You will likely need to run a swarm. In particular, you should give it the option to include a time-of-day field and make sure it can select a very fine encoding for that field. Also the standard permute options would be a good idea.
On Tue, May 13, 2014 at 12:22 PM, Matthew Taylor <[email protected]> wrote: > Can you paste the model params you are using? Looking at the chart, my > guess is that it's not being processed as temporal data. Are you using > a timestamp? Seeing your input CSV for the swarm (or at least a part > of it) would be helpful, too. > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Tue, May 13, 2014 at 12:13 PM, Daniel Cohen <[email protected]> > wrote: > > This is a data set taken from google analytics - it is almost 2 years of > web > > traffic data by date hour - that's about 4000 data points. > > > > I ran through the same process I used for the sine wave prediction > tutorial > > except I added more prediction steps. The attached .png is a zoom in of > the > > plot. Even the 1 step prediction is disappointing and I'd expect better > > after 4000 data points. The 10 step prediction is almost wholly > unreliable > > and anything beyond that is useless. Sure the predictions are within the > > right range of points but you couldn't base anything useful off them. > They > > don't even seem to have picked up on the hourly modulation throughout a > day. > > > > Is there any way to improve the prediction quality without simply using > more > > data points? > > > > _______________________________________________ > > 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 >
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