Metadata-Version: 2.1
Name: sgt
Version: 2.0.0b5
Summary: Sequence Graph Transform (SGT) is a sequence embedding function. SGT extracts the short- and long-term sequence features and embeds them in a finite-dimensional feature space. With SGT you can tune the amount of short- to long-term patterns extracted in the embeddings without any increase in the computation.
Home-page: https://github.com/cran2367/sgt
Author: Chitta Ranjan
Author-email: cran2367@gmail.com
License: UNKNOWN
Description: ```python
        # -*- coding: utf-8 -*-
        # Authors: Chitta Ranjan <cran2367@gmail.com>
        #
        # License: BSD 3 clause
        ```
        
        # Sgt definition.
        
        ## Purpose
        
        Sequence Graph Transform (SGT) is a sequence embedding function. SGT extracts the short- and long-term sequence features and embeds them in a finite-dimensional feature space. With SGT you can tune the amount of short- to long-term patterns extracted in the embeddings without any  increase in the computation."
        
        ```
        class Sgt():
            '''
            Compute embedding of a single or a collection of discrete item 
            sequences. A discrete item sequence is a sequence made from a set
            discrete elements, also known as alphabet set. For example,
            suppose the alphabet set is the set of roman letters, 
            {A, B, ..., Z}. This set is made of discrete elements. Examples of
            sequences from such a set are AABADDSA, UADSFJPFFFOIHOUGD, etc.
            Such sequence datasets are commonly found in online industry,
            for example, item purchase history, where the alphabet set is
            the set of all product items. Sequence datasets are abundant in
            bioinformatics as protein sequences.
            Using the embeddings created here, classification and clustering
            models can be built for sequence datasets.
            Read more in https://arxiv.org/pdf/1608.03533.pdf
            '''
        ```
            Parameters
            ----------
            Input:
        
            alphabets       Optional, except if mode is Spark. 
                            The set of alphabets that make up all 
                            the sequences in the dataset. If not passed, the
                            alphabet set is automatically computed as the 
                            unique set of elements that make all the sequences.
                            A list or 1d-array of the set of elements that make up the      
                            sequences. For example, np.array(["A", "B", "C"].
                            If mode is 'spark', the alphabets are necessary.
        
            kappa           Tuning parameter, kappa > 0, to change the extraction of 
                            long-term dependency. Higher the value the lesser
                            the long-term dependency captured in the embedding.
                            Typical values for kappa are 1, 5, 10.
        
            lengthsensitive Default false. This is set to true if the embedding of
                            should have the information of the length of the sequence.
                            If set to false then the embedding of two sequences with
                            similar pattern but different lengths will be the same.
                            lengthsensitive = false is similar to length-normalization.
                            
            flatten         Default True. If True the SGT embedding is flattened and returned as
                            a vector. Otherwise, it is returned as a matrix with the row and col
                            names same as the alphabets. The matrix form is used for            
                            interpretation purposes. Especially, to understand how the alphabets
                            are "related". Otherwise, for applying machine learning or deep
                            learning algorithms, the embedding vectors are required.
            
            mode            Choices in {'default', 'multiprocessing', 'spark'}.
            
            processors      Used if mode is 'multiprocessing'. By default, the 
                            number of processors used in multiprocessing is
                            number of available - 1.
            
            lazy            Used if mode is 'spark'. Default is False. If False,
                            the SGT embeddings are computed for each sequence
                            in the inputted RDD and returned as a list of 
                            embedding vectors. Otherwise, the RDD map is returned.
            '''
        
            Attributes
            ----------
            def fit(sequence)
            
            Extract Sequence Graph Transform features using Algorithm-2 in https://arxiv.org/abs/1608.03533.
            Input:
            sequence        An array of discrete elements. For example,
                            np.array(["B","B","A","C","A","C","A","A","B","A"].
                            
            Output: 
            sgt embedding   sgt matrix or vector (depending on Flatten==False or True) of the sequence
            
            
            --
            def fit_transform(corpus)
            
            Extract SGT embeddings for all sequences in a corpus. It finds
            the alphabets encompassing all the sequences in the corpus, if not inputted. 
            However, if the mode is 'spark', then the alphabets list has to be
            explicitly given in Sgt object declaration.
            
            Input:
            corpus          A list of sequences. Each sequence is a list of alphabets.
            
            Output:
            sgt embedding of all sequences in the corpus.
            
            
            --
            def transform(corpus)
            
            Find SGT embeddings of a new data sample belonging to the same population
            of the corpus that was fitted initially.
        
        ## Illustrative examples
        
        
        ```python
        import numpy as np
        import pandas as pd
        from itertools import chain
        import warnings
        
        ########
        from sklearn.preprocessing import LabelEncoder
        import tensorflow as tf
        from keras.datasets import imdb
        from tensorflow.keras.models import Sequential
        from tensorflow.keras.layers import Dense
        from tensorflow.keras.layers import LSTM
        from tensorflow.keras.layers import Dropout
        from tensorflow.keras.layers import Activation
        from tensorflow.keras.layers import Flatten
        from tensorflow.keras.layers import Embedding
        from tensorflow.keras.preprocessing import sequence
        
        from sklearn.model_selection import train_test_split
        from sklearn.model_selection import KFold
        from sklearn.model_selection import StratifiedKFold
        import sklearn.metrics
        import time
        
        from sklearn.decomposition import PCA
        from sklearn.cluster import KMeans
        
        import matplotlib.pyplot as plt
        %matplotlib inline
        
        np.random.seed(7) # fix random seed for reproducibility
        
        from sgt import Sgt
        ```
        
            Using TensorFlow backend.
        
        
        ## Installation Test Examples
        
        
        ```python
        # Learning a sgt embedding as a matrix with 
        # rows and columns as the sequence alphabets. 
        # This embedding shows the relationship between 
        # the alphabets. The higher the value the 
        # stronger the relationship.
        
        sgt = Sgt(flatten=False)
        sequence = np.array(["B","B","A","C","A","C","A","A","B","A"])
        sgt.fit(sequence)
        ```
        
        
        
        
        <div>
        <style scoped>
            .dataframe tbody tr th:only-of-type {
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        </style>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>A</th>
              <th>B</th>
              <th>C</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>A</th>
              <td>0.906163</td>
              <td>1.310023</td>
              <td>2.618487</td>
            </tr>
            <tr>
              <th>B</th>
              <td>0.865694</td>
              <td>1.230423</td>
              <td>0.525440</td>
            </tr>
            <tr>
              <th>C</th>
              <td>1.371416</td>
              <td>0.282625</td>
              <td>1.353353</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        
        
        
        ```python
        # Learning the sgt embeddings as vector for
        # all sequences in a corpus.
        
        sgt = Sgt(kappa=1, lengthsensitive=False)
        corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
        
        s = sgt.fit_transform(corpus)
        print(s)
        ```
        
            [[0.90616284 1.31002279 2.6184865  0.         0.         0.86569371
              1.23042262 0.52543984 0.         0.         1.37141609 0.28262508
              1.35335283 0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.        ]
             [0.         0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.         0.09157819 0.92166965 0.         0.         0.
              0.         0.         0.         0.         0.         0.92166965
              1.45182361]]
        
        
        
        ```python
        # Change the parameters from default to
        # a tuned value.
        
        sgt = Sgt(kappa=5, lengthsensitive=True)
        corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
        
        s = sgt.fit_transform(corpus)
        print(s)
        ```
        
            [[0.23305129 0.2791752  0.33922608 0.         0.         0.26177435
              0.29531212 0.10270374 0.         0.         0.28654051 0.04334255
              0.13533528 0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.        ]
             [0.         0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.         0.01831564 0.29571168 0.         0.         0.
              0.         0.         0.         0.         0.         0.29571168
              0.3394528 ]]
        
        
        
        ```python
        # Change the mode for faster computation.
        # Mode: 'multiprocessing'
        # Uses the multiple processors (CPUs) avalaible.
        
        corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
        
        sgt = Sgt(mode='multiprocessing')
        s = sgt.fit_transform(corpus)
        print(s)
        ```
        
            [[0.90616284 1.31002279 2.6184865  0.         0.         0.86569371
              1.23042262 0.52543984 0.         0.         1.37141609 0.28262508
              1.35335283 0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.        ]
             [0.         0.         0.         0.         0.         0.
              0.         0.         0.         0.         0.         0.
              0.         0.09157819 0.92166965 0.         0.         0.
              0.         0.         0.         0.         0.         0.92166965
              1.45182361]]
        
        
        
        ```python
        # Change the mode for faster computation.
        # Mode: 'spark'
        # Uses spark RDD.
        
        from pyspark import SparkContext
        sc = SparkContext("local", "app")
        
        corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
        
        rdd = sc.parallelize(corpus)
        
        sgt_sc = sgt.Sgt(kappa = 1, 
                         lengthsensitive = False, 
                         mode="spark", 
                         alphabets=["A", "B", "C", "D", "Z"],
                         lazy=False)
        
        s = sgt_sc.fit_transform(corpus=rdd)
        
        print(s)
        ```
        
        # Real data examples
        
        ## Protein Sequence Data Analysis
        
        The data used here is taken from www.uniprot.org. This is a public database for proteins. The data contains the protein sequences and their functions. In the following, we will demonstrate 
        - clustering of the sequences.
        - classification of the sequences with the functions as labels.
        
        
        ```python
        protein_data=pd.read_csv('../data/protein_classification.csv')
        X=protein_data['Sequence']
        def split(word): 
            return [char for char in word] 
        
        sequences = [split(x) for x in X]
        print(sequences[0])
        ```
        
            ['M', 'E', 'I', 'E', 'K', 'T', 'N', 'R', 'M', 'N', 'A', 'L', 'F', 'E', 'F', 'Y', 'A', 'A', 'L', 'L', 'T', 'D', 'K', 'Q', 'M', 'N', 'Y', 'I', 'E', 'L', 'Y', 'Y', 'A', 'D', 'D', 'Y', 'S', 'L', 'A', 'E', 'I', 'A', 'E', 'E', 'F', 'G', 'V', 'S', 'R', 'Q', 'A', 'V', 'Y', 'D', 'N', 'I', 'K', 'R', 'T', 'E', 'K', 'I', 'L', 'E', 'D', 'Y', 'E', 'M', 'K', 'L', 'H', 'M', 'Y', 'S', 'D', 'Y', 'I', 'V', 'R', 'S', 'Q', 'I', 'F', 'D', 'Q', 'I', 'L', 'E', 'R', 'Y', 'P', 'K', 'D', 'D', 'F', 'L', 'Q', 'E', 'Q', 'I', 'E', 'I', 'L', 'T', 'S', 'I', 'D', 'N', 'R', 'E']
        
        
        ### Generating sequence embeddings
        
        
        ```python
        sgt = Sgt(kappa=1, lengthsensitive=False, mode='multiprocessing')
        ```
        
        
        ```python
        %%time
        embedding = sgt.fit_transform(corpus=sequences)
        ```
        
            CPU times: user 79.5 ms, sys: 46 ms, total: 125 ms
            Wall time: 6.61 s
        
        
        
        ```python
        embedding.shape
        ```
        
        
        
        
            (2112, 400)
        
        
        
