For those of you concerned about why NuPIC is not doing well
predicting a simple sine wave, Jeff has explained this:

http://lists.numenta.org/pipermail/nupic_lists.numenta.org/2013-June/000327.html
---------
Matt Taylor
OS Community Flag-Bearer
Numenta


On Sat, Apr 26, 2014 at 6:31 PM, Pedro Tabacof <[email protected]> wrote:
> As always Ritchie's results are very interesting.
>
> I have to point out that if Nupic cannot make a better prediction than a
> simple time-series baseline (just forwarding the last output), then it is of
> no use for time-series forecasting.
>
> I think we should probe further to understand what is causing this, because
> I'm sure Nupic is better than this. From my own experience with time-series
> forecasting using Nupic, it should not be worst than a baseline (and should
> be close to state of the art algorithns).
>
> Pedro.
>
> Em 26/04/2014 20:44, "Marek Otahal" <[email protected]> escreveu:
>
>
>>
>> Hi Ritchie,
>>
>>
>> On Sat, Apr 26, 2014 at 8:25 PM, Ritchie Lee <[email protected]>
>> wrote:
>>>
>>> Hi friends of NuPIC,
>>>
>>> ......However, looking closely why does the anomaly score only spike at
>>> the end of the first and second anomalies?  Why not spike at the beginning
>>> (at least) and throughout the anomaly?
>>
>>
>> Just to check, your anomalies are introduced at {6000, 6500, 7000, 7500)
>> for about 100 steps, right?
>> Looks like (un)lucky coincidence to me, but it seems at times 6000, 6500
>> you introduce the anomaly "at the middle of the wave", where sin(x)=0, so
>> the first first anomaly step is actually not an anomaly, the for 99 steps
>> same value is not an anomaly either,
>> only the jump at the end (from 0 to -1) triggers an anomaly. (#1)
>>
>> At 7000, 7500 thhe introduced anomaly might have cought the predicted sine
>> at a different phase, triggering anomaly right off (and multiple times?)
>> ...if this is true, Nupic already outsmarted us! :)
>>
>>>
>>> Also, why is the prediction so good, and residual so small at the
>>> beginning?
>>
>>
>> Answer to this can be found in Nick Mitri's email: [nupic-discuss]
>> Confusion about shifted predictions
>> (#2) At the beginning, almost all predictions fail, and CLA returns
>> last-seen value. In your example you have 1000 steps per 5 "full sines",
>> thus the resolution is pretty high, change is small -> residual is actually
>> better at the beginning
>> than after learning :)
>>
>>
>> It would be interesting to see a rerun of your experiment with much
>> smaller resolution (100, 10 steps per period?).
>>
>> My question:
>>
>> is the "perfect predictor for unlearned" on high resolutions actually a
>> feature, or (misleading) bug? (#3)
>>
>> Also, anomaly is "actual(T)-predicted(T-1)/..."; now, what is fed as
>> input(i) when learning=OFF? actual(i), or predicted(i-1)? I think it's
>> actual(i) but no weight changes are stored. But for our example, it should
>> be predicted(i-1).
>> Example: sine; introduce anomaly as a line at level 0, at the phase where
>> sine and 0 meet. Then as in #1 the 1st point is not anomaly, on step 2, the
>> context is unknown (new), so prediction would give 0 according to #2
>> (actual(i-1)) which leads
>> to 0 anomaly score! (as "bug" in #3).
>>
>>
>> Cheers, Mark
>> --
>> Marek Otahal :o)
>>
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>>
>
>
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