jpeg729:

Are the target values normalized?
What about adding more training iterations? The model might need more time to adapt to the inputs when there are more of them.


Not yet. Actually my input and output are somewhat related, in the sense that output < = input. So, I thought we should normalize them using the same function. What do you think?



 jpeg729:

Maybe my ideas were badly formed too. I’ll try again. From your input data you produce sequences of length 24 that start at midnight, this is your training data. You could run through the process again producing sequences of length 24 that start at 1am, and add these to the training data. And again producing sequences that start at 2am, and so on. That way you would have windows that start at midnight, and windows that start at 1am, and windows that start at 2am, etc. Adding the hour features would be tricky though.


Hmm. This is exactly what I had in mind when I mentioned rolling windows. This sounds interesting and hopefully beneficial too!