        #### Sequence Clustering
        We perform PCA on the sequence embeddings and then do kmeans clustering.
        
        
        ```python
        pca = PCA(n_components=2)
        pca.fit(embedding)
        X=pca.transform(embedding)
        
        print(np.sum(pca.explained_variance_ratio_))
        df = pd.DataFrame(data=X, columns=['x1', 'x2'])
        df.head()
        ```
        
            0.6432744907364913
        
        
        
        
        
        <div>
        <style scoped>
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            }
        </style>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>x1</th>
              <th>x2</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>0.384913</td>
              <td>-0.269873</td>
            </tr>
            <tr>
              <th>1</th>
              <td>0.022764</td>
              <td>0.135995</td>
            </tr>
            <tr>
              <th>2</th>
              <td>0.177792</td>
              <td>-0.172454</td>
            </tr>
            <tr>
              <th>3</th>
              <td>0.168074</td>
              <td>-0.147334</td>
            </tr>
            <tr>
              <th>4</th>
              <td>0.383616</td>
              <td>-0.271163</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        
        
        
        ```python
        kmeans = KMeans(n_clusters=3, max_iter =300)
        kmeans.fit(df)
        
        labels = kmeans.predict(df)
        centroids = kmeans.cluster_centers_
        
        fig = plt.figure(figsize=(5, 5))
        colmap = {1: 'r', 2: 'g', 3: 'b'}
        colors = list(map(lambda x: colmap[x+1], labels))
        plt.scatter(df['x1'], df['x2'], color=colors, alpha=0.5, edgecolor=colors)
        ```
        
        
        
        
            <matplotlib.collections.PathCollection at 0x13bd97438>
        
        
        
        
        ![png](output_19_1.png)
        
        
        #### Sequence Classification
        We perform PCA on the sequence embeddings and then do kmeans clustering.
        
        
        ```python
        y = protein_data['Function [CC]']
        encoder = LabelEncoder()
        encoder.fit(y)
        encoded_y = encoder.transform(y)
        ```
        
        We will perform a 10-fold cross-validation to measure the performance of the classification model.
        
        
        ```python
        kfold = 10
        X = pd.DataFrame(embedding)
        y = encoded_y
        
        random_state = 1
        
        test_F1 = np.zeros(kfold)
        skf = KFold(n_splits = kfold, shuffle = True, random_state = random_state)
        k = 0
        epochs = 50
        batch_size = 128
        
        for train_index, test_index in skf.split(X, y):
            X_train, X_test = X.iloc[train_index], X.iloc[test_index]
            y_train, y_test = y[train_index], y[test_index]
            
            model = Sequential()
            model.add(Dense(64, input_shape = (X_train.shape[1],))) 
            model.add(Activation('relu'))
            model.add(Dropout(0.5))
            model.add(Dense(32))
            model.add(Activation('relu'))
            model.add(Dropout(0.5))
            model.add(Dense(1))
            model.add(Activation('sigmoid'))
            model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
            
            model.fit(X_train, y_train ,batch_size=batch_size, epochs=epochs, verbose=0)
            
            y_pred = model.predict_proba(X_test).round().astype(int)
            y_train_pred = model.predict_proba(X_train).round().astype(int)
        
            test_F1[k] = sklearn.metrics.f1_score(y_test, y_pred)
            k+=1
            
        print ('Average f1 score', np.mean(test_F1))
        ```
        
            Average f1 score 1.0
        
        
        ## Weblog Data Analysis
        This data sample is taken from https://www.ll.mit.edu/r-d/datasets/1998-darpa-intrusion-detection-evaluation-dataset. 
        This is a network intrusion data containing audit logs and any attack as a positive label. Since, network intrusion is a rare event, the data is unbalanced. Here we will,
        - build a sequence classification model to predict a network intrusion.
        
        Each sequence contains in the data is a series of activity, for example, {login, password}. The _alphabets_ in the input data sequences are already encoded into integers. The original sequences data file is also present in the `/data` directory.
        
        
        ```python
        darpa_data = pd.read_csv('../data/darpa_data.csv')
        darpa_data.columns
        ```
        
        
        
        
            Index(['timeduration', 'seqlen', 'seq', 'class'], dtype='object')
        
        
        
        
        ```python
        X = darpa_data['seq']
        sequences = [x.split('~') for x in X]
        ```
        
        
        ```python
        y = darpa_data['class']
        encoder = LabelEncoder()
        encoder.fit(y)
        y = encoder.transform(y)
        ```
        
        ### Generating sequence embeddings
        In this data, the sequence embeddings should be length-sensitive. The lengths are important here because sequences with similar patterns but different lengths can have different labels. Consider a simple example of two sessions: `{login, pswd, login, pswd,...}` and `{login, pswd,...(repeated several times)..., login, pswd}`. While the first session can be a regular user mistyping the password once, the other session is possibly an attack to guess the password. Thus, the sequence lengths are as important as the patterns.
        
        
        ```python
        sgt_darpa = Sgt(kappa=5, lengthsensitive=True, mode='multiprocessing')
        ```
        
        
        ```python
        embedding = sgt_darpa.fit_transform(corpus=sequences)
        ```
        
        
        ```python
        pd.DataFrame(embedding).to_csv(path_or_buf='tmp.csv', index=False)
        pd.DataFrame(embedding).head()
        ```
        
        
        
        
        <div>
        <style scoped>
            .dataframe tbody tr th:only-of-type {
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                text-align: right;
            }
        </style>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>0</th>
              <th>1</th>
              <th>2</th>
              <th>3</th>
              <th>4</th>
              <th>5</th>
              <th>6</th>
              <th>7</th>
              <th>8</th>
              <th>9</th>
              <th>...</th>
              <th>2391</th>
              <th>2392</th>
              <th>2393</th>
              <th>2394</th>
              <th>2395</th>
              <th>2396</th>
              <th>2397</th>
              <th>2398</th>
              <th>2399</th>
              <th>2400</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>0.069114</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>...</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
            </tr>
            <tr>
              <th>1</th>
              <td>0.000000</td>
              <td>0.0</td>
              <td>4.804190e-09</td>
              <td>7.041516e-10</td>
              <td>0.0</td>
              <td>2.004958e-12</td>
              <td>0.000132</td>
              <td>1.046458e-07</td>
              <td>5.863092e-16</td>
              <td>7.568986e-23</td>
              <td>...</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.540296</td>
              <td>5.739230e-32</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
            </tr>
            <tr>
              <th>2</th>
              <td>0.000000</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>...</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
            </tr>
            <tr>
              <th>3</th>
              <td>0.785666</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000</td>
              <td>1.950089e-03</td>
              <td>2.239981e-04</td>
              <td>2.343180e-07</td>
              <td>...</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.528133</td>
              <td>1.576703e-09</td>
              <td>0.0</td>
              <td>2.516644e-29</td>
              <td>1.484843e-57</td>
            </tr>
            <tr>
              <th>4</th>
              <td>0.000000</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
              <td>...</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.000000</td>
              <td>0.000000e+00</td>
              <td>0.0</td>
              <td>0.000000e+00</td>
              <td>0.000000e+00</td>
            </tr>
          </tbody>
        </table>
        <p>5 rows × 2401 columns</p>
        </div>
        
        
        
        #### Applying PCA on the embeddings
        The embeddings are sparse. We, therefore, apply PCA on the embeddings.
        
        
        ```python
        from sklearn.decomposition import PCA
        pca = PCA(n_components=35)
        pca.fit(embedding)
        X = pca.transform(embedding)
        print(np.sum(pca.explained_variance_ratio_))
        ```
        
            0.9887812978739061
        
        
        #### Building a Multi-Layer Perceptron Classifier
        The PCA transforms of the embeddings are used directly as inputs to an MLP classifier.
        
        
        ```python
        kfold = 3
        random_state = 11
        
        test_F1 = np.zeros(kfold)
        time_k = np.zeros(kfold)
        skf = StratifiedKFold(n_splits=kfold, shuffle=True, random_state=random_state)
        k = 0
        epochs = 300
        batch_size = 15
        
        # class_weight = {0 : 1., 1: 1.,}  # The weights can be changed and made inversely proportional to the class size to improve the accuracy.
        class_weight = {0 : 0.12, 1: 0.88,}
        
        for train_index, test_index in skf.split(X, y):
            X_train, X_test = X[train_index], X[test_index]
            y_train, y_test = y[train_index], y[test_index]
            
            model = Sequential()
            model.add(Dense(128, input_shape=(X_train.shape[1],))) 
            model.add(Activation('relu'))
            model.add(Dropout(0.5))
            model.add(Dense(1))
            model.add(Activation('sigmoid'))
            model.summary()
            model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
            
            start_time = time.time()
            model.fit(X_train, y_train ,batch_size=batch_size, epochs=epochs, verbose=1, class_weight=class_weight)
            end_time = time.time()
            time_k[k] = end_time-start_time
        
            y_pred = model.predict_proba(X_test).round().astype(int)
            y_train_pred = model.predict_proba(X_train).round().astype(int)
            test_F1[k] = sklearn.metrics.f1_score(y_test, y_pred)
            k += 1
        ```
        
