Hello. I'm a master student of TUAT. Currently, I am doing some research which is about handwritten character recognition(offline recognition). and I'm very interested in the HTM. I read the paper "How the Brain Might Work: A Hierarchical and Temporal Model for Learning and Recognition" and "Pattern Recognition by Hierarchical Temporal Memory", which are about the old version of HTM. I think the result shows in the paper is good, and i want to test the HTM with some other dataset (Alphabet, maybe more complex dataset like Chinese character), then I found the old HTM is obsolete. Now i want to test the HTMCLA with MNIST database (It seems someone already did it, but I didn't find any paper shows the result).
I found there is a mnist test on the github(https://github.com/numenta/nupic.research/blob/master/image_test/mnist_test.py). Then I dumped all images and labels from MNIST database(http://yann.lecun.com/exdb/mnist/) and try to use it to see if it works. After fixed some error, the program could run without any problem. But the result shows that the KNNClassifier only learned 1 category. "Num categories learned 1" The accuracy is lower than 10%. Any one knows what kind of problem that is. could any one help me? Thank you. An Qi Tokyo University of Agriculture and Technology - Nakagawa Laboratory 2-24-16 Naka-cho, Koganei-shi, Tokyo 184-8588 [email protected]
