Hi, Subutai, 

Thanks for the detailed reply. Really appreciate it! :)

Regards, 
Omair S


> On Jul 28, 2014, at 9:42 PM, Subutai Ahmad <[email protected]> wrote:
> 
> Hi Omair,
> 
> Thanks!  We have only done rough comparisons so far with standard models. One 
> problem has been the lack of good labeled datasets for streaming anomaly 
> detection (which is the specific application we've tuned for). We have been 
> accumulating some real world data and hope to put together a dataset for more 
> rigorous testing. I hope to release that soon. If you know of some good 
> datasets focused on streaming data, that would be really helpful - we could 
> add them to the mix.
> 
> In the meantime I can make some high level observations:
> 
> 1) HTM's are not more computationally efficient. There's a lot more going on. 
> It is reasonably fast - it takes about 25 msecs on my laptop to process one 
> data point. MA models are probably an order of magnitude faster though.
> 
> 2) HTM's can learn many different patterns, not just one pattern. It can also 
> make multiple predictions at each time step. With the likelihood code it can 
> also learn high level statistics about the data and thus can work with highly 
> unpredictable data.
> 
> 3) Anecdotally, with Grok, we've seen many examples of HTM anomaly detection 
> that probably would not have been caught by MA models.
> 
> 4) I did do a comparison of HTM prediction against ARIMA (I believe ARIMA is 
> a superset of Holt-Winters).  HTM did a lot better on one energy dataset. 
> There was a discussion of it here:
> 
> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/2013-September/001411.html
> 
> Hope this helps!
> 
> --Subutai
> 
> 
> 
>> On Fri, Jul 25, 2014 at 10:22 AM, Omair Shafi <[email protected]> wrote:
>> Hi again,
>> 
>> I've been fooling around the Anomaly detection sample code by Subutai using 
>> TemporalAnomaly, which seems absolutely awesome! I just wanted to know how 
>> it compared with standard models for anomaly detection like Holt Winters, 
>> other variations of Moving Average and the lot. Does it score higher on 
>> accuracy? Or is it more computationally efficient? Or maybe it can learn 
>> more than one pattern? 
>> 
>> Thanks!
>> 
>> Regards, 
>> Omair S
>> 
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