            Model: "sequential_10"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            dense_30 (Dense)             (None, 128)               4608      
            _________________________________________________________________
            activation_30 (Activation)   (None, 128)               0         
            _________________________________________________________________
            dropout_20 (Dropout)         (None, 128)               0         
            _________________________________________________________________
            dense_31 (Dense)             (None, 1)                 129       
            _________________________________________________________________
            activation_31 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 4,737
            Trainable params: 4,737
            Non-trainable params: 0
            _________________________________________________________________
            WARNING:tensorflow:sample_weight modes were coerced from
              ...
                to  
              ['...']
            Train on 74 samples
            Epoch 1/300
            74/74 [==============================] - 0s 6ms/sample - loss: 0.1404 - accuracy: 0.6216
            Epoch 2/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.1386 - accuracy: 0.6486
            Epoch 3/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.1404 - accuracy: 0.7568
            Epoch 4/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.1309 - accuracy: 0.7297
            Epoch 5/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.1274 - accuracy: 0.7162
            Epoch 6/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.1142 - accuracy: 0.7568
            Epoch 7/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.1041 - accuracy: 0.8784
            Epoch 8/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.1027 - accuracy: 0.8243
            Epoch 9/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0991 - accuracy: 0.8378
            Epoch 10/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0862 - accuracy: 0.8649
            Epoch 11/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0930 - accuracy: 0.8649
            Epoch 12/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0898 - accuracy: 0.8649
            Epoch 13/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0827 - accuracy: 0.8784
            Epoch 14/300
            74/74 [==============================] - 0s 154us/sample - loss: 0.0790 - accuracy: 0.8784
            Epoch 15/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0769 - accuracy: 0.8649
            Epoch 16/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0801 - accuracy: 0.8514
            Epoch 17/300
            74/74 [==============================] - 0s 139us/sample - loss: 0.0740 - accuracy: 0.8784
            Epoch 18/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0723 - accuracy: 0.8649
            Epoch 19/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0679 - accuracy: 0.8649
            Epoch 20/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0704 - accuracy: 0.8919
            Epoch 21/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0621 - accuracy: 0.8649
            Epoch 22/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0627 - accuracy: 0.8919
            Epoch 23/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0552 - accuracy: 0.8784
            Epoch 24/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0599 - accuracy: 0.8784
            Epoch 25/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0596 - accuracy: 0.8514
            Epoch 26/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0579 - accuracy: 0.8784
            Epoch 27/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0513 - accuracy: 0.8784
            Epoch 28/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0533 - accuracy: 0.8784
            Epoch 29/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0559 - accuracy: 0.8784
            Epoch 30/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0537 - accuracy: 0.8649
            Epoch 31/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0472 - accuracy: 0.8649
            Epoch 32/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0494 - accuracy: 0.8514
            Epoch 33/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0511 - accuracy: 0.8649
            Epoch 34/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0473 - accuracy: 0.8649
            Epoch 35/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0507 - accuracy: 0.8649
            Epoch 36/300
            74/74 [==============================] - 0s 137us/sample - loss: 0.0468 - accuracy: 0.8649
            Epoch 37/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0459 - accuracy: 0.8649
            Epoch 38/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0428 - accuracy: 0.8649
            Epoch 39/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0439 - accuracy: 0.8649
            Epoch 40/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0388 - accuracy: 0.8649
            Epoch 41/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0406 - accuracy: 0.8649
            Epoch 42/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0450 - accuracy: 0.8919
            Epoch 43/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0403 - accuracy: 0.8784
            Epoch 44/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0463 - accuracy: 0.8649
            Epoch 45/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0443 - accuracy: 0.8784
            Epoch 46/300
            74/74 [==============================] - 0s 157us/sample - loss: 0.0437 - accuracy: 0.8514
            Epoch 47/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0379 - accuracy: 0.8919
            Epoch 48/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0388 - accuracy: 0.8784
            Epoch 49/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.0403 - accuracy: 0.8784
            Epoch 50/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0344 - accuracy: 0.8919
            Epoch 51/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0378 - accuracy: 0.8649
            Epoch 52/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0403 - accuracy: 0.8784
            Epoch 53/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0372 - accuracy: 0.9054
            Epoch 54/300
            74/74 [==============================] - 0s 146us/sample - loss: 0.0397 - accuracy: 0.8649
            Epoch 55/300
            74/74 [==============================] - 0s 141us/sample - loss: 0.0408 - accuracy: 0.8784
            Epoch 56/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0422 - accuracy: 0.8649
            Epoch 57/300
            74/74 [==============================] - 0s 143us/sample - loss: 0.0372 - accuracy: 0.8649
            Epoch 58/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0380 - accuracy: 0.8649
            Epoch 59/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0413 - accuracy: 0.8649
            Epoch 60/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0327 - accuracy: 0.8649
            Epoch 61/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0358 - accuracy: 0.8649
            Epoch 62/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 63/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0393 - accuracy: 0.8649
            Epoch 64/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0387 - accuracy: 0.8784
            Epoch 65/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0366 - accuracy: 0.8649
            Epoch 66/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0328 - accuracy: 0.8784
            Epoch 67/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0390 - accuracy: 0.8649
            Epoch 68/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0324 - accuracy: 0.8919
            Epoch 69/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 70/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0328 - accuracy: 0.8784
            Epoch 71/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 72/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0383 - accuracy: 0.8514
            Epoch 73/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0366 - accuracy: 0.8649
            Epoch 74/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0359 - accuracy: 0.8919
            Epoch 75/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0395 - accuracy: 0.8514
            Epoch 76/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0363 - accuracy: 0.8649
            Epoch 77/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0346 - accuracy: 0.8784
            Epoch 78/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0370 - accuracy: 0.8649
            Epoch 79/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0319 - accuracy: 0.8919
            Epoch 80/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 81/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0365 - accuracy: 0.8649
            Epoch 82/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0359 - accuracy: 0.8514
            Epoch 83/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0319 - accuracy: 0.8784
            Epoch 84/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0361 - accuracy: 0.8649
            Epoch 85/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0294 - accuracy: 0.8784
            Epoch 86/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0360 - accuracy: 0.8784
            Epoch 87/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0325 - accuracy: 0.8784
            Epoch 88/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0303 - accuracy: 0.8919
            Epoch 89/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0309 - accuracy: 0.8784
            Epoch 90/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0347 - accuracy: 0.8784
            Epoch 91/300
            74/74 [==============================] - 0s 139us/sample - loss: 0.0379 - accuracy: 0.8649
            Epoch 92/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0382 - accuracy: 0.8514
            Epoch 93/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0349 - accuracy: 0.8919
            Epoch 94/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0274 - accuracy: 0.8919
            Epoch 95/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0368 - accuracy: 0.8514
            Epoch 96/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0281 - accuracy: 0.8649
            Epoch 97/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0291 - accuracy: 0.9054
            Epoch 98/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0299 - accuracy: 0.9054
            Epoch 99/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0287 - accuracy: 0.8649
            Epoch 100/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8649
            Epoch 101/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0316 - accuracy: 0.8919
            Epoch 102/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0299 - accuracy: 0.8649
            Epoch 103/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0353 - accuracy: 0.8784
            Epoch 104/300
            74/74 [==============================] - 0s 105us/sample - loss: 0.0347 - accuracy: 0.8514
            Epoch 105/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0294 - accuracy: 0.8784
            Epoch 106/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0344 - accuracy: 0.8784
            Epoch 107/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0323 - accuracy: 0.8919
            Epoch 108/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0297 - accuracy: 0.9189
            Epoch 109/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0333 - accuracy: 0.8649
            Epoch 110/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0300 - accuracy: 0.8649
            Epoch 111/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0369 - accuracy: 0.8514
            Epoch 112/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0323 - accuracy: 0.8919
            Epoch 113/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0361 - accuracy: 0.8919
            Epoch 114/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0336 - accuracy: 0.8649
            Epoch 115/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0291 - accuracy: 0.8649
            Epoch 116/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0351 - accuracy: 0.8649
            Epoch 117/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0288 - accuracy: 0.8649
            Epoch 118/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0329 - accuracy: 0.8919
            Epoch 119/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0393 - accuracy: 0.8784
            Epoch 120/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0234 - accuracy: 0.8919
            Epoch 121/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0381 - accuracy: 0.8784
            Epoch 122/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0319 - accuracy: 0.8784
            Epoch 123/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0286 - accuracy: 0.8919
            Epoch 124/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0335 - accuracy: 0.8784
            Epoch 125/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0324 - accuracy: 0.9054
            Epoch 126/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0268 - accuracy: 0.8784
            Epoch 127/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 128/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0326 - accuracy: 0.9054
            Epoch 129/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8784
            Epoch 130/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0306 - accuracy: 0.8784
            Epoch 131/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 132/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0312 - accuracy: 0.8784
            Epoch 133/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0330 - accuracy: 0.8919
            Epoch 134/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 135/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0330 - accuracy: 0.8649
            Epoch 136/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0335 - accuracy: 0.8649
            Epoch 137/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0363 - accuracy: 0.8514
            Epoch 138/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0363 - accuracy: 0.8649
            Epoch 139/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0334 - accuracy: 0.8649
            Epoch 140/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0341 - accuracy: 0.8649
            Epoch 141/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0298 - accuracy: 0.8919
            Epoch 142/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0370 - accuracy: 0.8514
            Epoch 143/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0325 - accuracy: 0.8649
            Epoch 144/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0293 - accuracy: 0.8649
            Epoch 145/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0380 - accuracy: 0.8514
            Epoch 146/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0315 - accuracy: 0.8784
            Epoch 147/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0328 - accuracy: 0.8649
            Epoch 148/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 149/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0286 - accuracy: 0.8649
            Epoch 150/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0278 - accuracy: 0.8784
            Epoch 151/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0297 - accuracy: 0.8784
            Epoch 152/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0302 - accuracy: 0.9189
            Epoch 153/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 154/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0299 - accuracy: 0.8784
            Epoch 155/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 156/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0325 - accuracy: 0.8649
            Epoch 157/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 158/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0308 - accuracy: 0.8784
            Epoch 159/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0295 - accuracy: 0.8649
            Epoch 160/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0323 - accuracy: 0.8514
            Epoch 161/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0314 - accuracy: 0.8919
            Epoch 162/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0309 - accuracy: 0.8784
            Epoch 163/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0304 - accuracy: 0.9189
            Epoch 164/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0275 - accuracy: 0.8919
            Epoch 165/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0327 - accuracy: 0.8784
            Epoch 166/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 167/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.8919
            Epoch 168/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0341 - accuracy: 0.8649
            Epoch 169/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0316 - accuracy: 0.8649
            Epoch 170/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0270 - accuracy: 0.8649
            Epoch 171/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0300 - accuracy: 0.8649
            Epoch 172/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0298 - accuracy: 0.9054
            Epoch 173/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0270 - accuracy: 0.8919
            Epoch 174/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0293 - accuracy: 0.8649
            Epoch 175/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0337 - accuracy: 0.8649
            Epoch 176/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0313 - accuracy: 0.8784
            Epoch 177/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0327 - accuracy: 0.8784
            Epoch 178/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0380 - accuracy: 0.8649
            Epoch 179/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.8649
            Epoch 180/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0337 - accuracy: 0.8514
            Epoch 181/300
            74/74 [==============================] - 0s 137us/sample - loss: 0.0344 - accuracy: 0.8649
            Epoch 182/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0355 - accuracy: 0.8514
            Epoch 183/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0330 - accuracy: 0.8784
            Epoch 184/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0295 - accuracy: 0.8784
            Epoch 185/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0368 - accuracy: 0.8514
            Epoch 186/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0339 - accuracy: 0.8649
            Epoch 187/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0283 - accuracy: 0.8649
            Epoch 188/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0309 - accuracy: 0.8649
            Epoch 189/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0315 - accuracy: 0.8919
            Epoch 190/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0285 - accuracy: 0.8649
            Epoch 191/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0339 - accuracy: 0.8649
            Epoch 192/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0285 - accuracy: 0.8784
            Epoch 193/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0304 - accuracy: 0.8919
            Epoch 194/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0355 - accuracy: 0.8784
            Epoch 195/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0392 - accuracy: 0.8514
            Epoch 196/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0282 - accuracy: 0.8784
            Epoch 197/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 198/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 199/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0274 - accuracy: 0.8784
            Epoch 200/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0289 - accuracy: 0.8784
            Epoch 201/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0375 - accuracy: 0.8514
            Epoch 202/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0337 - accuracy: 0.8649
            Epoch 203/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 204/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0303 - accuracy: 0.8649
            Epoch 205/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0335 - accuracy: 0.8784
            Epoch 206/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0304 - accuracy: 0.8649
            Epoch 207/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0339 - accuracy: 0.8649
            Epoch 208/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0261 - accuracy: 0.8784
            Epoch 209/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.8649
            Epoch 210/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0303 - accuracy: 0.8649
            Epoch 211/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0318 - accuracy: 0.8784
            Epoch 212/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0358 - accuracy: 0.8919
            Epoch 213/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0272 - accuracy: 0.8784
            Epoch 214/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0293 - accuracy: 0.8649
            Epoch 215/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0347 - accuracy: 0.8649
            Epoch 216/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 217/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0331 - accuracy: 0.8784
            Epoch 218/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0283 - accuracy: 0.8784
            Epoch 219/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 220/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0291 - accuracy: 0.8919
            Epoch 221/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0323 - accuracy: 0.8784
            Epoch 222/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0341 - accuracy: 0.8784
            Epoch 223/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0310 - accuracy: 0.8919
            Epoch 224/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0337 - accuracy: 0.8784
