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@@ -36,35 +36,37 @@ def generate_model_2D(_input_shape):
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model.add(Flatten())
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- model.add(Dense(140))
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- model.add(Activation('relu'))
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model.add(BatchNormalization())
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model.add(Dropout(0.5))
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+ model.add(Activation('relu'))
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- # model.add(Dense(120))
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- # model.add(Activation('sigmoid'))
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- # model.add(BatchNormalization())
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- # model.add(Dropout(0.5))
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+ model.add(Dense(256,
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+ kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4),
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+ bias_regularizer=regularizers.l2(1e-4),
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+ activity_regularizer=regularizers.l2(1e-5)))
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- model.add(Dense(80))
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- model.add(Activation('relu'))
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model.add(BatchNormalization())
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model.add(Dropout(0.5))
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-
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- model.add(Dense(40))
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model.add(Activation('relu'))
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- model.add(BatchNormalization())
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- model.add(Dropout(0.5))
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- model.add(Dense(20))
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- model.add(Activation('relu'))
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+ model.add(Dense(64,
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+ kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4),
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+ bias_regularizer=regularizers.l2(1e-4),
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+ activity_regularizer=regularizers.l2(1e-5)))
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+
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model.add(BatchNormalization())
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model.add(Dropout(0.5))
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+ model.add(Activation('relu'))
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+
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+ model.add(Dense(20,
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+ kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4),
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+ bias_regularizer=regularizers.l2(1e-4),
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+ activity_regularizer=regularizers.l2(1e-5)))
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model.add(Dense(2))
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model.add(Activation('softmax'))
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- model.compile(loss='categorical_crossentropy',
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+ model.compile(loss='binary_crossentropy',
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optimizer='adam',
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#metrics=['accuracy', metrics.auc])
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metrics=['accuracy'])
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