I've been searching for a while now to find the precise way to feed a Recurrent Neural Network (RNN, LSTM, GRU, ESN, Etc) with time series data with no real success. Here is a question that was close, but the answers aren't very clear: Proper way of using recurrent neural network for time series analysis I'm not looking for a breakdown of how the networks work, but rather how to structure the input/output vectors for optimal results. So, let's say I'm working with a growing sinusoid. I am very familiar with the sliding time window approach that works well with Feed forward networks (FFN). And this works very well with FFN (And with RNN also), but I'm led to believe RNN shouldn't need to be setup that way.
Oct-13-2019, 21:10:07 GMT