            Epoch 225/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0359 - accuracy: 0.8649
            Epoch 226/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0355 - accuracy: 0.8649
            Epoch 227/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 228/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0353 - accuracy: 0.8649
            Epoch 229/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0323 - accuracy: 0.8784
            Epoch 230/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 231/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0350 - accuracy: 0.8649
            Epoch 232/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0279 - accuracy: 0.8919
            Epoch 233/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 234/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
            Epoch 235/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0327 - accuracy: 0.8649
            Epoch 236/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0316 - accuracy: 0.8649
            Epoch 237/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0292 - accuracy: 0.8919
            Epoch 238/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0320 - accuracy: 0.8919
            Epoch 239/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0312 - accuracy: 0.8649
            Epoch 240/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 241/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0296 - accuracy: 0.8649
            Epoch 242/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0331 - accuracy: 0.8649
            Epoch 243/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0258 - accuracy: 0.8784
            Epoch 244/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0316 - accuracy: 0.8919
            Epoch 245/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0321 - accuracy: 0.8784
            Epoch 246/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0306 - accuracy: 0.8649
            Epoch 247/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0319 - accuracy: 0.8649
            Epoch 248/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0275 - accuracy: 0.8784
            Epoch 249/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 250/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 251/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0311 - accuracy: 0.8919
            Epoch 252/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0335 - accuracy: 0.8649
            Epoch 253/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
            Epoch 254/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0359 - accuracy: 0.8514
            Epoch 255/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0326 - accuracy: 0.8784
            Epoch 256/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 257/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0343 - accuracy: 0.8784
            Epoch 258/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0309 - accuracy: 0.8649
            Epoch 259/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0301 - accuracy: 0.8649
            Epoch 260/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0315 - accuracy: 0.8649
            Epoch 261/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0342 - accuracy: 0.8649
            Epoch 262/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0300 - accuracy: 0.8649
            Epoch 263/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0358 - accuracy: 0.8649
            Epoch 264/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0295 - accuracy: 0.8649
            Epoch 265/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0356 - accuracy: 0.8649
            Epoch 266/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 267/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0298 - accuracy: 0.8784
            Epoch 268/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0278 - accuracy: 0.8649
            Epoch 269/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 270/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8649
            Epoch 271/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 272/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0322 - accuracy: 0.8784
            Epoch 273/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 274/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0309 - accuracy: 0.8649
            Epoch 275/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0296 - accuracy: 0.8649
            Epoch 276/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0285 - accuracy: 0.8649
            Epoch 277/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 278/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8514
            Epoch 279/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0347 - accuracy: 0.8649
            Epoch 280/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0320 - accuracy: 0.8649
            Epoch 281/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0350 - accuracy: 0.8784
            Epoch 282/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0320 - accuracy: 0.8649
            Epoch 283/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0331 - accuracy: 0.8649
            Epoch 284/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0283 - accuracy: 0.8649
            Epoch 285/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 286/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0306 - accuracy: 0.8649
            Epoch 287/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0306 - accuracy: 0.8784
            Epoch 288/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 289/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0347 - accuracy: 0.8514
            Epoch 290/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0362 - accuracy: 0.8514
            Epoch 291/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0330 - accuracy: 0.8649
            Epoch 292/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0306 - accuracy: 0.8649
            Epoch 293/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0326 - accuracy: 0.8649
            Epoch 294/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0346 - accuracy: 0.8649
            Epoch 295/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0335 - accuracy: 0.8649
            Epoch 296/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0304 - accuracy: 0.8649
            Epoch 297/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0303 - accuracy: 0.8784
            Epoch 298/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 299/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 300/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0297 - accuracy: 0.8649
            Model: "sequential_11"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            dense_32 (Dense)             (None, 128)               4608      
            _________________________________________________________________
            activation_32 (Activation)   (None, 128)               0         
            _________________________________________________________________
            dropout_21 (Dropout)         (None, 128)               0         
            _________________________________________________________________
            dense_33 (Dense)             (None, 1)                 129       
            _________________________________________________________________
            activation_33 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 4,737
            Trainable params: 4,737
            Non-trainable params: 0
            _________________________________________________________________
            WARNING:tensorflow:sample_weight modes were coerced from
              ...
                to  
              ['...']
            Train on 74 samples
            Epoch 1/300
            74/74 [==============================] - 0s 6ms/sample - loss: 0.1394 - accuracy: 0.6757
            Epoch 2/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.1322 - accuracy: 0.7568
            Epoch 3/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.1254 - accuracy: 0.7973
            Epoch 4/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.1130 - accuracy: 0.7973
            Epoch 5/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.1276 - accuracy: 0.7568
            Epoch 6/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.1141 - accuracy: 0.9054
            Epoch 7/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.1047 - accuracy: 0.8514
            Epoch 8/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.1044 - accuracy: 0.8784
            Epoch 9/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.1066 - accuracy: 0.8919
            Epoch 10/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0914 - accuracy: 0.8919
            Epoch 11/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0893 - accuracy: 0.9054
            Epoch 12/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0854 - accuracy: 0.9054
            Epoch 13/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0835 - accuracy: 0.8919
            Epoch 14/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0761 - accuracy: 0.9054
            Epoch 15/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0776 - accuracy: 0.9189
            Epoch 16/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0744 - accuracy: 0.9189
            Epoch 17/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0717 - accuracy: 0.9189
            Epoch 18/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0722 - accuracy: 0.9054
            Epoch 19/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0662 - accuracy: 0.8919
            Epoch 20/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0679 - accuracy: 0.9189
            Epoch 21/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0633 - accuracy: 0.9189
            Epoch 22/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0597 - accuracy: 0.9189
            Epoch 23/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0615 - accuracy: 0.8919
            Epoch 24/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0586 - accuracy: 0.9189
            Epoch 25/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0625 - accuracy: 0.9054
            Epoch 26/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0528 - accuracy: 0.9189
            Epoch 27/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0592 - accuracy: 0.9054
            Epoch 28/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0547 - accuracy: 0.9189
            Epoch 29/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0532 - accuracy: 0.9054
            Epoch 30/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0529 - accuracy: 0.9189
            Epoch 31/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0491 - accuracy: 0.9189
            Epoch 32/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0557 - accuracy: 0.9189
            Epoch 33/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0480 - accuracy: 0.9189
            Epoch 34/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0480 - accuracy: 0.9189
            Epoch 35/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0449 - accuracy: 0.9189
            Epoch 36/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0452 - accuracy: 0.9189
            Epoch 37/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0472 - accuracy: 0.9189
            Epoch 38/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0494 - accuracy: 0.9189
            Epoch 39/300
            74/74 [==============================] - 0s 171us/sample - loss: 0.0431 - accuracy: 0.9189
            Epoch 40/300
            74/74 [==============================] - 0s 157us/sample - loss: 0.0429 - accuracy: 0.9189
            Epoch 41/300
            74/74 [==============================] - 0s 151us/sample - loss: 0.0438 - accuracy: 0.9189
            Epoch 42/300
            74/74 [==============================] - 0s 177us/sample - loss: 0.0412 - accuracy: 0.9189
            Epoch 43/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0427 - accuracy: 0.9189
            Epoch 44/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0416 - accuracy: 0.9054
            Epoch 45/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0382 - accuracy: 0.9189
            Epoch 46/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0392 - accuracy: 0.9189
            Epoch 47/300
            74/74 [==============================] - 0s 106us/sample - loss: 0.0406 - accuracy: 0.9189
            Epoch 48/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0368 - accuracy: 0.9189
            Epoch 49/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0412 - accuracy: 0.9189
            Epoch 50/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0352 - accuracy: 0.9189
            Epoch 51/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0420 - accuracy: 0.9189
            Epoch 52/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0377 - accuracy: 0.9189
            Epoch 53/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0392 - accuracy: 0.9189
            Epoch 54/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0380 - accuracy: 0.9189
            Epoch 55/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0352 - accuracy: 0.9189
            Epoch 56/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0348 - accuracy: 0.9189
            Epoch 57/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0365 - accuracy: 0.9189
            Epoch 58/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0319 - accuracy: 0.9189
            Epoch 59/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0350 - accuracy: 0.9054
            Epoch 60/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0373 - accuracy: 0.9189
            Epoch 61/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0382 - accuracy: 0.9189
            Epoch 62/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0346 - accuracy: 0.9189
            Epoch 63/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0312 - accuracy: 0.9189
            Epoch 64/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0349 - accuracy: 0.9189
            Epoch 65/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0345 - accuracy: 0.9189
            Epoch 66/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0312 - accuracy: 0.9189
            Epoch 67/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0322 - accuracy: 0.9189
            Epoch 68/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0307 - accuracy: 0.9189
            Epoch 69/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0308 - accuracy: 0.9189
            Epoch 70/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0368 - accuracy: 0.9189
            Epoch 71/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0312 - accuracy: 0.9189
            Epoch 72/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0337 - accuracy: 0.9189
            Epoch 73/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0319 - accuracy: 0.9189
            Epoch 74/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0344 - accuracy: 0.9189
            Epoch 75/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0338 - accuracy: 0.9189
            Epoch 76/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0303 - accuracy: 0.9189
            Epoch 77/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0303 - accuracy: 0.9189
            Epoch 78/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
            Epoch 79/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0301 - accuracy: 0.9189
            Epoch 80/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0333 - accuracy: 0.9189
            Epoch 81/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0294 - accuracy: 0.9189
            Epoch 82/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0271 - accuracy: 0.9189
            Epoch 83/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0327 - accuracy: 0.9189
            Epoch 84/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0297 - accuracy: 0.9189
            Epoch 85/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0309 - accuracy: 0.9189
            Epoch 86/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0331 - accuracy: 0.9189
            Epoch 87/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0327 - accuracy: 0.9189
            Epoch 88/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.9189
            Epoch 89/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0275 - accuracy: 0.9189
            Epoch 90/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.9189
            Epoch 91/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0293 - accuracy: 0.9189
            Epoch 92/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0331 - accuracy: 0.9189
            Epoch 93/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0298 - accuracy: 0.9189
            Epoch 94/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0311 - accuracy: 0.9189
            Epoch 95/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0310 - accuracy: 0.9189
            Epoch 96/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0309 - accuracy: 0.9189
            Epoch 97/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0292 - accuracy: 0.9189
            Epoch 98/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.9189
            Epoch 99/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0261 - accuracy: 0.9189
            Epoch 100/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 101/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0282 - accuracy: 0.9189
            Epoch 102/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0355 - accuracy: 0.9189
            Epoch 103/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0281 - accuracy: 0.9189
            Epoch 104/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0286 - accuracy: 0.9189
            Epoch 105/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0310 - accuracy: 0.9189
            Epoch 106/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0269 - accuracy: 0.9189
            Epoch 107/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0344 - accuracy: 0.9189
            Epoch 108/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0323 - accuracy: 0.9189
            Epoch 109/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0309 - accuracy: 0.9189
            Epoch 110/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0258 - accuracy: 0.9189
            Epoch 111/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 112/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0274 - accuracy: 0.9189
            Epoch 113/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 114/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 115/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0274 - accuracy: 0.9189
            Epoch 116/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0311 - accuracy: 0.9189
            Epoch 117/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0318 - accuracy: 0.9189
            Epoch 118/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0265 - accuracy: 0.9189
            Epoch 119/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 120/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0258 - accuracy: 0.9189
            Epoch 121/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0269 - accuracy: 0.9189
            Epoch 122/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0323 - accuracy: 0.9189
            Epoch 123/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0291 - accuracy: 0.9189
            Epoch 124/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0292 - accuracy: 0.9189
            Epoch 125/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0258 - accuracy: 0.9189
            Epoch 126/300
            74/74 [==============================] - 0s 103us/sample - loss: 0.0257 - accuracy: 0.9189
            Epoch 127/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0321 - accuracy: 0.9189
            Epoch 128/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0274 - accuracy: 0.9189
            Epoch 129/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0284 - accuracy: 0.9189
            Epoch 130/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0285 - accuracy: 0.9189
            Epoch 131/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0272 - accuracy: 0.9189
            Epoch 132/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0295 - accuracy: 0.9189
            Epoch 133/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0273 - accuracy: 0.9189
            Epoch 134/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0293 - accuracy: 0.9189
            Epoch 135/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.9189
            Epoch 136/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0271 - accuracy: 0.9189
            Epoch 137/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0292 - accuracy: 0.9189
            Epoch 138/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0285 - accuracy: 0.9189
            Epoch 139/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0299 - accuracy: 0.9189
            Epoch 140/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0308 - accuracy: 0.9189
            Epoch 141/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0256 - accuracy: 0.9189
            Epoch 142/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 143/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0256 - accuracy: 0.9189
            Epoch 144/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0294 - accuracy: 0.9189
            Epoch 145/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0275 - accuracy: 0.9189
            Epoch 146/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0321 - accuracy: 0.9189
            Epoch 147/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0258 - accuracy: 0.9189
            Epoch 148/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0271 - accuracy: 0.9189
            Epoch 149/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0286 - accuracy: 0.9189
            Epoch 150/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0337 - accuracy: 0.9189
            Epoch 151/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0277 - accuracy: 0.9189
            Epoch 152/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0290 - accuracy: 0.9189
