Subutai & Matt
That makes sense, the transitions are what is anomalous and not the
data. So I think my setup is correct.
FYI: I am using the Network API and also using the
RandomDistributedScalarEncoder with a resolution of 1.0 and all other params
are defaults.
Thanks
-Phil
> On Aug 25, 2015, at 11:05 AM, Subutai Ahmad <[email protected]> wrote:
>
> Hi Phil,
>
> I echo Matt's point about the encoder - it's important to have min/max set
> correctly. However even with the correct encoder you would still get the
> result you report. The anomaly score in NuPIC is only defined with respect
> to temporal memory and sequences. As you mentioned, there's no currently
> concept of spatial-only anomaly. The anomaly score is computed with respect
> to each transition in the sequence.
>
> In your example, it is learning common sequences between the numbers
> (randomly generated here). Given the past distribution, the transition from
> 57 to 115 is anomalous, but so is the transition from 115 to 36. It has never
> seen a jump down from 115 to 36. Hence two transitions where the anomaly
> score is 1.0
>
> --Subutai
>
> On Tue, Aug 25, 2015 at 8:50 AM, Matthew Taylor <[email protected]
> <mailto:[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]
> <mailto:[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
> >
> >
>
>
