452/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1930 - accuracy: 0.6429\n","Epoch 453/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1929 - accuracy: 0.6429\n","Epoch 454/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1929 - accuracy: 0.6429\n","Epoch 455/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1928 - accuracy: 0.6429\n","Epoch 456/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1927 - accuracy: 0.6429\n","Epoch 457/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1926 - accuracy: 0.6429\n","Epoch 458/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1926 - accuracy: 0.6429\n","Epoch 459/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1925 - accuracy: 0.6429\n","Epoch 460/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1924 - accuracy: 0.6429\n","Epoch 461/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1923 - accuracy: 0.6429\n","Epoch 462/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1923 - accuracy: 0.6429\n","Epoch 463/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1922 - accuracy: 0.6429\n","Epoch 464/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1921 - accuracy: 0.6429\n","Epoch 465/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1921 - accuracy: 0.6429\n","Epoch 466/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1920 - accuracy: 0.6429\n","Epoch 467/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1919 - accuracy: 0.6429\n","Epoch 468/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1918 - accuracy: 0.6429\n","Epoch 469/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1918 - accuracy: 0.6429\n","Epoch 470/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1917 - accuracy: 0.6429\n","Epoch 471/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1916 - accuracy: 0.6429\n","Epoch 472/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1915 - accuracy: 0.6429\n","Epoch 473/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1915 - accuracy: 0.6429\n","Epoch 474/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1914 - accuracy: 0.6429\n","Epoch 475/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1913 - accuracy: 0.6429\n","Epoch 476/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1913 - accuracy: 0.6429\n","Epoch 477/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1912 - accuracy: 0.6429\n","Epoch 478/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1911 - accuracy: 0.6429\n","Epoch 479/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1910 - accuracy: 0.6429\n","Epoch 480/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1910 - accuracy: 0.6429\n","Epoch 481/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1909 - accuracy: 0.6429\n","Epoch 482/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1908 - accuracy: 0.6429\n","Epoch 483/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1908 - accuracy: 0.6429\n","Epoch 484/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1907 - accuracy: 0.6429\n","Epoch 485/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1906 - accuracy: 0.6429\n","Epoch 486/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1905 - accuracy: 0.6429\n","Epoch 487/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1905 - accuracy: 0.6429\n","Epoch 488/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1904 - accuracy: 0.6429\n","Epoch 489/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1903 - accuracy: 0.6429\n","Epoch 490/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1903 - accuracy: 0.6429\n","Epoch 491/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1902 - accuracy: 0.6429\n","Epoch 492/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1901 - accuracy: 0.6429\n","Epoch 493/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1900 - accuracy: 0.6429\n","Epoch 494/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1900 - accuracy: 0.6429\n","Epoch 495/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1899 - accuracy: 0.6429\n","Epoch 496/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1898 - accuracy: 0.6429\n","Epoch 497/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1898 - accuracy: 0.6429\n","Epoch 498/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1897 - accuracy: 0.6429\n","Epoch 499/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1896 - accuracy: 0.6429\n","Epoch 500/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1895 - accuracy: 0.6429\n","Epoch 501/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1895 - accuracy: 0.6429\n","Epoch 502/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1894 - accuracy: 0.6429\n","Epoch 503/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1893 - accuracy: 0.6429\n","Epoch 504/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1893 - accuracy: 0.6429\n","Epoch 505/1000\n","1/1 [==============================] - 0s 7ms/step - loss: 0.1892 - accuracy: 0.6429\n","Epoch 506/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1891 - accuracy: 0.6429\n","Epoch 507/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1890 - accuracy: 0.6429\n","Epoch 508/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1890 - accuracy: 0.6429\n","Epoch 509/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1889 - accuracy: 0.6429\n","Epoch 510/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1888 - accuracy: 0.6429\n","Epoch 511/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1888 - accuracy: 0.6429\n","Epoch 512/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1887 - accuracy: 0.6429\n","Epoch 513/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1886 - accuracy: 0.6429\n","Epoch 514/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1886 - accuracy: 0.6429\n","Epoch 515/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1885 - accuracy: 0.6429\n","Epoch 516/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1884 - accuracy: 0.6429\n","Epoch 517/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1884 - accuracy: 0.6429\n","Epoch 