There is overfitting in the sense of learning overly specific patterns without generalising. But that's a much broader question than just swarming, and is unsolved.
-f On 13 April 2016 at 05:59, Matthew Taylor <[email protected]> wrote: > Hi Sam. No danger of overfitting with HTM because it is an online learning > system. It changes it's representation of the input space as the temporal > patterns change. Don't think of swarming as a "test set", just think of it > as a data sample to get the right encoding parameters. > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > On Tue, Apr 12, 2016 at 2:20 PM, Samuel O Heiserman < > [email protected]> wrote: > >> Hey Nupic! >> >> I'm wondering: when running data ]through Nupic, should I not run the >> same file to build the model as I did to swarm for the parameters? Since >> the parameters were tuned to that exact data, it seems like a potential >> overfitting risk. The data is a series of control actions of subjects >> playing a simple game. What I'm trying to do is train a model on the >> subject 1's data, save that model and use it to forecast for subjects 1 - >> 20. >> I hope to show that the HTM can learn the individual behavioral >> patterns of a given subject distinct from the others, and I plan to show >> this capacity with a result where the model does well forecasting for all >> subjects, but especially well at forecasting for the subject it was trained >> on. However I wonder if when testing the model on subject 1, I should use >> different subject 1 data than I used to swarm for the parameters. Thanks >> again! >> >> -- Sam >> > > -- Felix Andrews / 安福立 http://www.neurofractal.org/felix/
