Hi Michael, Afaik, the "Anomaly" class is what you are looking for, just that it tracks the moving average of accuracy or maybe the inverse (anomaly). You could in any case have a look at that code to see if it either does what you are looking for or can be "adapted" to do more of what you're looking for.
Also afaik, the steps will "overwrite" when that point in the cycle is reached again (so every 500 steps a new prediction quality is estimated - if 500-steps is one of the step configurations). Correct me if I'm wrong someone? David On Wed, Mar 4, 2015 at 6:21 PM, Michael Roy Ames via nupic < [email protected]> wrote: > > > ---------- Forwarded message ---------- > From: Michael Roy Ames <[email protected]> > To: NuPIC Mailing List <[email protected]> > Cc: > Date: Wed, 04 Mar 2015 16:08:38 -0800 > Subject: Prediction. Several steps. Future or past. > NuPIC list: > > "Predictions in an HTM region can be for several time steps into the > future" - according to the HTM White paper. > > Question 1: Is there a NuPIC code that does prediction for the next n time > steps? > > Question 2: Is there NuPIC code that keeps activation history such that > one could access the last 15 or 20 sets of active cells? > > I'm interested in making NuPIC learn and recognize temporal sequences of > data, and want to limit the amount of additional code I have to write to > get this done. So, I'd rather use existing NuPIC functionality that works > instead of writing algorithm that might duplicate something already in > place. The sequences may be long (500 steps) or short (20 steps). The > one-step predictions I've found in NuPIC examples need extra code to be > written to 'remember' the predictions and how many predictions in-a-row > have been correct, each additional successful prediction lending greater > confidence to the data recognition. > > Question 3: Is there code that does this already (successful prediction > tracking), or will I have to write it? > > MRA > > > > > -- *We find it hard to hear what another is saying because of how loudly "who one is", speaks...*