            Epoch 153/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 154/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0257 - accuracy: 0.9189
            Epoch 155/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0263 - accuracy: 0.9189
            Epoch 156/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0299 - accuracy: 0.9189
            Epoch 157/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 158/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0325 - accuracy: 0.9189
            Epoch 159/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0247 - accuracy: 0.9189
            Epoch 160/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 161/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0252 - accuracy: 0.9189
            Epoch 162/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0282 - accuracy: 0.9189
            Epoch 163/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0255 - accuracy: 0.9189
            Epoch 164/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0265 - accuracy: 0.9189
            Epoch 165/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
            Epoch 166/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0300 - accuracy: 0.9189
            Epoch 167/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 168/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0321 - accuracy: 0.9189
            Epoch 169/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0246 - accuracy: 0.9189
            Epoch 170/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0230 - accuracy: 0.9189
            Epoch 171/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 172/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0263 - accuracy: 0.9189
            Epoch 173/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 174/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0262 - accuracy: 0.9189
            Epoch 175/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0276 - accuracy: 0.9189
            Epoch 176/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0254 - accuracy: 0.9189
            Epoch 177/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0311 - accuracy: 0.9189
            Epoch 178/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0311 - accuracy: 0.9189
            Epoch 179/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0278 - accuracy: 0.9189
            Epoch 180/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0313 - accuracy: 0.9189
            Epoch 181/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0291 - accuracy: 0.9189
            Epoch 182/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0277 - accuracy: 0.9189
            Epoch 183/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0276 - accuracy: 0.9189
            Epoch 184/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0247 - accuracy: 0.9189
            Epoch 185/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0314 - accuracy: 0.9189
            Epoch 186/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0270 - accuracy: 0.9189
            Epoch 187/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0306 - accuracy: 0.9189
            Epoch 188/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0250 - accuracy: 0.9189
            Epoch 189/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0280 - accuracy: 0.9189
            Epoch 190/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0304 - accuracy: 0.9189
            Epoch 191/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0286 - accuracy: 0.9189
            Epoch 192/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0278 - accuracy: 0.9189
            Epoch 193/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0225 - accuracy: 0.9189
            Epoch 194/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0266 - accuracy: 0.9189
            Epoch 195/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0260 - accuracy: 0.9189
            Epoch 196/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0254 - accuracy: 0.9189
            Epoch 197/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 198/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0248 - accuracy: 0.9189
            Epoch 199/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0285 - accuracy: 0.9189
            Epoch 200/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0237 - accuracy: 0.9189
            Epoch 201/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0291 - accuracy: 0.9189
            Epoch 202/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0290 - accuracy: 0.9189
            Epoch 203/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0292 - accuracy: 0.9189
            Epoch 204/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0307 - accuracy: 0.9189
            Epoch 205/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0264 - accuracy: 0.9189
            Epoch 206/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0288 - accuracy: 0.9189
            Epoch 207/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 208/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0252 - accuracy: 0.9189
            Epoch 209/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0273 - accuracy: 0.9189
            Epoch 210/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 211/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 212/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0253 - accuracy: 0.9189
            Epoch 213/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0244 - accuracy: 0.9189
            Epoch 214/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0276 - accuracy: 0.9189
            Epoch 215/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0281 - accuracy: 0.9189
            Epoch 216/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0260 - accuracy: 0.9189
            Epoch 217/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0265 - accuracy: 0.9189
            Epoch 218/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0301 - accuracy: 0.9189
            Epoch 219/300
            74/74 [==============================] - 0s 143us/sample - loss: 0.0279 - accuracy: 0.9189
            Epoch 220/300
            74/74 [==============================] - 0s 144us/sample - loss: 0.0254 - accuracy: 0.9189
            Epoch 221/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 222/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0238 - accuracy: 0.9189
            Epoch 223/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0303 - accuracy: 0.9189
            Epoch 224/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0244 - accuracy: 0.9189
            Epoch 225/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0270 - accuracy: 0.9189
            Epoch 226/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0297 - accuracy: 0.9189
            Epoch 227/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0266 - accuracy: 0.9189
            Epoch 228/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0265 - accuracy: 0.9189
            Epoch 229/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0240 - accuracy: 0.9189
            Epoch 230/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 231/300
            74/74 [==============================] - 0s 141us/sample - loss: 0.0309 - accuracy: 0.9189
            Epoch 232/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0305 - accuracy: 0.9189
            Epoch 233/300
            74/74 [==============================] - 0s 143us/sample - loss: 0.0279 - accuracy: 0.9189
            Epoch 234/300
            74/74 [==============================] - 0s 149us/sample - loss: 0.0267 - accuracy: 0.9189
            Epoch 235/300
            74/74 [==============================] - 0s 140us/sample - loss: 0.0281 - accuracy: 0.9189
            Epoch 236/300
            74/74 [==============================] - 0s 145us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 237/300
            74/74 [==============================] - 0s 160us/sample - loss: 0.0263 - accuracy: 0.9189
            Epoch 238/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0286 - accuracy: 0.9189
            Epoch 239/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0279 - accuracy: 0.9189
            Epoch 240/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.0254 - accuracy: 0.9189
            Epoch 241/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0297 - accuracy: 0.9189
            Epoch 242/300
            74/74 [==============================] - 0s 146us/sample - loss: 0.0276 - accuracy: 0.9189
            Epoch 243/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0280 - accuracy: 0.9189
            Epoch 244/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0280 - accuracy: 0.9189
            Epoch 245/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0295 - accuracy: 0.9189
            Epoch 246/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
            Epoch 247/300
            74/74 [==============================] - 0s 133us/sample - loss: 0.0298 - accuracy: 0.9189
            Epoch 248/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0273 - accuracy: 0.9189
            Epoch 249/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 250/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0232 - accuracy: 0.9189
            Epoch 251/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0288 - accuracy: 0.9189
            Epoch 252/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0255 - accuracy: 0.9189
            Epoch 253/300
            74/74 [==============================] - 0s 146us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 254/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0249 - accuracy: 0.9189
            Epoch 255/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0269 - accuracy: 0.9189
            Epoch 256/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 257/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0259 - accuracy: 0.9189
            Epoch 258/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0247 - accuracy: 0.9189
            Epoch 259/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0288 - accuracy: 0.9189
            Epoch 260/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0272 - accuracy: 0.9189
            Epoch 261/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0262 - accuracy: 0.9189
            Epoch 262/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0285 - accuracy: 0.9189
            Epoch 263/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0269 - accuracy: 0.9189
            Epoch 264/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0289 - accuracy: 0.9189
            Epoch 265/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0248 - accuracy: 0.9189
            Epoch 266/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0243 - accuracy: 0.9189
            Epoch 267/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0282 - accuracy: 0.9189
            Epoch 268/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0269 - accuracy: 0.9189
            Epoch 269/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0268 - accuracy: 0.9189
            Epoch 270/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0272 - accuracy: 0.9189
            Epoch 271/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0258 - accuracy: 0.9189
            Epoch 272/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0255 - accuracy: 0.9189
            Epoch 273/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0279 - accuracy: 0.9189
            Epoch 274/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0262 - accuracy: 0.9189
            Epoch 275/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0281 - accuracy: 0.9189
            Epoch 276/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0247 - accuracy: 0.9189
            Epoch 277/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0245 - accuracy: 0.9189
            Epoch 278/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0279 - accuracy: 0.9189
            Epoch 279/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0309 - accuracy: 0.9189
            Epoch 280/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0240 - accuracy: 0.9189
            Epoch 281/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0265 - accuracy: 0.9189
            Epoch 282/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0267 - accuracy: 0.9189
            Epoch 283/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0292 - accuracy: 0.9189
            Epoch 284/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0270 - accuracy: 0.9189
            Epoch 285/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0267 - accuracy: 0.9189
            Epoch 286/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0299 - accuracy: 0.9189
            Epoch 287/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0283 - accuracy: 0.9189
            Epoch 288/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0248 - accuracy: 0.9189
            Epoch 289/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0257 - accuracy: 0.9189
            Epoch 290/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0257 - accuracy: 0.9189
            Epoch 291/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0272 - accuracy: 0.9189
            Epoch 292/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0301 - accuracy: 0.9189
            Epoch 293/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0321 - accuracy: 0.9189
            Epoch 294/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0241 - accuracy: 0.9189
            Epoch 295/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0277 - accuracy: 0.9189
            Epoch 296/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0254 - accuracy: 0.9189
            Epoch 297/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0263 - accuracy: 0.9189
            Epoch 298/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0276 - accuracy: 0.9189
            Epoch 299/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0225 - accuracy: 0.9189
            Epoch 300/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0309 - accuracy: 0.9189
            Model: "sequential_12"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            dense_34 (Dense)             (None, 128)               4608      
            _________________________________________________________________
            activation_34 (Activation)   (None, 128)               0         
            _________________________________________________________________
            dropout_22 (Dropout)         (None, 128)               0         
            _________________________________________________________________
            dense_35 (Dense)             (None, 1)                 129       
            _________________________________________________________________
            activation_35 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 4,737
            Trainable params: 4,737
            Non-trainable params: 0
            _________________________________________________________________
            WARNING:tensorflow:sample_weight modes were coerced from
              ...
                to  
              ['...']
            Train on 74 samples
            Epoch 1/300
            74/74 [==============================] - 0s 6ms/sample - loss: 0.1366 - accuracy: 0.6081
            Epoch 2/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.1310 - accuracy: 0.7027
            Epoch 3/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.1200 - accuracy: 0.7027
            Epoch 4/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.1165 - accuracy: 0.7568
            Epoch 5/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.1130 - accuracy: 0.7973
            Epoch 6/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.1052 - accuracy: 0.7973
            Epoch 7/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.1005 - accuracy: 0.8649
            Epoch 8/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0983 - accuracy: 0.7973
            Epoch 9/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0957 - accuracy: 0.7838
            Epoch 10/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0917 - accuracy: 0.8514
            Epoch 11/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0894 - accuracy: 0.8243
            Epoch 12/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0860 - accuracy: 0.8514
            Epoch 13/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0821 - accuracy: 0.8243
            Epoch 14/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0786 - accuracy: 0.8378
            Epoch 15/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0756 - accuracy: 0.8514
            Epoch 16/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0779 - accuracy: 0.8784
            Epoch 17/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0761 - accuracy: 0.8514
            Epoch 18/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0713 - accuracy: 0.8378
            Epoch 19/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0686 - accuracy: 0.8649
            Epoch 20/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0678 - accuracy: 0.8649
            Epoch 21/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0627 - accuracy: 0.8784
            Epoch 22/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0680 - accuracy: 0.8649
            Epoch 23/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0629 - accuracy: 0.8514
            Epoch 24/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0601 - accuracy: 0.8649
            Epoch 25/300
            74/74 [==============================] - 0s 132us/sample - loss: 0.0617 - accuracy: 0.8514
            Epoch 26/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0586 - accuracy: 0.8649
            Epoch 27/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0536 - accuracy: 0.8784
            Epoch 28/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0583 - accuracy: 0.8649
            Epoch 29/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0503 - accuracy: 0.8784
            Epoch 30/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0528 - accuracy: 0.8784
            Epoch 31/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0542 - accuracy: 0.8514
            Epoch 32/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0519 - accuracy: 0.8649
            Epoch 33/300
            74/74 [==============================] - 0s 105us/sample - loss: 0.0576 - accuracy: 0.8514
            Epoch 34/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0538 - accuracy: 0.8649
            Epoch 35/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0475 - accuracy: 0.8649
            Epoch 36/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0530 - accuracy: 0.8514
            Epoch 37/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0467 - accuracy: 0.8784
            Epoch 38/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0480 - accuracy: 0.8649
            Epoch 39/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0444 - accuracy: 0.8784
            Epoch 40/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0432 - accuracy: 0.8784
            Epoch 41/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0445 - accuracy: 0.8649
            Epoch 42/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0530 - accuracy: 0.8514
            Epoch 43/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0483 - accuracy: 0.8649
            Epoch 44/300
            74/74 [==============================] - 0s 151us/sample - loss: 0.0430 - accuracy: 0.8919
            Epoch 45/300
            74/74 [==============================] - 0s 159us/sample - loss: 0.0415 - accuracy: 0.8649
            Epoch 46/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0478 - accuracy: 0.8514
            Epoch 47/300
            74/74 [==============================] - 0s 138us/sample - loss: 0.0407 - accuracy: 0.8649
            Epoch 48/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0394 - accuracy: 0.8649
            Epoch 49/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0384 - accuracy: 0.8649
            Epoch 50/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0406 - accuracy: 0.8649
            Epoch 51/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0440 - accuracy: 0.8649
            Epoch 52/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0469 - accuracy: 0.8649
            Epoch 53/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0407 - accuracy: 0.8649
            Epoch 54/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0403 - accuracy: 0.8784
            Epoch 55/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0400 - accuracy: 0.8649
            Epoch 56/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0371 - accuracy: 0.8784
            Epoch 57/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0431 - accuracy: 0.8784
            Epoch 58/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0351 - accuracy: 0.8649
            Epoch 59/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0371 - accuracy: 0.8649
            Epoch 60/300
            74/74 [==============================] - 0s 136us/sample - loss: 0.0380 - accuracy: 0.8784
            Epoch 61/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0354 - accuracy: 0.8919
            Epoch 62/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0371 - accuracy: 0.8649
            Epoch 63/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0360 - accuracy: 0.8784
            Epoch 64/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0401 - accuracy: 0.8649
            Epoch 65/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0412 - accuracy: 0.8649
            Epoch 66/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0402 - accuracy: 0.8649
            Epoch 67/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0416 - accuracy: 0.8649
            Epoch 68/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0368 - accuracy: 0.8649
            Epoch 69/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0395 - accuracy: 0.8649
            Epoch 70/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0357 - accuracy: 0.8649
            Epoch 71/300
            74/74 [==============================] - 0s 135us/sample - loss: 0.0365 - accuracy: 0.8649
