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[D] Apply GRU to some features but not others?

I am not an expert at either neural nets in general or RNN’s but I have a data set that I would like to experiment with that is mostly time series in nature. I have roughly 30 different time series variables that I would like to use as my input in order to predict the classification of several classes

As i’ve been looking into RNN’s, I only recently came across the concept of a GRU and from my initial thoughts it seems better suited to my particular task as I can specify which of the variables need something like a GRU unit and which do not. Is that even possible? For the variables that do not have a GRU I would like the longer term dependency to decay over the time series, thus I think I want to avoid LSTM.

I am curious to hear if there are any best practices for using GRU or even deep RNN in general on time series classification. A lot of what I am reading re:RNN is related to NLP, which is an area I also like but quite different vs time series modelling.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.