Matt, On a separate subject I've been thinking it would be super cool to have some way to post a snap shot of all the code and data required for each set of results so if someone is interested after looking at the results they could run the code themselves. I'm not sure what the best way to do this is. Git tags or a webpage or something else. Any ideas?
On Mon, Jul 7, 2014 at 2:20 PM, Jim Bridgewater <[email protected]> wrote: > Great! I'm glad you gave it a try Matt. > > I ran into that JPEG decoder issue on the Amazon EC2 image that Ian > put together. It looks like PIL and pillow depend on libjpeg-dev for > this so it has to be installed when PIL / pillow is compiled. > > http://stackoverflow.com/questions/8915296/python-image-library-fails-with-message-decoder-jpeg-not-available-pil > > > > > > On Mon, Jul 7, 2014 at 8:41 AM, Matthew Taylor <[email protected]> wrote: >> Thanks Jim. I was able to run your demo, but I had to recompile PIL because >> the "jpeg decoder" was missing. >> >> --------- >> Matt Taylor >> OS Community Flag-Bearer >> Numenta >> >> >> On Sun, Jul 6, 2014 at 11:09 PM, Jim Bridgewater <[email protected]> wrote: >>> >>> Here's the version of this experiment using an SP with 1024 columns >>> and 16 active columns on a data set that contains 16 characters (0-9, >>> A-F). >>> >>> The results are similar in that setting increment for active columns, >>> synPermActiveInc, equal to the connection threshold, synPermConnected, >>> tends to produce the best results. However, one exception was that >>> setting both increment and decrement values to 0.1*synPermConnected >>> produced 100% accuracies for all but the highest threshold values. >>> This was not the case for the SP with only one active column. >>> >>> This time I included pictures of the permanences for the best and >>> worst configurations for comparison. For the worst configuration many >>> columns have permanences far above zero for inputs that are not >>> active for any of the input images. Maybe these columns were never >>> active and therefore those permanences were never decremented? I >>> guess that is another experiment to run...recording active columns to >>> see how many get used. >>> >>> On Sat, Jul 5, 2014 at 8:23 AM, Ian Danforth <[email protected]> >>> wrote: >>> > >>> > >>> > >>> > On Fri, Jul 4, 2014 at 9:31 PM, Jim Bridgewater <[email protected]> >>> > wrote: >>> >> >>> >> Hi Ian, >>> >> >>> >> You are correct. Thanks for the feedback, I've updated the >>> >> introduction and attached the revised document. >>> >> >>> >> There is still the question of whether these results will hold with >>> >> more active columns and I plan to run that experiment and post the >>> >> results soon. I am planning to use your Amazon EC2 image for this >>> >> since these jobs can take some time for large numbers of columns. >>> >> >>> > >>> > Awesome! Let me know if you end up installing tools that you think >>> > should be >>> > part of the default AMI. >>> > >>> >> >>> >> For pooling, I want to duplicate the characters in the data set using >>> >> different fonts and see if I can get the spatial pooler to generalize >>> >> between the different fonts. >>> >> >>> >> >>> > >>> > Looking forward to those results! >>> > >>> > Ian >>> > >>> > >>> > >>> >> >>> >> >>> >> On Fri, Jul 4, 2014 at 6:43 PM, Ian Danforth <[email protected]> >>> >> wrote: >>> >> > Jim, >>> >> > >>> >> > To be clear you have 186 training examples and 256 columns, 100% >>> >> > potential >>> >> > pool and you have 1 column on at a time, so you would expect 100% >>> >> > accuracy. >>> >> > Correct? You might want to note this up front. Something like "this >>> >> > should >>> >> > be an easy task for the spatial pooler, however certain parameter >>> >> > configurations were found to be problematic." >>> >> > >>> >> > Also I know you know this but for others reading along, to do >>> >> > "pooling" >>> >> > the >>> >> > number of training examples needs to be at least > than number of >>> >> > columns >>> >> > and preferably >>. Otherwise each column will perfectly fit a single >>> >> > example. Also you need to test on a separate set of data to see how >>> >> > well >>> >> > the >>> >> > model generalizes. >>> >> > >>> >> > Ian >>> >> > >>> >> > >>> >> > On Fri, Jul 4, 2014 at 12:29 AM, Jim Bridgewater <[email protected]> >>> >> > wrote: >>> >> >> >>> >> >> Hi everyone, >>> >> >> >>> >> >> I'm working on a NuPIC vision toolkit for the Season of NuPIC this >>> >> >> summer and I've created a GitHub repo for it called nupic.vision. >>> >> >> The >>> >> >> URL is: >>> >> >> >>> >> >> https://github.com/baroobob/nupic.vision >>> >> >> >>> >> >> There is a demo for those who want to try it out. >>> >> >> >>> >> >> I've attached the write up of results from using this toolkit to >>> >> >> investigate the effects of the synapse connection threshold, >>> >> >> synPermConnected, the permanence increment for active synapses, >>> >> >> synPermActiveInc, and the permanence decrement for inactive >>> >> >> synapses, >>> >> >> synPermInactiveDec, on image recognition accuracy and the amount of >>> >> >> training required. >>> >> >> >>> >> >> -- >>> >> >> Jim Bridgewater, PhD >>> >> >> Arizona State University >>> >> >> 480-227-9592 >>> >> >> >>> >> >> _______________________________________________ >>> >> >> 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 >>> >> > >>> >> >>> >> >>> >> >>> >> -- >>> >> Jim Bridgewater, PhD >>> >> Arizona State University >>> >> 480-227-9592 >>> >> >>> >> _______________________________________________ >>> >> 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 >>> > >>> >>> >>> >>> -- >>> Jim Bridgewater, PhD >>> Arizona State University >>> 480-227-9592 >>> >>> _______________________________________________ >>> 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 >> > > > > -- > Jim Bridgewater, PhD > Arizona State University > 480-227-9592 -- Jim Bridgewater, PhD Arizona State University 480-227-9592 _______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
