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jaungiers / LSTM-Neural-Network-for-Time-Series-Prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

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About normalization and de-normalization

hongyi-huang opened this issue · comments

commented

I inspect the code and in my view, you normalize each window data that contains the input and result both. (e.g. window data is in size $seq_len$, [0:seq_len-1] is input and the last one should be output) In the case that I didn't know the output, i.e., I only know input data of size $seq_len-1$, how could I normalize the input for prediction?