Hi Allan, If I understood it correctly, you are using the classifier without the TP or the SP. Is that correct? I think you should try with the SP, it will probably yield much better results.
I also suggest testing on a different dataset, so you can check whether the model is generalizing well or just overfitting. Pedro. On Wed, Jan 22, 2014 at 2:57 PM, Allan Inocêncio de Souza Costa < [email protected]> wrote: > > Hi, > > I read a question that someone else asked here, but I couldn't find the > question nor the answers (if any), so I will ask again, as I'm now working > around with the classifier. > > I tried to apply the classifier to the task of handwritten recognition > using the MNIST dataset. The best result I got was an overall accuracy of > about 42% (by that I mean that after training the entire dataset, the > proportion of right predictions from the first to the last training example > was 42%), after playing a little with the encoders. Of course this is > better than the expected 10% accuracy of a random picker algorithm, but it > falls short of what is accomplished by other (linear) algorithms. For those > interested, I attached a plot of the accuracy. > > So here comes the question: what are the inner workings of the classifier? > I'm puzzled as it doesn't have a SP. Can someone help or point to some > reading? > > Best regards, > Allan > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > -- Pedro Tabacof, Unicamp - Eng. de Computação 08.
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