Subutai, Thanks for the link, interesting reading. I'm amused by the problem of it being (1) a problem NuPIC isn't really well suited to and (2) the first thing lots of people are going to try anyway.
Thinking about statistics, it seems to me that if you have a problem with big stationary correlational structure in the inputs--either temporal, as the sine wave example, or spatial, as John's bridge data--you should transform it out so NuPIC can work on the nonobvious features. Thinking about biology, by the time you get to cortex a lot of the stationary structure has been filtered out -- think about the processing in the retina. It's possible that NuPIC is good enough to solve lots of interesting problems even without preprocessing, but I suspect that some care to the input representation could greatly help with performance (in cycles, at least by reducing the input dimensionality) and performance (in error rate, by getting rid of lots of chaff). Or I could be all wet. It happens. - k On Sep 25, 2014, at 1:53 PM, Subutai Ahmad wrote: Hi Kevin, I did some simple experiments with swarming and correlated inputs [1]. One thing to note is that temporal correlation / sequence structure is also very important. That is independent from spatial correlation. --Subutai [1] https://github.com/subutai/nupic.subutai/tree/master/swarm_examples On Thu, Sep 25, 2014 at 11:33 AM, Archie, Kevin <[email protected]<mailto:[email protected]>> wrote: John, I think this is an example of an important general case. On both statistical and biological grounds I suspect you should decorrelate your inputs before producing SDRs from them. I haven't tried this myself (have hardly done anything with NuPIC) but I'm wondering if anyone has done substantial preprocessing to compensate for the statistics of the inputs. Even better would be if anyone has done a comparison of feeding NuPIC decorrelated vs. direct sensor inputs--or a theoretical argument that decorrelating the inputs is unnecessary or unwise. - Kevin ________________________________ From: nupic [[email protected]<mailto:[email protected]>] on behalf of John Blackburn [[email protected]<mailto:[email protected]>] Sent: Tuesday, September 23, 2014 7:27 AM To: Archie, Kevin Subject: Re: Which NuPIC tutorial do you want to see next? Hi Matthew, Rather self serving, but I would love to see a tutorial related to the "bridge" simulation I've been trying to do or similar. I have not got NuPIC to work yet despite some effort. Basically the difference with Hotgym is we have 18 sensors, 10 temperature and 8 tilt (ie strain) and we want to make predictions on all taking account of cross-correlations. So a tutorial with multiple correlated time series would be great! At NPL we monitored a bridge every 5 minutes for 3 years recording all 18 sensors so I think this data would be a great showcase for a real-world NuPIC example. We also perturbed the bridge at known times (cutting supports, adding weights etc) so we know when the anomalies should appear. John. On Mon, Sep 22, 2014 at 4:57 PM, Matthew Taylor <[email protected]<mailto:[email protected]>> wrote: I have more tutorials planned, but I'd like some help deciding which to do first. Please answer this 1-question poll: https://docs.google.com/forms/d/1GBYWg_-LIaYmOz9EJ5LbFo6N2ot1xv9AA22gaNdENs0/viewform?usp=send_form Thanks, --------- Matt Taylor OS Community Flag-Bearer Numenta ________________________________ The material in this message is private and may contain Protected Healthcare Information (PHI). If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
