Hi Subutai, Please clarify. The input is a sparse vector of the indexes of predicted columns correct? Namely the TM output?
On Sun, Oct 18, 2015 at 11:13 PM, Subutai Ahmad <[email protected]> wrote: > The CLA classifier normally gets the active cells of the TM passed in (not > active columns or predicted cells/columns). > > --Subutai > > > On Oct 18, 2015, at 21:01, cogmission (David Ray) < > [email protected]> wrote: > > Hi Sebastian, > > I'm not sure what you were doing, but as far as I've always known, the > CLAClassifier takes the TM output of predicted columns? There term "Active > columns" usually refers to the SP input. > > It's confusing because the CLAClassifier method documentation says "Active > Columns" --> > > patternNZ: list of the active indices from the output below > > > This should probably be changed to "predicted columns". The clue that I > take is that the column indices passed in are "sparse" (meaning that the > input vector consists of the indices of columns which have on bits). (i.e > [1,3,5] instead of [0,1,0,1,0,1]) > > Cheers, > David > > On Sun, Oct 18, 2015 at 10:35 PM, Sebastián Narváez <[email protected]> > wrote: > >> Regarding my previous question, I've encountered that the error was >> rather silly. I was feeding the CLA Classifier with the predicted columns >> instead of the active ones. Changing that turned out in accuarate >> multi-step predictions. >> >> On Sun, Oct 18, 2015 at 3:31 PM, Sebastián Narváez <[email protected]> >> wrote: >> >>> Hey guys. I've trained nupic with some data, but when I try to predict >>> the outcome given an input with the CLA Classifier, it always predicts the >>> output belonging to the first sequence. I've tried changing the order of >>> which I pass the data to Nupic, but it will just predict the output of the >>> new first sequence. Am I doing something wrong? >>> I've attached the data I'm using for these tests. For each column, each >>> word is passed to a TM. Then the Active cells of both are passed into a >>> general TM (first all the words from the first column, and then all the >>> words from the second column). I reset() all the TMs for each row. >>> >>> Thanks in advance. >>> >> >> > > > -- > *With kind regards,* > > David Ray > Java Solutions Architect > > *Cortical.io <http://cortical.io/>* > Sponsor of: HTM.java <https://github.com/numenta/htm.java> > > [email protected] > http://cortical.io > > -- *With kind regards,* David Ray Java Solutions Architect *Cortical.io <http://cortical.io/>* Sponsor of: HTM.java <https://github.com/numenta/htm.java> [email protected] http://cortical.io
