Hi Matt,

I'm wondering whether it is worth expanding critic to handle genre
classification? Modifying the current code to allow for a dataset like
GTZAN (modified through Bob L. Sturm's work) to setup an initial
classifier. For me it sounds like a great way to get NuPIC running
under Windows (I've installed and run tests via VMs and cygwin) and
learning the internals of NuPIC. Does that sounds like a good idea to
pursue?

Regards, Richard.

On Sat, Jul 12, 2014 at 4:59 PM, Matthew Taylor <[email protected]> wrote:
> On Fri, Jul 11, 2014 at 11:04 PM, Alexander Hirner <[email protected]>
> wrote:
>>
>> Great test case. As far as I understood, you build separate models for
>> each frequency bin and aggregate a total anomaly score by an arbitrary
>> number of how many single anomaly score must be above a certain treshold.
>
>
> Correct. And the # of anomalyLikelihood values that cause the trigger is
> configurable, as well as the anomalyLikelihood threshold itself. You can do
> a lot of tuning with these two values, which I haven't done much of yet. I'm
> still trying to find the best parameters for these for the music I'm passing
> in.
>
>>
>> What do you think about dumping all the bins into one TP at once? In that
>> way, the model could also capture covariance between the frequency bins and
>> derive on a conclusion of an aggregate anomaly score on its own.
>
>
> I wouldn't know how to do that. The input bin values would need to be
> converted into SDRs, which is what the SP does. The only time I've ever fed
> data directly into the TP is when my data was already in SDR format (from
> Cortical.IO API).
>
> ---------
> Matt Taylor
> OS Community Flag-Bearer
> Numenta
>
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