Hi, everyone
I use nupic anomaly model to detect the anomaly point from sine data, which is generated in the following way by repeating many times
np.sin(np.linspace(0,3.14*2,100))
The picture below shows very high anomaly_score, where anomaly is computed as follows
from nupic.algorithms import anomaly_likelihood anomaly_score = anomaly_likelihood.AnomalyLikelihood.anomalyProbability(...)
I really don’t understand for such a extremely simple data pattern, nupic still got very high anomaly likelihood after learning many times. Why?
Here is the model param used for anomaly detection in json format.
{
"aggregationInfo": {
"hours": 0,
"microseconds": 0,
"seconds": 0,
"fields": [],
"weeks": 0,
"months": 0,
"minutes": 0,
"days": 0,
"milliseconds": 0,
"years": 0
},
"model": "HTMPrediction",
"version": 1,
"predictAheadTime": null,
"modelParams": {
"sensorParams": {
"verbosity": 0,
"sensorAutoReset": null,
"encoders": {
"value": {
"name": "value",
"resolution": 0.001,
"n": 400,
"seed": 50,
"fieldname": "value",
"w": 21,
"type": "RandomDistributedScalarEncoder"
}
}
},
"anomalyParams": {
"anomalyCacheRecords": null,
"autoDetectThreshold": null,
"autoDetectWaitRecords": 5030
},
"clEnable": true,
"spParams": {
"columnCount": 2048,
"synPermInactiveDec": 0.0005,
"spatialImp": "cpp",
"synPermConnected": 0.2,
"seed": 1956,
"numActiveColumnsPerInhArea": 40,
"globalInhibition": 1,
"inputWidth": 0,
"spVerbosity": 0,
"synPermActiveInc": 0.003,
"potentialPct": 0.8,
"boostStrength": 1
},
"trainSPNetOnlyIfRequested": false,
"clParams": {
"alpha": 0.035828933612158,
"verbosity": 0,
"steps": "1",
"regionName": "SDRClassifierRegion"
},
"inferenceType": "TemporalAnomaly",
"spEnable": true,
"tmParams": {
"columnCount": 2048,
"activationThreshold": 13,
"pamLength": 3,
"cellsPerColumn": 32,
"permanenceDec": 0.1,
"minThreshold": 10,
"inputWidth": 2048,
"maxSynapsesPerSegment": 32,
"outputType": "normal",
"globalDecay": 0.0,
"initialPerm": 0.21,
"newSynapseCount": 20,
"maxAge": 0,
"maxSegmentsPerCell": 128,
"permanenceInc": 0.1,
"temporalImp": "cpp",
"seed": 1960,
"verbosity": 0
},
"tmEnable": true
}
Looking forward to reply!
Thanks