            Epoch 72/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0360 - accuracy: 0.8784
            Epoch 73/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0360 - accuracy: 0.8649
            Epoch 74/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0324 - accuracy: 0.8649
            Epoch 75/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0328 - accuracy: 0.8649
            Epoch 76/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0390 - accuracy: 0.8784
            Epoch 77/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0297 - accuracy: 0.8919
            Epoch 78/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0415 - accuracy: 0.8649
            Epoch 79/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.0354 - accuracy: 0.8784
            Epoch 80/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0345 - accuracy: 0.8784
            Epoch 81/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0377 - accuracy: 0.8784
            Epoch 82/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0308 - accuracy: 0.8649
            Epoch 83/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0358 - accuracy: 0.8784
            Epoch 84/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
            Epoch 85/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0348 - accuracy: 0.8514
            Epoch 86/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0329 - accuracy: 0.8784
            Epoch 87/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0290 - accuracy: 0.8919
            Epoch 88/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 89/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0373 - accuracy: 0.8514
            Epoch 90/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0381 - accuracy: 0.8649
            Epoch 91/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0346 - accuracy: 0.8649
            Epoch 92/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0322 - accuracy: 0.8649
            Epoch 93/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8919
            Epoch 94/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0336 - accuracy: 0.8649
            Epoch 95/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0360 - accuracy: 0.8784
            Epoch 96/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0322 - accuracy: 0.8784
            Epoch 97/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0354 - accuracy: 0.8784
            Epoch 98/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0312 - accuracy: 0.8919
            Epoch 99/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0387 - accuracy: 0.8649
            Epoch 100/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0311 - accuracy: 0.8784
            Epoch 101/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0271 - accuracy: 0.8919
            Epoch 102/300
            74/74 [==============================] - 0s 130us/sample - loss: 0.0351 - accuracy: 0.8784
            Epoch 103/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0384 - accuracy: 0.8919
            Epoch 104/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 105/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0350 - accuracy: 0.8649
            Epoch 106/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0337 - accuracy: 0.9054
            Epoch 107/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0355 - accuracy: 0.8649
            Epoch 108/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0310 - accuracy: 0.8784
            Epoch 109/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0339 - accuracy: 0.8649
            Epoch 110/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0336 - accuracy: 0.8784
            Epoch 111/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0296 - accuracy: 0.8649
            Epoch 112/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0323 - accuracy: 0.8919
            Epoch 113/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.8784
            Epoch 114/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0350 - accuracy: 0.8649
            Epoch 115/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0325 - accuracy: 0.8649
            Epoch 116/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 117/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0316 - accuracy: 0.8784
            Epoch 118/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0305 - accuracy: 0.9054
            Epoch 119/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0377 - accuracy: 0.8784
            Epoch 120/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0328 - accuracy: 0.8919
            Epoch 121/300
            74/74 [==============================] - 0s 134us/sample - loss: 0.0345 - accuracy: 0.8649
            Epoch 122/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0392 - accuracy: 0.8649
            Epoch 123/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0340 - accuracy: 0.8784
            Epoch 124/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0294 - accuracy: 0.8919
            Epoch 125/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0351 - accuracy: 0.8649
            Epoch 126/300
            74/74 [==============================] - 0s 128us/sample - loss: 0.0322 - accuracy: 0.8649
            Epoch 127/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0325 - accuracy: 0.8649
            Epoch 128/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0371 - accuracy: 0.8514
            Epoch 129/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0303 - accuracy: 0.8784
            Epoch 130/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0398 - accuracy: 0.8514
            Epoch 131/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0323 - accuracy: 0.8784
            Epoch 132/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0292 - accuracy: 0.8784
            Epoch 133/300
            74/74 [==============================] - 0s 123us/sample - loss: 0.0293 - accuracy: 0.9054
            Epoch 134/300
            74/74 [==============================] - 0s 106us/sample - loss: 0.0304 - accuracy: 0.8784
            Epoch 135/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0292 - accuracy: 0.8919
            Epoch 136/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0385 - accuracy: 0.8514
            Epoch 137/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0302 - accuracy: 0.8784
            Epoch 138/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0291 - accuracy: 0.8784
            Epoch 139/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0323 - accuracy: 0.8919
            Epoch 140/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.0307 - accuracy: 0.8784
            Epoch 141/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0298 - accuracy: 0.8784
            Epoch 142/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0295 - accuracy: 0.8784
            Epoch 143/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0334 - accuracy: 0.8649
            Epoch 144/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0319 - accuracy: 0.8649
            Epoch 145/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0347 - accuracy: 0.8649
            Epoch 146/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0310 - accuracy: 0.8649
            Epoch 147/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0340 - accuracy: 0.8649
            Epoch 148/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8784
            Epoch 149/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0291 - accuracy: 0.8784
            Epoch 150/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0288 - accuracy: 0.8649
            Epoch 151/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0370 - accuracy: 0.8784
            Epoch 152/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0298 - accuracy: 0.8784
            Epoch 153/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0328 - accuracy: 0.8784
            Epoch 154/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0327 - accuracy: 0.8649
            Epoch 155/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0340 - accuracy: 0.8514
            Epoch 156/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0276 - accuracy: 0.8649
            Epoch 157/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0308 - accuracy: 0.8649
            Epoch 158/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0373 - accuracy: 0.8649
            Epoch 159/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0297 - accuracy: 0.8649
            Epoch 160/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0347 - accuracy: 0.8784
            Epoch 161/300
            74/74 [==============================] - 0s 142us/sample - loss: 0.0319 - accuracy: 0.8784
            Epoch 162/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0301 - accuracy: 0.8649
            Epoch 163/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0305 - accuracy: 0.8919
            Epoch 164/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 165/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0336 - accuracy: 0.8649
            Epoch 166/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0331 - accuracy: 0.8649
            Epoch 167/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0319 - accuracy: 0.8784
            Epoch 168/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0318 - accuracy: 0.8919
            Epoch 169/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0302 - accuracy: 0.8784
            Epoch 170/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0327 - accuracy: 0.8649
            Epoch 171/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0303 - accuracy: 0.8784
            Epoch 172/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0315 - accuracy: 0.8919
            Epoch 173/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0319 - accuracy: 0.8649
            Epoch 174/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0285 - accuracy: 0.8649
            Epoch 175/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0320 - accuracy: 0.8919
            Epoch 176/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 177/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0338 - accuracy: 0.8919
            Epoch 178/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0333 - accuracy: 0.8784
            Epoch 179/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0242 - accuracy: 0.9054
            Epoch 180/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0379 - accuracy: 0.8649
            Epoch 181/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0308 - accuracy: 0.8919
            Epoch 182/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0340 - accuracy: 0.8784
            Epoch 183/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0352 - accuracy: 0.8784
            Epoch 184/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0267 - accuracy: 0.9054
            Epoch 185/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0274 - accuracy: 0.8784
            Epoch 186/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0342 - accuracy: 0.8784
            Epoch 187/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0351 - accuracy: 0.8649
            Epoch 188/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0363 - accuracy: 0.8649
            Epoch 189/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0295 - accuracy: 0.8784
            Epoch 190/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 191/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0307 - accuracy: 0.8784
            Epoch 192/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0287 - accuracy: 0.8784
            Epoch 193/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0304 - accuracy: 0.8919
            Epoch 194/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0301 - accuracy: 0.8649
            Epoch 195/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0309 - accuracy: 0.8784
            Epoch 196/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0355 - accuracy: 0.8514
            Epoch 197/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 198/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0389 - accuracy: 0.8514
            Epoch 199/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0331 - accuracy: 0.8649
            Epoch 200/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0315 - accuracy: 0.8919
            Epoch 201/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8784
            Epoch 202/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0384 - accuracy: 0.8649
            Epoch 203/300
            74/74 [==============================] - 0s 104us/sample - loss: 0.0288 - accuracy: 0.8649
            Epoch 204/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0279 - accuracy: 0.8919
            Epoch 205/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0381 - accuracy: 0.8514
            Epoch 206/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0280 - accuracy: 0.8784
            Epoch 207/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0319 - accuracy: 0.8514
            Epoch 208/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0324 - accuracy: 0.8919
            Epoch 209/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0294 - accuracy: 0.8784
            Epoch 210/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 211/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 212/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0298 - accuracy: 0.8784
            Epoch 213/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0333 - accuracy: 0.8514
            Epoch 214/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 215/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0306 - accuracy: 0.8919
            Epoch 216/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0307 - accuracy: 0.8649
            Epoch 217/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 218/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0337 - accuracy: 0.8649
            Epoch 219/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0311 - accuracy: 0.8649
            Epoch 220/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0345 - accuracy: 0.8649
            Epoch 221/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0351 - accuracy: 0.8649
            Epoch 222/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0289 - accuracy: 0.8784
            Epoch 223/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0295 - accuracy: 0.8649
            Epoch 224/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0302 - accuracy: 0.8649
            Epoch 225/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0366 - accuracy: 0.8514
            Epoch 226/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0282 - accuracy: 0.8649
            Epoch 227/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 228/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0319 - accuracy: 0.8784
            Epoch 229/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 230/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0320 - accuracy: 0.8649
            Epoch 231/300
            74/74 [==============================] - 0s 125us/sample - loss: 0.0369 - accuracy: 0.8649
            Epoch 232/300
            74/74 [==============================] - 0s 104us/sample - loss: 0.0306 - accuracy: 0.8649
            Epoch 233/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0324 - accuracy: 0.8784
            Epoch 234/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0245 - accuracy: 0.8919
            Epoch 235/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0406 - accuracy: 0.8514
            Epoch 236/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0310 - accuracy: 0.8649
            Epoch 237/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0309 - accuracy: 0.8649
            Epoch 238/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0309 - accuracy: 0.8784
            Epoch 239/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0293 - accuracy: 0.8649
            Epoch 240/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0354 - accuracy: 0.8649
            Epoch 241/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8784
            Epoch 242/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0329 - accuracy: 0.8649
            Epoch 243/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0321 - accuracy: 0.8649
            Epoch 244/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0279 - accuracy: 0.8649
            Epoch 245/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0312 - accuracy: 0.8649
            Epoch 246/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0355 - accuracy: 0.8649
            Epoch 247/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0292 - accuracy: 0.8649
            Epoch 248/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8649
            Epoch 249/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0272 - accuracy: 0.9054
            Epoch 250/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0301 - accuracy: 0.8649
            Epoch 251/300
            74/74 [==============================] - 0s 119us/sample - loss: 0.0294 - accuracy: 0.8784
            Epoch 252/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0270 - accuracy: 0.8919
            Epoch 253/300
            74/74 [==============================] - 0s 117us/sample - loss: 0.0326 - accuracy: 0.8649
            Epoch 254/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0338 - accuracy: 0.8649
            Epoch 255/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.8784
            Epoch 256/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0312 - accuracy: 0.8784
            Epoch 257/300
            74/74 [==============================] - 0s 124us/sample - loss: 0.0346 - accuracy: 0.8514
            Epoch 258/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 259/300
            74/74 [==============================] - 0s 107us/sample - loss: 0.0308 - accuracy: 0.8649
            Epoch 260/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0315 - accuracy: 0.8649
            Epoch 261/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0296 - accuracy: 0.8649
            Epoch 262/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0304 - accuracy: 0.8784
            Epoch 263/300
            74/74 [==============================] - 0s 110us/sample - loss: 0.0290 - accuracy: 0.8649
            Epoch 264/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0315 - accuracy: 0.8784
            Epoch 265/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0350 - accuracy: 0.8649
            Epoch 266/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0328 - accuracy: 0.8649
            Epoch 267/300
            74/74 [==============================] - 0s 127us/sample - loss: 0.0289 - accuracy: 0.8784
            Epoch 268/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0344 - accuracy: 0.8784
            Epoch 269/300
            74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
            Epoch 270/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0305 - accuracy: 0.8649
            Epoch 271/300
            74/74 [==============================] - 0s 173us/sample - loss: 0.0291 - accuracy: 0.8649
            Epoch 272/300
            74/74 [==============================] - 0s 153us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 273/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0316 - accuracy: 0.8649
            Epoch 274/300
            74/74 [==============================] - 0s 122us/sample - loss: 0.0281 - accuracy: 0.8649
            Epoch 275/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0291 - accuracy: 0.8649
            Epoch 276/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8649
            Epoch 277/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0309 - accuracy: 0.8919
            Epoch 278/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0338 - accuracy: 0.8649
            Epoch 279/300
            74/74 [==============================] - 0s 129us/sample - loss: 0.0329 - accuracy: 0.8784
            Epoch 280/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0331 - accuracy: 0.8919
            Epoch 281/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 282/300
            74/74 [==============================] - 0s 112us/sample - loss: 0.0272 - accuracy: 0.8784
            Epoch 283/300
            74/74 [==============================] - 0s 113us/sample - loss: 0.0310 - accuracy: 0.8784
            Epoch 284/300
            74/74 [==============================] - 0s 116us/sample - loss: 0.0309 - accuracy: 0.8784
            Epoch 285/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0332 - accuracy: 0.8649
            Epoch 286/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0340 - accuracy: 0.8649
            Epoch 287/300
            74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8649
            Epoch 288/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0328 - accuracy: 0.8649
            Epoch 289/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 290/300
            74/74 [==============================] - 0s 118us/sample - loss: 0.0357 - accuracy: 0.8649
            Epoch 291/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0334 - accuracy: 0.8784
            Epoch 292/300
            74/74 [==============================] - 0s 121us/sample - loss: 0.0343 - accuracy: 0.8649
            Epoch 293/300
            74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.8649
            Epoch 294/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0313 - accuracy: 0.8649
            Epoch 295/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0342 - accuracy: 0.8649
            Epoch 296/300
            74/74 [==============================] - 0s 109us/sample - loss: 0.0319 - accuracy: 0.8649
            Epoch 297/300
            74/74 [==============================] - 0s 120us/sample - loss: 0.0323 - accuracy: 0.8649
            Epoch 298/300
            74/74 [==============================] - 0s 115us/sample - loss: 0.0349 - accuracy: 0.8649
            Epoch 299/300
            74/74 [==============================] - 0s 114us/sample - loss: 0.0316 - accuracy: 0.8649
            Epoch 300/300
            74/74 [==============================] - 0s 111us/sample - loss: 0.0330 - accuracy: 0.8649
        
