Training A Multi-variate Multi-series Regression Problem With Stateful Lstms In Keras

I have time series of P processes, each of varying length but all having 5 variables (dimensions). I am trying to predict the estimated lifetime of a test process. I am approaching

Solution 1:

Usually when results are the same it's because your data isn't normalized. I suggest you center your data with mean=0 and std=1 with a simple normal transform (ie. (data - mean)/std ). Try transforming it like so before training and testing. Differences in how data is normalized between training and testing sets can also cause problems, which may be the cause of your discrepancy in train vs test loss. Always use the same normalization technique for all your data.