I am not using KNN, I am routing a standard neural network through the HTM's on cells (so only small subnetworks are activate at a time). That is probably why it is working better for me.
On Sun, Jan 18, 2015 at 6:20 PM, <[email protected]> wrote: > Hi: > > > Hi, Eric. 95% and in 5 mins, That's pretty good if just with a SP + KNN. > Did you turn the SP learning on? or just turn off and use it to get the > SDR. Recently, i changed the training order - the order of training > sequences. before that, I just followed the order of MNIST dataset. Now the > training sequences are from 0 to 9. I got 97% on a small dataset > (6000/1000). I am still wondering if there are some errors in my code which > I just added, because all of the errors happen to input 0 and 1. So, now i > am trying to train the full size dataset with SP learning on and classifier > learning on to see what will happen. With the current parameters, training > is really slow. I am still waiting for the result. > > Actually, I'm thinking about using other non-python engine. I am using the > nupic python currently. > > The world record 0.23 is using deep CNN as the basic unit. Then using them > as column structures...Anyway, the result is applaudable. > > > What about the parameters which you used for the SP? > > > > Thank you. > An Qi > Tokyo University of Agriculture and Technology - Nakagawa Laboratory > 2-24-16 Naka-cho, Koganei-shi, Tokyo 184-8588 > [email protected] > > > On Sun, 18 Jan 2015 12:05:42 -0500 > Eric Laukien <[email protected]> wrote: > >> Hmm, I got 95% after five minutes. Perhaps you can try CHTM on this task. >> Especially with the latest spatial pooler, which is far more efficient >> than >> what I had before, it should work very well. >> Also make sure to use multiple layers, and make the NN pass through all of >> them. >> The world record is held by Yann Lecun using "sparse codes" which are >> SDRs. >> So the approach definitely works. >> >> Regards, >> Eric Laukien >> >> >> On Sun, Jan 18, 2015 at 5:06 AM, Fergal Byrne < >> [email protected]> >> wrote: >> >> Hi An Qi, >>> >>> That's very interesting, thanks for sharing. Could you place your code >>> and >>> setup on Github so we can take a look at exactly what you did? It seems >>> at >>> first glance that you're just using SP, which is perhaps the least >>> powerful >>> part of HTM. I think a saccading system which also does Temporal Pooling >>> (which we haven't quite got yet) would be able to do a much better job on >>> this kind of task, but 89.6% is still a very good start for a plain >>> SP-based approach. >>> >>> Very well done! Hopefully we can help you do even better. >>> >>> Regards, >>> >>> Fergal Byrne >>> >>> On Sun, Jan 18, 2015 at 7:00 AM, <[email protected]> wrote: >>> >>> Hello. >>>> >>>> Sorry for the last email. Thx to the rich formatting :( ... I have to >>>> type again. >>>> >>>> Recently, I got the result of the test. I followed the source code and >>>> built the Spatial Pooler + KNN classifier. Then I extracted images from >>>> MNIST dataset(Train/test : 60000/10000) and parsed them to the model. I >>>> tried to test with different parameters (using small dataset: >>>> Train/Test - >>>> 6000/1000 ), the best recognition result is about 87.6%. After that, i >>>> tried the full size MNIST dataset, the result is 89.6%. Currently, this >>>> is >>>> the best result I got. >>>> >>>> Here is the statistics. It shows the error counts for each digits. the >>>> Row presents the input digit. the column presents the recognition >>>> result. >>>> Most of the "7" are recognized as "9". It seems the SDR from SP is still >>>> not good enough for the classifier. >>>> >>>> I found some interesting things. When I let the "inputDimensions" and >>>> "columnDimensions" be "784" and "1024", the result will be around 68%. >>>> If i >>>> use "(28,28)","(32,32)" and keep others the same, the result will be >>>> around >>>> 82%. That 's a lot of difference. It seems the array shape will effect >>>> SP a >>>> lot. >>>> >>>> Did any one get a better result? Does any one have some suggestion about >>>> the parameters or others? >>>> >>>> Thank you. >>>> An Qi >>>> Tokyo University of Agriculture and Technology - Nakagawa Laboratory >>>> 2-24-16 Naka-cho, Koganei-shi, Tokyo 184-8588 >>>> [email protected] >>>> >>>> >>> >>> >>> -- >>> >>> Fergal Byrne, Brenter IT >>> >>> http://inbits.com - Better Living through Thoughtful Technology >>> http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne >>> >>> Founder of Clortex: HTM in Clojure - >>> https://github.com/nupic-community/clortex >>> >>> Author, Real Machine Intelligence with Clortex and NuPIC >>> Read for free or buy the book at https://leanpub.com/realsmartmachines >>> >>> Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014: >>> http://euroclojure.com/2014/ >>> and at LambdaJam Chicago, July 2014: http://www.lambdajam.com >>> >>> e:[email protected] t:+353 83 4214179 >>> Join the quest for Machine Intelligence at http://numenta.org >>> Formerly of Adnet [email protected] http://www.adnet.ie >>> >>> > >
