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I'm trying to predict a time series, let's say I have 3 features and a target variable. I used the standard approach when feature lags have the same length, for example, 10. Then the size of my batch will be (32, 10, 3). But looking at the autocorrelation graphs, I want to use a lag length of 10 for the first feature, 5 for the second, and 7 for the third. How can I construct a batch in this case?

My architecture looks like this:

inp = Input(shape=(10, 3, batch_size=None)
x = LSTM(128, return_sequences=True)(inp)
x = Flatten()(x)
x = Dropout(0.2)(x)
out = Dense(2, activation='linear')(x)
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  • $\begingroup$ Have you gotten any answers or made any advances in this issue? I have been searching a lot through the internet and no one seemed to talk about this or have any information but you. Please let me know if you have any updates or directions. Thank you. $\endgroup$
    – Rima
    Nov 15, 2021 at 16:28
  • $\begingroup$ @Rima No, unfortunately, I have not found an answer to my question $\endgroup$
    – Fissium
    Nov 16, 2021 at 10:24

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