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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