        
        
        ```python
        print ('Average f1 score', np.mean(test_F1))
        print ('Average Run time', np.mean(time_k))
        ```
        
            Average f1 score 0.6
            Average Run time 3.3290751775105796
        
        
        #### Building an LSTM Classifier on the sequences for comparison
        We built an LSTM Classifier on the sequences to compare the accuracy.
        
        
        ```python
        X = darpa_data['seq']
        encoded_X = np.ndarray(shape=(len(X),), dtype=list)
        for i in range(0,len(X)):
            encoded_X[i]=X.iloc[i].split("~")
        ```
        
        
        ```python
        max_seq_length = np.max(darpa_data['seqlen'])
        encoded_X = tf.keras.preprocessing.sequence.pad_sequences(encoded_X, maxlen=max_seq_length)
        ```
        
        
        ```python
        kfold = 3
        random_state = 11
        
        test_F1 = np.zeros(kfold)
        time_k = np.zeros(kfold)
        
        epochs = 50
        batch_size = 15
        skf = StratifiedKFold(n_splits=kfold, shuffle=True, random_state=random_state)
        k = 0
        
        for train_index, test_index in skf.split(encoded_X, y):
            X_train, X_test = encoded_X[train_index], encoded_X[test_index]
            y_train, y_test = y[train_index], y[test_index]
            
            embedding_vecor_length = 32
            top_words=50
            model = Sequential()
            model.add(Embedding(top_words, embedding_vecor_length, input_length=max_seq_length))
            model.add(LSTM(32))
            model.add(Dense(1))
            model.add(Activation('sigmoid'))
            model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
            
            model.summary()
            
            start_time = time.time()
            model.fit(X_train, y_train, epochs=epochs, batch_size=batch_size, verbose=1)
            end_time=time.time()
            time_k[k]=end_time-start_time
        
            y_pred = model.predict_proba(X_test).round().astype(int)
            y_train_pred=model.predict_proba(X_train).round().astype(int)
            test_F1[k]=sklearn.metrics.f1_score(y_test, y_pred)
            k+=1
        ```
        
