Good point Matt, Phil , If you are using the Scalar encoder, check the max val on the Scalar encoder. If it 100 then the scalar encoder output is the same for any value about 100. So the prediction will be incorrect as it sees several possible next values for the same encoded o/p for anything greater than100
Chandan On Tue, Aug 25, 2015 at 8:50 AM, Matthew Taylor <[email protected]> wrote: > Phil, > > What NuPIC interface are you using for your experiment? Seems like you > are using the Network API. If you are creating a model with model > parameters that include a maxValue of 100, any data you pass in that > is above that threshold will be treated as if it were the maxValue of > 100. That might explain the results you are seeing. > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Fri, Aug 21, 2015 at 6:16 PM, Phil iacarella <[email protected]> > wrote: > > I'm attempting to do spatial anomaly detection. > > > > I've setup a file with a list of 1000 entries of random > numbers > > between 1 and 100. Because the numbers are randomly generated I don't > care > > about data sequence only its pooled content. So, I've created the TP with > > only 1 cell per column - not caring about sequence. > > > > I execute a run with anomaly scores. Everything behaves as expected, at > > first lots of anomalies and then it settles down little to zero > anomalies. > > > > I then modify the data file and insert just a few numbers larger than 100 > > (i.e. 115 , 135) towards the end of the file and not consecutively. Again > > everything works as expect with the exception that the anomaly scores do > not > > occur with the aberrant numbers (115, 135). The high anomaly scores > always > > appear with the subsequent numbers - both the subsequent and the > following > > subsequent number have high scores. > > > > If I create another hierarchy and feed the output of the first hierarchy > > into the second hierarchy I get a more stable low anomaly scores of 0.0 > (as > > I should) and the aberrant numbers still bring out high scores ( .95) but > > now they seem to be 2 and 3 steps behind - the first high score appears 2 > > steps after the aberrant number. > > > > Is this correct behavior? Why is the bursting behavior delayed? > > > > Should I be using the Spatial Pooler Anomaly detection? If so, please > point > > to some example code. > > > > Thanks > > > > Phil > > > > > > -- Regards Chandan Maruthi
