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
