Hi Jim, This is an interesting task. I am confused about how the amount of required training varies with the data set size (Fig. 3). Do you have any intuition on this (why it first increase and then decreases). I am also having trouble to understand the criterion for stop training sounds. You said there must be "no collisions" for images of different characters. But for SDR, a small number of collisions should not affect the performance much (since the representation is distributed). It would be interesting if you could plot the "error rate" as a function of iteration number during learning.
Yuwei On Sun, Jul 6, 2014 at 12:20 AM, Jim Bridgewater <[email protected]> wrote: > Hi everyone, > > I wanted to make sure I know how to size the spatial pooler properly > for a given task so I ran a few tests to measure its image recognition > accuracy on data sets of different sizes. One of the surprising > results was how the amount of training required varies with the size > of the data set. The results are shown in the attached pdf. > > -- > Jim Bridgewater, PhD > Arizona State University > 480-227-9592 > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > -- -- Yuwei Cui Algorithm Internship, Numenta Inc. PhD Candidate, Neuroscience and Cognitive Science University of Maryland, College Park, MD, 20742 Homepage: http://terpconnect.umd.edu/~ywcui/
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