Pedro, This kind of experimentation is great! Please keep us posted with your results.
Thanks, Chetan On Thu, Oct 3, 2013 at 6:59 AM, Pedro Tabacof <[email protected]> wrote: > Hello, > > I've been working with an energy competition dataset [1] and I've been > experimenting with some different ways to predict many steps ahead (I have > to predict 31 different energy loads for the whole month). This led me to > some questions: > > 1) Has anyone tried feeding one-step classifier predictions back to the > input? This can be done easily by hand but I'm not sure if this is a good > idea for many steps prediction. > > 2) Does "disableLearning" also turn off classifier learning? If not, how > do I do it? > > 3) Is "finishLearning" deprecated? I tried using it but I got an error > message. > > 4) Is it possible run swarming within the Vagrant VM? What about Cerebro? > > On a side note, so far I have achieved 3.3% MAPE on the test data, which > would put me among the top 10 competitors (out of 26), with pretty much the > basic NuPIC configuration, very similar to the hotgym example. > > I have experimented with 31-step predictions and 1,2,3,...,31 predictions, > but this was too slow and didn't improve the results. When I finish testing > all my ideas, I will post my results and experience here. > > Pedro. > > [1] http://neuron.tuke.sk/competition/index.php > -- > Pedro Tabacof, > Unicamp - Eng. de Computação 08. > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > >
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