Casper, have you seen this? It explains how our anomaly "likelihood" code works, which is something like a moving average (but a bit more).
- https://www.youtube.com/watch?v=nVCKjZWYavM --------- Matt Taylor OS Community Flag-Bearer Numenta On Mon, Dec 21, 2015 at 7:40 AM, Cas <[email protected]> wrote: > Hello NuPIC, > > The wiki page on anomaly scores mentions that some cases call for the use of > a moving average on the raw anomaly score[1]. However, it does not mention > examples in which this is used. I would like to know more about applications > using a moving average of the anomaly score. > > I'm experimenting with custom generated datasets. In the datasets that I > added randomized noise to, the predictions are impressive, but sometimes > seem 'too perfect'. For example, the prediction will be a little off, but it > will follow the spikes caused by noisiness impeccably. > > By contrast, a dataset without noise and a seemingly clearcut pattern will > result in a gradual breakdown of the prediction, where it will start > switching values in consecutive steps, or spiking to an extreme prediction > in the middle of following the pattern accurately. > > With regards, > > Casper Rooker > [email protected] > > [1]: > https://github.com/numenta/nupic/wiki/Anomaly-Detection-and-Anomaly-Scores#results
