Hi, I am very intrigued by Nupic CLA and its potentials. I was trying to use CLA algorithm to perform anomaly detection. My data set is similar to that of the hotgym example - the usage is high during the day/business hours and low, but never zero, during night/non-business hours (sorry I can’t share my data set). The zero usage means outage and should be considered as an anomaly regardless when it happens. The problem is CLA failed to raise anomaly score when outage/zero usage happening during the non-business hours.
I managed to reproduce the problem using the the hot gym anomaly example. I made following change to "extra/hotgym/rec-center-hourly.csv" 4373,4374c4373,4374 < 12/31/10 1:00,0 < 12/31/10 2:00,0 --- > 12/31/10 1:00,4.9 > 12/31/10 2:00,5 that means zero energy usage during the 1 & 2 AM, which should be abnormal. And corresponding CLA score are 0 (shown below) INFO:__main__:Anomaly detected at [2010-12-31 01:00:00]. Anomaly score: 0.000000. INFO:__main__:Anomaly detected at [2010-12-31 02:00:00]. Anomaly score: 0.000000. When I used 24 “traditional” statistical models, each for an hour of the day, I was able to detect zero usage and report as an anomaly. CLA doesn’t appear to be superior in this case. Can CLA model be tuned to account for scenarios like this? Regards, Tom
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