It's odd that the SP runs out of memory. Could you post your code here?
On Wed, Jan 22, 2014 at 4:15 PM, Allan Inocêncio de Souza Costa < [email protected]> wrote: > Thanks for the reply, Pedro and Mark. > > @Pedro > You're right, I'm not using SP or TP. I did tried to simply activate SP in > model_params.py, but it soon ran out of memory (I'm using 8 GB), so I have > to use few columns and the result does not get improved. > > @Mark > I agree with point 3. > About point 1: I think you're right about the classifier and I would like > to know more details about how it is implemented, so if someone knows, > please let me know. > About point 2: the images are encoded in 1D arrays with 784 (28x28) > features, so I do lost topological information. But it is still a high > dimensional space in which the data shows good clustering, so that even the > hyperplanes obtained by simple logistic regression are capable of > classifying the digits with good accuracy (> 90%). That's why I would like > to get more information about the classifier itself. > > Best regards, > Allan > > > Em Quarta-feira, 22 de Janeiro de 2014 15:28, Pedro Tabacof < > [email protected]> escreveu: > Marek's second point is of utmost importance for anyone doing image > classification. It would be awesome if someone could make 2D topology > easily available. Convolutional neural networks are so much better than > regular neural networks for image classification. > > > > On Wed, Jan 22, 2014 at 3:18 PM, Marek Otahal <[email protected]>wrote: > > Hi Allan, > > that was maybe me, it's great someone is working on the MNIST here! > > 1/ I'm not 100% clear about the Classifier, but I think it's just a helper > utility, unrelated to the HTM/CLA, so you've been testing performance of > any algorithm the CLassifier implements (not CLA imho). So you'd want to > create a CLA (with SP only) and place Classifier atop of it. The pipeline > would look like: {MNIST-data[ith-example]} >>> CLA(without TP) >>>(you get > SDR) >>> Classifier (add MNIST-label[ith-example] > > 2/ I assume the mnist dataset is created from 2D images of hadwritten > digits -> and just simply put in 1D array (??) > Then you'll lose lot of topological info passing it to the CLA just as is. > I think this will require ressurection of the Image Encoders that take into > account distance for neighborhood pixels (each pixel has 8 neighboring px), > this is used in inhibition etc. > > 3/ You're probably overfitting, rather experiment with 80%/20% data split. > > Cheers, Mark > > > On Wed, Jan 22, 2014 at 5:57 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 > > > > > -- > Marek Otahal :o) > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > > > > -- > Pedro Tabacof, > Unicamp - Eng. de Computação 08. > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > > > _______________________________________________ > 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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