I have a training data with various sequences, which I pass trough a nupic
structure (made of SPs, TMs and a CLAClassifier on top). Some of the
sequences are alike (there are only one or two elements that change between
them). I've noticed that if I put the alike sequences together, one after
the other, nupic will learn the differences better than if I put them
appart. I reset() all the TMs when a sequence ends, so my guess is that it
has to do with the classifier. Anyone knows why could this happen?
Note that I have not done any serious tests about this. I could, but it
would take some time.
