I'm trying to develop a multistep forecasting model using LSTM Network. The model takes three times steps as input and predicting two time_steps. both input and output columns are normalised using minmax_scalar within the range of 0 and 1.
Please see the below model architecture
model = Sequential() model.add(LSTM(80,input_shape=(3,1),activation='sigmoid',return_sequences=True)) model.add(LSTM(20,activation='sigmoid',return_sequences=False)) model.add(Dense(2))
In this case, using sigmoid as an activation function is it correct?