518/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1883 - accuracy: 0.6429\n","Epoch 519/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1882 - accuracy: 0.6429\n","Epoch 520/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1882 - accuracy: 0.6429\n","Epoch 521/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1881 - accuracy: 0.6429\n","Epoch 522/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1880 - accuracy: 0.6429\n","Epoch 523/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1880 - accuracy: 0.6429\n","Epoch 524/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1879 - accuracy: 0.6429\n","Epoch 525/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1878 - accuracy: 0.6429\n","Epoch 526/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1878 - accuracy: 0.6429\n","Epoch 527/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1877 - accuracy: 0.6429\n","Epoch 528/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1876 - accuracy: 0.6429\n","Epoch 529/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1876 - accuracy: 0.6429\n","Epoch 530/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1875 - accuracy: 0.6429\n","Epoch 531/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1874 - accuracy: 0.6429\n","Epoch 532/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1874 - accuracy: 0.6429\n","Epoch 533/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1873 - accuracy: 0.6429\n","Epoch 534/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1872 - accuracy: 0.6429\n","Epoch 535/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1872 - accuracy: 0.6429\n","Epoch 536/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1871 - accuracy: 0.6429\n","Epoch 537/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1870 - accuracy: 0.6429\n","Epoch 538/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1869 - accuracy: 0.6429\n","Epoch 539/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1869 - accuracy: 0.6429\n","Epoch 540/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1868 - accuracy: 0.6429\n","Epoch 541/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1868 - accuracy: 0.6429\n","Epoch 542/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1867 - accuracy: 0.6429\n","Epoch 543/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1866 - accuracy: 0.6429\n","Epoch 544/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1866 - accuracy: 0.6429\n","Epoch 545/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1865 - accuracy: 0.6429\n","Epoch 546/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1865 - accuracy: 0.6429\n","Epoch 547/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1864 - accuracy: 0.6429\n","Epoch 548/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1864 - accuracy: 0.6429\n","Epoch 549/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1863 - accuracy: 0.6429\n","Epoch 550/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1863 - accuracy: 0.6429\n","Epoch 551/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1862 - accuracy: 0.6429\n","Epoch 552/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1862 - accuracy: 0.6429\n","Epoch 553/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1861 - accuracy: 0.6429\n","Epoch 554/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1861 - accuracy: 0.6429\n","Epoch 555/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1860 - accuracy: 0.6429\n","Epoch 556/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1860 - accuracy: 0.6429\n","Epoch 557/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1859 - accuracy: 0.6429\n","Epoch 558/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1858 - accuracy: 0.6429\n","Epoch 559/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1858 - accuracy: 0.6429\n","Epoch 560/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1857 - accuracy: 0.6429\n","Epoch 561/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1857 - accuracy: 0.6429\n","Epoch 562/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1856 - accuracy: 0.6429\n","Epoch 563/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1856 - accuracy: 0.6429\n","Epoch 564/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1855 - accuracy: 0.6429\n","Epoch 565/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1855 - accuracy: 0.6429\n","Epoch 566/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1854 - accuracy: 0.6429\n","Epoch 567/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1854 - accuracy: 0.6429\n","Epoch 568/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1853 - accuracy: 0.6429\n","Epoch 569/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1853 - accuracy: 0.6429\n","Epoch 570/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1852 - accuracy: 0.6429\n","Epoch 571/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1852 - accuracy: 0.6429\n","Epoch 572/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1851 - accuracy: 0.6429\n","Epoch 573/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1851 - accuracy: 0.6429\n","Epoch 574/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1850 - accuracy: 0.6429\n","Epoch 575/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1850 - accuracy: 0.6429\n","Epoch 576/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1849 - accuracy: 0.6429\n","Epoch 577/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1849 - accuracy: 0.6429\n","Epoch 578/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1848 - accuracy: 0.6429\n","Epoch 579/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1848 - accuracy: 0.6429\n","Epoch 580/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1847 - accuracy: 0.6429\n","Epoch 581/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1846 - accuracy: 0.6429\n","Epoch 582/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1846 - accuracy: 0.6429\n","Epoch 583/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1845 - accuracy: 0.6429\n","Epoch 584/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1845 - accuracy: 0.6429\n","Epoch 585/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1844 - accuracy: 0.6429\n","Epoch 586/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1844 - accuracy: 0.6429\n","Epoch 587/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1843 - accuracy: 0.6429\n","Epoch 588/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1843 - accuracy: 0.6429\n","Epoch 589/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1842 - accuracy: 0.6429\n","Epoch 590/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1842 - accuracy: 0.6429\n","Epoch 591/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1841 - accuracy: 0.6429\n","Epoch 592/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1841 - accuracy: 0.6429\n","Epoch 593/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1840 - accuracy: 0.6429\n","Epoch 594/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1840 - accuracy: 0.6429\n","Epoch 595/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1839 - accuracy: 0.6429\n","Epoch 596/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1839 - accuracy: 0.6429\n","Epoch 597/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1838 - accuracy: 0.6429\n","Epoch 598/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1838 - accuracy: 0.6429\n","Epoch 599/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1837 - accuracy: 0.6429\n","Epoch 600/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1837 - accuracy: 0.6429\n","Epoch 601/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1836 - accuracy: 0.6429\n","Epoch 602/1000\n","1/1 [==============================] - 0s 22ms/step - loss: 0.1836 - accuracy: 0.6429\n","Epoch 603/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1835 - accuracy: 0.6429\n","Epoch 604/1000\n","1/1 [==============================] - 0s 18ms/step - loss: 0.1834 - accuracy: 0.6429\n","Epoch 605/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1834 - accuracy: 0.6429\n","Epoch 606/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1833 - accuracy: 0.6429\n","Epoch 607/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1833 - accuracy: 0.6429\n","Epoch 608/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1832 - accuracy: 0.6429\n","Epoch 609/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1832 - accuracy: 0.6429\n","Epoch 610/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1831 - accuracy: 0.6429\n","Epoch 611/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1831 - accuracy: 0.6429\n","Epoch 612/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1830 - accuracy: 0.6429\n","Epoch 613/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1830 - accuracy: 0.6429\n","Epoch 614/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1829 - accuracy: 0.6429\n","Epoch 615/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1829 - accuracy: 0.6429\n","Epoch 616/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1828 - accuracy: 0.6429\n","Epoch 617/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1828 - accuracy: 0.6429\n","Epoch 618/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1827 - accuracy: 0.6429\n","Epoch 619/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1827 - accuracy: 0.6429\n","Epoch 620/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1826 - accuracy: 0.6429\n","Epoch 621/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1826 - accuracy: 0.6429\n","Epoch 622/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1825 - accuracy: 0.6429\n","Epoch 623/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1825 - accuracy: 0.6429\n","Epoch 624/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1824 - accuracy: 0.6429\n","Epoch 625/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1824 - accuracy: 0.6429\n","Epoch 626/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1823 - accuracy: 0.6429\n","Epoch 627/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1823 - accuracy: 0.6429\n","Epoch 628/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1822 - accuracy: 0.6429\n","Epoch 629/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1822 - accuracy: 0.6429\n","Epoch 630/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1821 - accuracy: 0.6429\n","Epoch 631/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1821 - accuracy: 0.6429\n","Epoch 632/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1820 - accuracy: 0.6429\n","Epoch 633/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1820 - accuracy: 0.6429\n","Epoch 634/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1819 - accuracy: 0.6429\n","Epoch 635/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1819 - accuracy: 0.6429\n","Epoch 636/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1818 - accuracy: 0.6429\n","Epoch 637/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1818 - accuracy: 0.6429\n","Epoch 638/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1817 - accuracy: 0.6429\n","Epoch 639/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1817 - accuracy: 0.6429\n","Epoch 640/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1816 - accuracy: 0.6429\n","Epoch 641/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1816 - accuracy: 0.6429\n","Epoch 642/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1815 - accuracy: 0.6429\n","Epoch 643/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1815 - accuracy: 0.6429\n","Epoch 644/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1814 - accuracy: 0.6429\n","Epoch 645/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1814 - accuracy: 0.6429\n","Epoch 646/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1813 - accuracy: 0.6429\n","Epoch 647/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1813 - accuracy: 0.6429\n","Epoch 648/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1812 - accuracy: 0.6429\n","Epoch 649/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1811 - accuracy: 0.6429\n","Epoch 