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@@ -103,17 +103,22 @@ def create_model(_input_shape):
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model.add(ConvLSTM2D(filters=100, kernel_size=(3, 3),
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input_shape=_input_shape,
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+ dropout=0.4,
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+ recurrent_dropout=0.4,
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padding='same', return_sequences=True))
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model.add(BatchNormalization())
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- model.add(Dropout(0.4))
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model.add(ConvLSTM2D(filters=50, kernel_size=(3, 3),
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+ dropout=0.4,
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+ recurrent_dropout=0.4,
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padding='same', return_sequences=True))
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model.add(BatchNormalization())
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model.add(Dropout(0.4))
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model.add(Conv3D(filters=20, kernel_size=(3, 3, 3),
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activation='sigmoid',
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+ dropout=0.4,
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+ recurrent_dropout=0.4,
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padding='same', data_format='channels_last'))
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model.add(Dropout(0.4))
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@@ -200,7 +205,7 @@ def main():
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model.summary()
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print("Fitting model with custom class_weight", class_weight)
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- history = model.fit(X_train, y_train, batch_size=64, epochs=30, validation_split = 0.30, verbose=1, shuffle=True, class_weight=class_weight)
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+ history = model.fit(X_train, y_train, batch_size=64, epochs=1, validation_split = 0.30, verbose=1, shuffle=True, class_weight=class_weight)
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# list all data in history
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# print(history.history.keys())
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