I have created an LSTM model which is trained on an 8-hour time frame for a cryptocurrency. When the training is finished I see that it is learning the pattern but there is some bias in it. How to handle this?
This is my model:
'''Build LST model''' model = Sequential() model.add(LSTM(50, return_sequences = True, input_shape=(x_train.shape[1:]))) model.add(Dropout(0.2)) model.add(LSTM(50, return_sequences = False)) model.add(Dense(25)) model.add(Dropout(0.2)) model.add(Dense(1)) '''Compile the Model''' model.compile(optimizer='adam', loss='mean_squared_error') model.fit(x_train, y_train, batch_size=1, epochs=50,verbose = 2)