650/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1811 - accuracy: 0.6429\n","Epoch 651/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1811 - accuracy: 0.6429\n","Epoch 652/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1810 - accuracy: 0.6429\n","Epoch 653/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1810 - accuracy: 0.6429\n","Epoch 654/1000\n","1/1 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[==============================] - 0s 9ms/step - loss: 0.1805 - accuracy: 0.6429\n","Epoch 664/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1805 - accuracy: 0.6429\n","Epoch 665/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1805 - accuracy: 0.6429\n","Epoch 666/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1804 - accuracy: 0.6429\n","Epoch 667/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1804 - accuracy: 0.6429\n","Epoch 668/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1803 - accuracy: 0.6429\n","Epoch 669/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1803 - accuracy: 0.6429\n","Epoch 670/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1803 - accuracy: 0.6429\n","Epoch 671/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1802 - accuracy: 0.6429\n","Epoch 672/1000\n","1/1 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[==============================] - 0s 8ms/step - loss: 0.1798 - accuracy: 0.6429\n","Epoch 682/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1798 - accuracy: 0.6429\n","Epoch 683/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1797 - accuracy: 0.6429\n","Epoch 684/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1797 - accuracy: 0.6429\n","Epoch 685/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1796 - accuracy: 0.6429\n","Epoch 686/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1796 - accuracy: 0.6429\n","Epoch 687/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1795 - accuracy: 0.6429\n","Epoch 688/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1795 - accuracy: 0.6429\n","Epoch 689/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1795 - accuracy: 0.6429\n","Epoch 690/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1794 - accuracy: 0.6429\n","Epoch 691/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1794 - accuracy: 0.6429\n","Epoch 692/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1793 - accuracy: 0.6429\n","Epoch 693/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1793 - accuracy: 0.6429\n","Epoch 694/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1793 - accuracy: 0.6429\n","Epoch 695/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1792 - accuracy: 0.6429\n","Epoch 696/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1792 - accuracy: 0.6429\n","Epoch 697/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1792 - accuracy: 0.6429\n","Epoch 698/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1791 - accuracy: 0.6429\n","Epoch 699/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1791 - accuracy: 0.6429\n","Epoch 700/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1790 - accuracy: 0.6429\n","Epoch 701/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1790 - accuracy: 0.6429\n","Epoch 702/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1790 - accuracy: 0.6429\n","Epoch 703/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1789 - accuracy: 0.6429\n","Epoch 704/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1789 - accuracy: 0.6429\n","Epoch 705/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1788 - accuracy: 0.6429\n","Epoch 706/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1788 - accuracy: 0.6429\n","Epoch 707/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1788 - accuracy: 0.6429\n","Epoch 708/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1787 - accuracy: 0.6429\n","Epoch 709/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1787 - accuracy: 0.6429\n","Epoch 710/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1786 - accuracy: 0.6429\n","Epoch 711/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1786 - accuracy: 0.6429\n","Epoch 712/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1786 - accuracy: 0.6429\n","Epoch 713/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1785 - accuracy: 0.6429\n","Epoch 714/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1785 - accuracy: 0.6429\n","Epoch 715/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1784 - accuracy: 0.6429\n","Epoch 716/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1784 - accuracy: 0.6429\n","Epoch 717/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1784 - accuracy: 0.6429\n","Epoch 718/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1783 - accuracy: 0.6429\n","Epoch 719/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1783 - accuracy: 0.6429\n","Epoch 720/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1782 - accuracy: 0.6429\n","Epoch 721/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1782 - accuracy: 0.6429\n","Epoch 722/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1782 - accuracy: 0.6429\n","Epoch 723/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1781 - accuracy: 0.6429\n","Epoch 724/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1781 - accuracy: 0.6429\n","Epoch 725/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1781 - accuracy: 0.6429\n","Epoch 726/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1780 - accuracy: 0.6429\n","Epoch 727/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1780 - accuracy: 0.6429\n","Epoch 728/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1779 - accuracy: 0.6429\n","Epoch 729/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1779 - accuracy: 0.6429\n","Epoch 730/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1779 - accuracy: 0.6429\n","Epoch 731/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1778 - accuracy: 0.6429\n","Epoch 732/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1778 - accuracy: 0.6429\n","Epoch 