            Model: "sequential_13"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            embedding (Embedding)        (None, 1773, 32)          1600      
            _________________________________________________________________
            lstm (LSTM)                  (None, 32)                8320      
            _________________________________________________________________
            dense_36 (Dense)             (None, 1)                 33        
            _________________________________________________________________
            activation_36 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 9,953
            Trainable params: 9,953
            Non-trainable params: 0
            _________________________________________________________________
            Train on 74 samples
            Epoch 1/50
            74/74 [==============================] - 4s 60ms/sample - loss: 0.6934 - accuracy: 0.5135
            Epoch 2/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.6591 - accuracy: 0.8784
            Epoch 3/50
            74/74 [==============================] - 3s 46ms/sample - loss: 0.6201 - accuracy: 0.8784
            Epoch 4/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.5612 - accuracy: 0.8784
            Epoch 5/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.4500 - accuracy: 0.8784
            Epoch 6/50
            74/74 [==============================] - 3s 46ms/sample - loss: 0.3808 - accuracy: 0.8784
            Epoch 7/50
            74/74 [==============================] - 4s 49ms/sample - loss: 0.3807 - accuracy: 0.8784
            Epoch 8/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3795 - accuracy: 0.8784
            Epoch 9/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3718 - accuracy: 0.8784
            Epoch 10/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3713 - accuracy: 0.8784
            Epoch 11/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3697 - accuracy: 0.8784
            Epoch 12/50
            74/74 [==============================] - 3s 46ms/sample - loss: 0.3696 - accuracy: 0.8784
            Epoch 13/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3696 - accuracy: 0.8784
            Epoch 14/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3677 - accuracy: 0.8784
            Epoch 15/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3666 - accuracy: 0.8784
            Epoch 16/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3661 - accuracy: 0.8784
            Epoch 17/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3654 - accuracy: 0.8784
            Epoch 18/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3634 - accuracy: 0.8784
            Epoch 19/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3638 - accuracy: 0.8784
            Epoch 20/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3598 - accuracy: 0.8784
            Epoch 21/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3584 - accuracy: 0.8784
            Epoch 22/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3539 - accuracy: 0.8784
            Epoch 23/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3588 - accuracy: 0.8784
            Epoch 24/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3374 - accuracy: 0.8784
            Epoch 25/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3356 - accuracy: 0.8784
            Epoch 26/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3044 - accuracy: 0.8784
            Epoch 27/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2896 - accuracy: 0.8784
            Epoch 28/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2864 - accuracy: 0.8784
            Epoch 29/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2430 - accuracy: 0.8784
            Epoch 30/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2675 - accuracy: 0.8784
            Epoch 31/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2764 - accuracy: 0.8784
            Epoch 32/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2404 - accuracy: 0.8784
            Epoch 33/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2131 - accuracy: 0.8784
            Epoch 34/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2109 - accuracy: 0.8784
            Epoch 35/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2060 - accuracy: 0.8919
            Epoch 36/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1925 - accuracy: 0.9054
            Epoch 37/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1913 - accuracy: 0.9189
            Epoch 38/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1947 - accuracy: 0.9324
            Epoch 39/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1762 - accuracy: 0.9324
            Epoch 40/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1856 - accuracy: 0.9459
            Epoch 41/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1689 - accuracy: 0.9324
            Epoch 42/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1762 - accuracy: 0.9324
            Epoch 43/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1914 - accuracy: 0.9459
            Epoch 44/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1867 - accuracy: 0.9595
            Epoch 45/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1602 - accuracy: 0.9459
            Epoch 46/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1627 - accuracy: 0.9324
            Epoch 47/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1475 - accuracy: 0.9595
            Epoch 48/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1527 - accuracy: 0.9595
            Epoch 49/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1408 - accuracy: 0.9595
            Epoch 50/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1745 - accuracy: 0.9595
            Model: "sequential_14"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            embedding_1 (Embedding)      (None, 1773, 32)          1600      
            _________________________________________________________________
            lstm_1 (LSTM)                (None, 32)                8320      
            _________________________________________________________________
            dense_37 (Dense)             (None, 1)                 33        
            _________________________________________________________________
            activation_37 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 9,953
            Trainable params: 9,953
            Non-trainable params: 0
            _________________________________________________________________
            Train on 74 samples
            Epoch 1/50
            74/74 [==============================] - 4s 59ms/sample - loss: 0.6898 - accuracy: 0.5676
            Epoch 2/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.6513 - accuracy: 0.8784
            Epoch 3/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.6120 - accuracy: 0.8784
            Epoch 4/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.5458 - accuracy: 0.8784
            Epoch 5/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.4240 - accuracy: 0.8784
            Epoch 6/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3963 - accuracy: 0.8784
            Epoch 7/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3924 - accuracy: 0.8784
            Epoch 8/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3851 - accuracy: 0.8784
            Epoch 9/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3731 - accuracy: 0.8784
            Epoch 10/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3708 - accuracy: 0.8784
            Epoch 11/50
            74/74 [==============================] - 3s 46ms/sample - loss: 0.3737 - accuracy: 0.8784
            Epoch 12/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3716 - accuracy: 0.8784
            Epoch 13/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3706 - accuracy: 0.8784
            Epoch 14/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3697 - accuracy: 0.8784
            Epoch 15/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3698 - accuracy: 0.8784
            Epoch 16/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.3686 - accuracy: 0.8784
            Epoch 17/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3686 - accuracy: 0.8784
            Epoch 18/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3682 - accuracy: 0.8784
            Epoch 19/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.3667 - accuracy: 0.8784
            Epoch 20/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3678 - accuracy: 0.8784
            Epoch 21/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3640 - accuracy: 0.8784
            Epoch 22/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3621 - accuracy: 0.8784
            Epoch 23/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3601 - accuracy: 0.8784
            Epoch 24/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3574 - accuracy: 0.8784
            Epoch 25/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3514 - accuracy: 0.8784
            Epoch 26/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3552 - accuracy: 0.8784
            Epoch 27/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3381 - accuracy: 0.8784
            Epoch 28/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3274 - accuracy: 0.8784
            Epoch 29/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3118 - accuracy: 0.8784
            Epoch 30/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2943 - accuracy: 0.8784
            Epoch 31/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2783 - accuracy: 0.8784
            Epoch 32/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.2459 - accuracy: 0.8784
            Epoch 33/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.2276 - accuracy: 0.8919
            Epoch 34/50
            74/74 [==============================] - 3s 46ms/sample - loss: 0.2345 - accuracy: 0.9189
            Epoch 35/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.1888 - accuracy: 0.9189
            Epoch 36/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2413 - accuracy: 0.9189
            Epoch 37/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.2389 - accuracy: 0.8649
            Epoch 38/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.2136 - accuracy: 0.9054
            Epoch 39/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1933 - accuracy: 0.9054
            Epoch 40/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.1882 - accuracy: 0.8919
            Epoch 41/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1999 - accuracy: 0.9054
            Epoch 42/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1760 - accuracy: 0.8919
            Epoch 43/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1990 - accuracy: 0.8243
            Epoch 44/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1632 - accuracy: 0.9189
            Epoch 45/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1626 - accuracy: 0.9189
            Epoch 46/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1700 - accuracy: 0.8784
            Epoch 47/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1529 - accuracy: 0.9189
            Epoch 48/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1641 - accuracy: 0.9189
            Epoch 49/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1482 - accuracy: 0.9189
            Epoch 50/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.1661 - accuracy: 0.8784
            Model: "sequential_15"
            _________________________________________________________________
            Layer (type)                 Output Shape              Param #   
            =================================================================
            embedding_2 (Embedding)      (None, 1773, 32)          1600      
            _________________________________________________________________
            lstm_2 (LSTM)                (None, 32)                8320      
            _________________________________________________________________
            dense_38 (Dense)             (None, 1)                 33        
            _________________________________________________________________
            activation_38 (Activation)   (None, 1)                 0         
            =================================================================
            Total params: 9,953
            Trainable params: 9,953
            Non-trainable params: 0
            _________________________________________________________________
            Train on 74 samples
            Epoch 1/50
            74/74 [==============================] - 5s 63ms/sample - loss: 0.6756 - accuracy: 0.8919
            Epoch 2/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.6397 - accuracy: 0.8919
            Epoch 3/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.5892 - accuracy: 0.8919
            Epoch 4/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.5005 - accuracy: 0.8919
            Epoch 5/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3800 - accuracy: 0.8919
            Epoch 6/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3459 - accuracy: 0.8919
            Epoch 7/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3529 - accuracy: 0.8919
            Epoch 8/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3502 - accuracy: 0.8919
            Epoch 9/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3455 - accuracy: 0.8919
            Epoch 10/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3438 - accuracy: 0.8919
            Epoch 11/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3434 - accuracy: 0.8919
            Epoch 12/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3431 - accuracy: 0.8919
            Epoch 13/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3433 - accuracy: 0.8919
            Epoch 14/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3433 - accuracy: 0.8919
            Epoch 15/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.3432 - accuracy: 0.8919
            Epoch 16/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.3421 - accuracy: 0.8919
            Epoch 17/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3426 - accuracy: 0.8919
            Epoch 18/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3423 - accuracy: 0.8919
            Epoch 19/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3424 - accuracy: 0.8919
            Epoch 20/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.3420 - accuracy: 0.8919
            Epoch 21/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3429 - accuracy: 0.8919
            Epoch 22/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3412 - accuracy: 0.8919
            Epoch 23/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3402 - accuracy: 0.8919
            Epoch 24/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3397 - accuracy: 0.8919
            Epoch 25/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3390 - accuracy: 0.8919
            Epoch 26/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3398 - accuracy: 0.8919
            Epoch 27/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3372 - accuracy: 0.8919
            Epoch 28/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3374 - accuracy: 0.8919
            Epoch 29/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3323 - accuracy: 0.8919
            Epoch 30/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.3323 - accuracy: 0.8919
            Epoch 31/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.3253 - accuracy: 0.8919
            Epoch 32/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.3228 - accuracy: 0.8919
            Epoch 33/50
            74/74 [==============================] - 3s 40ms/sample - loss: 0.3075 - accuracy: 0.8919
            Epoch 34/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2985 - accuracy: 0.8919
            Epoch 35/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.3000 - accuracy: 0.8919
            Epoch 36/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.2791 - accuracy: 0.8919
            Epoch 37/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.2580 - accuracy: 0.8919
            Epoch 38/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2874 - accuracy: 0.8919
            Epoch 39/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.2712 - accuracy: 0.8919
            Epoch 40/50
            74/74 [==============================] - 3s 44ms/sample - loss: 0.2432 - accuracy: 0.8919
            Epoch 41/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.2231 - accuracy: 0.8919
            Epoch 42/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.2146 - accuracy: 0.8919
            Epoch 43/50
            74/74 [==============================] - 3s 45ms/sample - loss: 0.2026 - accuracy: 0.8919
            Epoch 44/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.2371 - accuracy: 0.9054
            Epoch 45/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2293 - accuracy: 0.9189
            Epoch 46/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2524 - accuracy: 0.9324
            Epoch 47/50
            74/74 [==============================] - 3s 42ms/sample - loss: 0.2331 - accuracy: 0.9189
            Epoch 48/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.2046 - accuracy: 0.8919
            Epoch 49/50
            74/74 [==============================] - 3s 43ms/sample - loss: 0.2020 - accuracy: 0.8919
            Epoch 50/50
            74/74 [==============================] - 3s 41ms/sample - loss: 0.1992 - accuracy: 0.9054
        
        
        
        ```python
        print ('Average f1 score', np.mean(test_F1))
        print ('Average Run time', np.mean(time_k))
        ```
        
            Average f1 score 0.3313492063492064
            Average Run time 157.32080109914145
        
        
        We find that the LSTM classifier gives a significantly lower F1 score. This may be improved by changing the model. However, we find that the SGT embedding could work with a small and unbalanced data without the need of a complicated classifier model.
        
        LSTM models typically require more data for training and also has significantly more computation time. The LSTM model above took 425.6 secs while the MLP model took just 9.1 secs.
        
        
        ```python
        
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