733/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1777 - accuracy: 0.6429\n","Epoch 734/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1777 - accuracy: 0.6429\n","Epoch 735/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1777 - accuracy: 0.6429\n","Epoch 736/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1776 - accuracy: 0.6429\n","Epoch 737/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1776 - accuracy: 0.6429\n","Epoch 738/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1775 - accuracy: 0.6429\n","Epoch 739/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1775 - accuracy: 0.6429\n","Epoch 740/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1775 - accuracy: 0.6429\n","Epoch 741/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1774 - accuracy: 0.6429\n","Epoch 742/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1774 - accuracy: 0.6429\n","Epoch 743/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1773 - accuracy: 0.6429\n","Epoch 744/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1773 - accuracy: 0.6429\n","Epoch 745/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1773 - accuracy: 0.6429\n","Epoch 746/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1772 - accuracy: 0.6429\n","Epoch 747/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1772 - accuracy: 0.6429\n","Epoch 748/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1772 - accuracy: 0.6429\n","Epoch 749/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1771 - accuracy: 0.6429\n","Epoch 750/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1771 - accuracy: 0.6429\n","Epoch 751/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1770 - accuracy: 0.6429\n","Epoch 752/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1770 - accuracy: 0.6429\n","Epoch 753/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1770 - accuracy: 0.6429\n","Epoch 754/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1769 - accuracy: 0.6429\n","Epoch 755/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1769 - accuracy: 0.6429\n","Epoch 756/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1768 - accuracy: 0.6429\n","Epoch 757/1000\n","1/1 [==============================] - 0s 18ms/step - loss: 0.1768 - accuracy: 0.6429\n","Epoch 758/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1768 - accuracy: 0.6429\n","Epoch 759/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1767 - accuracy: 0.6429\n","Epoch 760/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1767 - accuracy: 0.6429\n","Epoch 761/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1766 - accuracy: 0.6429\n","Epoch 762/1000\n","1/1 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[==============================] - 0s 10ms/step - loss: 0.1763 - accuracy: 0.6429\n","Epoch 772/1000\n","1/1 [==============================] - 0s 21ms/step - loss: 0.1762 - accuracy: 0.6429\n","Epoch 773/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1762 - accuracy: 0.6429\n","Epoch 774/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.1761 - accuracy: 0.6429\n","Epoch 775/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1761 - accuracy: 0.6429\n","Epoch 776/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1761 - accuracy: 0.6429\n","Epoch 777/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1760 - accuracy: 0.6429\n","Epoch 778/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1760 - accuracy: 0.6429\n","Epoch 779/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1760 - accuracy: 0.6429\n","Epoch 780/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1759 - accuracy: 0.6429\n","Epoch 781/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1759 - accuracy: 0.6429\n","Epoch 782/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1758 - accuracy: 0.6429\n","Epoch 783/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1758 - accuracy: 0.6429\n","Epoch 784/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1758 - accuracy: 0.6429\n","Epoch 785/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1757 - accuracy: 0.6429\n","Epoch 786/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1757 - accuracy: 0.6429\n","Epoch 787/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1756 - accuracy: 0.6429\n","Epoch 788/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1756 - accuracy: 0.6429\n","Epoch 789/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1756 - accuracy: 0.6429\n","Epoch 790/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1755 - accuracy: 0.6429\n","Epoch 791/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1755 - accuracy: 0.6429\n","Epoch 792/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1754 - accuracy: 0.6429\n","Epoch 793/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1754 - accuracy: 0.6429\n","Epoch 794/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1754 - accuracy: 0.6429\n","Epoch 795/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1753 - accuracy: 0.6429\n","Epoch 796/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1753 - accuracy: 0.6429\n","Epoch 797/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1753 - accuracy: 0.6429\n","Epoch 798/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1752 - accuracy: 0.6429\n","Epoch 799/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1752 - accuracy: 0.6429\n","Epoch 800/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1751 - accuracy: 0.6429\n","Epoch 801/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1751 - accuracy: 0.6429\n","Epoch 802/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1751 - accuracy: 0.6429\n","Epoch 803/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1750 - accuracy: 0.6429\n","Epoch 804/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1750 - accuracy: 0.6429\n","Epoch 805/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1749 - accuracy: 0.6429\n","Epoch 806/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1749 - accuracy: 0.6429\n","Epoch 807/1000\n","1/1 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[==============================] - 0s 14ms/step - loss: 0.1742 - accuracy: 0.6429\n","Epoch 826/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1741 - accuracy: 0.6429\n","Epoch 827/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1741 - accuracy: 0.6429\n","Epoch 828/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1741 - accuracy: 0.6429\n","Epoch 829/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1740 - accuracy: 0.6429\n","Epoch 830/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1740 - accuracy: 0.6429\n","Epoch 831/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1739 - accuracy: 0.6429\n","Epoch 832/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1739 - accuracy: 0.6429\n","Epoch 833/1000\n","1/1 [==============================] - 0s 21ms/step - loss: 0.1739 - accuracy: 0.6429\n","Epoch 834/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1738 - accuracy: 0.6429\n","Epoch 835/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1738 - accuracy: 0.6429\n","Epoch 836/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1737 - accuracy: 0.6429\n","Epoch 837/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1737 - accuracy: 0.6429\n","Epoch 838/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1737 - accuracy: 0.6429\n","Epoch 839/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1736 - accuracy: 0.6429\n","Epoch 840/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1736 - accuracy: 0.6429\n","Epoch 841/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1736 - accuracy: 0.6429\n","Epoch 842/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1735 - accuracy: 0.6429\n","Epoch 843/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1735 - accuracy: 0.6429\n","Epoch 844/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1734 - accuracy: 0.6429\n","Epoch 845/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1734 - accuracy: 0.6429\n","Epoch 846/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1734 - accuracy: 0.6429\n","Epoch 847/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1733 - accuracy: 0.6429\n","Epoch 848/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1733 - accuracy: 0.6429\n","Epoch 849/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1732 - accuracy: 0.6429\n","Epoch 850/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1732 - accuracy: 0.6429\n","Epoch 851/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1732 - accuracy: 0.6429\n","Epoch 852/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1731 - accuracy: 0.6429\n","Epoch 853/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1731 - accuracy: 0.6429\n","Epoch 854/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1730 - accuracy: 0.6429\n","Epoch 855/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1730 - accuracy: 0.6429\n","Epoch 856/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1730 - accuracy: 0.6429\n","Epoch 857/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1729 - accuracy: 0.6429\n","Epoch 858/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1729 - accuracy: 0.6429\n","Epoch 859/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1729 - accuracy: 0.6429\n","Epoch 860/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1728 - accuracy: 0.6429\n","Epoch 861/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1728 - accuracy: 0.6429\n","Epoch 862/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1727 - accuracy: 0.6429\n","Epoch 863/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1727 - accuracy: 0.6429\n","Epoch 864/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1727 - accuracy: 0.6429\n","Epoch 865/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1726 - accuracy: 0.6429\n","Epoch 866/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1726 - accuracy: 0.6429\n","Epoch 867/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1725 - accuracy: 0.6429\n","Epoch 868/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1725 - accuracy: 0.6429\n","Epoch 869/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1725 - accuracy: 0.6429\n","Epoch 870/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1724 - accuracy: 0.6429\n","Epoch 871/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1724 - accuracy: 0.6429\n","Epoch 872/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1724 - accuracy: 0.6429\n","Epoch 873/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1723 - accuracy: 0.6429\n","Epoch 874/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1723 - accuracy: 0.6429\n","Epoch 875/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1722 - accuracy: 0.6429\n","Epoch 876/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1722 - accuracy: 0.6429\n","Epoch 877/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1722 - accuracy: 0.6429\n","Epoch 878/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1721 - accuracy: 0.6429\n","Epoch 879/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1721 - accuracy: 0.6429\n","Epoch 880/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1720 - accuracy: 0.6429\n","Epoch 881/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1720 - accuracy: 0.6429\n","Epoch 882/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1720 - accuracy: 0.6429\n","Epoch 883/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1719 - accuracy: 0.6429\n","Epoch 884/1000\n","1/1 [==============================] - 0s 17ms/step - loss: 0.1719 - accuracy: 0.6429\n","Epoch 885/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1718 - accuracy: 0.6429\n","Epoch 886/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1718 - accuracy: 0.6429\n","Epoch 887/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1718 - accuracy: 0.6429\n","Epoch 888/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1717 - accuracy: 0.6429\n","Epoch 889/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1717 - accuracy: 0.6429\n","Epoch 890/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1717 - accuracy: 0.6429\n","Epoch 891/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1716 - accuracy: 0.6429\n","Epoch 892/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1716 - accuracy: 0.6429\n","Epoch 893/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1715 - accuracy: 0.6429\n","Epoch 894/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1715 - accuracy: 0.6429\n","Epoch 895/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1715 - accuracy: 0.6429\n","Epoch 896/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1714 - accuracy: 0.6429\n","Epoch 897/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1714 - accuracy: 0.6429\n","Epoch 898/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1713 - accuracy: 0.6429\n","Epoch 899/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1713 - accuracy: 0.6429\n","Epoch 900/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1713 - accuracy: 0.6429\n","Epoch 901/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1712 - accuracy: 0.6429\n","Epoch 902/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1712 - accuracy: 0.6429\n","Epoch 903/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1712 - accuracy: 0.6429\n","Epoch 904/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1711 - accuracy: 0.6429\n","Epoch 905/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1711 - accuracy: 0.6429\n","Epoch 906/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1710 - accuracy: 0.6429\n","Epoch 907/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1710 - accuracy: 0.6429\n","Epoch 908/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1710 - accuracy: 0.6429\n","Epoch 909/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1709 - accuracy: 0.6429\n","Epoch 910/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1709 - accuracy: 0.6429\n","Epoch 911/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1708 - accuracy: 0.6429\n","Epoch 912/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1708 - accuracy: 0.7857\n","Epoch 913/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1708 - accuracy: 0.7857\n","Epoch 914/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1707 - accuracy: 0.7857\n","Epoch 915/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1707 - accuracy: 0.7857\n","Epoch 916/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1706 - accuracy: 0.7857\n","Epoch 917/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1706 - accuracy: 0.7857\n","Epoch 918/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1706 - accuracy: 0.7857\n","Epoch 919/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1705 - accuracy: 0.7857\n","Epoch 920/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1705 - accuracy: 0.7857\n","Epoch 921/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1705 - accuracy: 0.7857\n","Epoch 922/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1704 - accuracy: 0.7857\n","Epoch 923/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1704 - accuracy: 0.7857\n","Epoch 924/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1703 - accuracy: 0.7857\n","Epoch 925/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1703 - accuracy: 0.7857\n","Epoch 926/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1703 - accuracy: 0.7857\n","Epoch 927/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1702 - accuracy: 0.7857\n","Epoch 928/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1702 - accuracy: 0.7857\n","Epoch 929/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1701 - accuracy: 0.7857\n","Epoch 930/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1701 - accuracy: 0.7857\n","Epoch 931/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1701 - accuracy: 0.7857\n","Epoch 932/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1700 - accuracy: 0.7857\n","Epoch 933/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1700 - accuracy: 0.7857\n","Epoch 934/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1700 - accuracy: 0.7857\n","Epoch 935/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1699 - accuracy: 0.7857\n","Epoch 936/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1699 - accuracy: 0.7857\n","Epoch 937/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1698 - accuracy: 0.7857\n","Epoch 938/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1698 - accuracy: 0.7857\n","Epoch 939/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1698 - accuracy: 0.7857\n","Epoch 940/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1697 - accuracy: 0.7857\n","Epoch 941/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1697 - accuracy: 0.7857\n","Epoch 942/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1697 - accuracy: 0.7857\n","Epoch 943/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1696 - accuracy: 0.7857\n","Epoch 944/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1696 - accuracy: 0.7857\n","Epoch 945/1000\n","1/1 [==============================] - 0s 15ms/step - loss: 0.1695 - accuracy: 0.7857\n","Epoch 946/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1695 - accuracy: 0.7857\n","Epoch 947/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1695 - accuracy: 0.7857\n","Epoch 948/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1694 - accuracy: 0.7857\n","Epoch 949/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1694 - accuracy: 0.7857\n","Epoch 950/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1694 - accuracy: 0.7857\n","Epoch 951/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1693 - accuracy: 0.7857\n","Epoch 952/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1693 - accuracy: 0.7857\n","Epoch 953/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1692 - accuracy: 0.7857\n","Epoch 954/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1692 - accuracy: 0.7857\n","Epoch 955/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1692 - accuracy: 0.7857\n","Epoch 956/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1691 - accuracy: 0.7857\n","Epoch 957/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1691 - accuracy: 0.7857\n","Epoch 958/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1691 - accuracy: 0.7857\n","Epoch 959/1000\n","1/1 [==============================] - 0s 12ms/step - loss: 0.1690 - accuracy: 0.7857\n","Epoch 960/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1690 - accuracy: 0.7857\n","Epoch 961/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1689 - accuracy: 0.7857\n","Epoch 962/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1689 - accuracy: 0.7857\n","Epoch 963/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1689 - accuracy: 0.7857\n","Epoch 964/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1688 - accuracy: 0.7857\n","Epoch 965/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1688 - accuracy: 0.7857\n","Epoch 966/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1688 - accuracy: 0.7857\n","Epoch 967/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1687 - accuracy: 0.7857\n","Epoch 968/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1687 - accuracy: 0.7857\n","Epoch 969/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1687 - accuracy: 0.7857\n","Epoch 970/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1686 - accuracy: 0.7857\n","Epoch 971/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1686 - accuracy: 0.7857\n","Epoch 972/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1686 - accuracy: 0.7857\n","Epoch 973/1000\n","1/1 [==============================] - 0s 8ms/step - loss: 0.1685 - accuracy: 0.7857\n","Epoch 974/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1685 - accuracy: 0.7857\n","Epoch 975/1000\n","1/1 [==============================] - 0s 13ms/step - loss: 0.1684 - accuracy: 0.7857\n","Epoch 976/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1684 - accuracy: 0.7857\n","Epoch 977/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1684 - accuracy: 0.7857\n","Epoch 978/1000\n","1/1 [==============================] - 0s 16ms/step - loss: 0.1683 - accuracy: 0.7857\n","Epoch 979/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1683 - accuracy: 0.7857\n","Epoch 980/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1683 - accuracy: 0.7857\n","Epoch 981/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1682 - accuracy: 0.7857\n","Epoch 982/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1682 - accuracy: 0.7857\n","Epoch 983/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1682 - accuracy: 0.7857\n","Epoch 984/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1681 - accuracy: 0.7857\n","Epoch 985/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1681 - accuracy: 0.7857\n","Epoch 986/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1680 - accuracy: 0.7857\n","Epoch 987/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1680 - accuracy: 0.7857\n","Epoch 988/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1680 - accuracy: 0.7857\n","Epoch 989/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1679 - accuracy: 0.7857\n","Epoch 990/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1679 - accuracy: 0.7857\n","Epoch 991/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1679 - accuracy: 0.7857\n","Epoch 992/1000\n","1/1 [==============================] - 0s 14ms/step - loss: 0.1678 - accuracy: 0.7857\n","Epoch 993/1000\n","1/1 [==============================] - 0s 11ms/step - loss: 0.1678 - accuracy: 0.7857\n","Epoch 994/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1678 - accuracy: 0.7857\n","Epoch 995/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1677 - accuracy: 0.7857\n","Epoch 996/1000\n","1/1 [==============================] - 0s 10ms/step - loss: 0.1677 - accuracy: 0.7857\n","Epoch 997/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1677 - accuracy: 0.7857\n","Epoch 998/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1676 - accuracy: 0.7857\n","Epoch 999/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1676 - accuracy: 0.7857\n","Epoch 1000/1000\n","1/1 [==============================] - 0s 9ms/step - loss: 0.1675 - accuracy: 0.7857\n"]},{"output_type":"execute_result","data":{"text/plain":["<keras.callbacks.History at 0x7fe0e5622ac0>"]},"metadata":{},"execution_count":334}]},{"cell_type":"code","source":["a= model.predict([[-1.48081501, -1.28719181, -1.48824711,  0.        ,  0.90834052,\n","        -1.5468686 , -1.13857457,  1.61607216, -0.40435899,  0.73995597,\n","        -2.        ,  2.        ]])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"R8_L8jLZ6Ras","outputId":"ce066f4b-eb93-456f-adb4-d6da02acc063"},"id":"R8_L8jLZ6Ras","execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["1/1 [==============================] - 0s 137ms/step\n"]}]},{"cell_type":"code","source":["a"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DGlsgfgX6Rlz","outputId":"49f2c548-26aa-41a8-8257-19e8f5df8669"},"id":"DGlsgfgX6Rlz","execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[0.50318307]], dtype=float32)"]},"metadata":{},"execution_count":336}]},{"cell_type":"code","source":["aa=np.array([a], \"float32\")"],"metadata":{"id":"sMwxC_BR_5TM"},"id":"sMwxC_BR_5TM","execution_count":null,"outputs":[]},{"cell_type":"code","source":["aa"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Av5BRf8e_-4U","outputId":"87634b65-1087-4e60-cc81-58fcf478b96d"},"id":"Av5BRf8e_-4U","execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[[0.50318307]]], dtype=float32)"]},"metadata":{},"execution_count":338}]},{"cell_type":"code","source":["if (aa>0.5):\n","  print(\"Champions SI\")\n","else:\n","  print(\"Champions NO\")\n"," "],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0VTdACARCoj-","outputId":"26a76952-f6c6-4e2d-da3c-0c9b875d820a"},"id":"0VTdACARCoj-","execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Champions SI\n"]}]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.8.8"},"colab":{"provenance":[]}},"nbformat":4,"nbformat_minor":5}