We are continuing this conversation on Gitter: https://gitter.im/numenta/public/archives/2015/11/02 --------- Matt Taylor OS Community Flag-Bearer Numenta
On Mon, Nov 2, 2015 at 12:08 PM, Cas <[email protected]> wrote: > hey Matt, > > I don't have access to my machine right now, but I've checked out the > metrics data table in a db gui and I recall seeing all null values in the > anomaly scores columns. I think the total amount of recorded data points is > around 230000 (it's the default set from the tutorial). I'll double check > tomorrow morning, it would definitely be silly if that was it! > > Meanwhile I've tried to track down the code responsible for sending the data > into HTM Engine. The fact that I'm unfamiliar with python complicates this, > though. I'm thinking maybe anomaly_service.py or a file in model_swapper > could tell me more? In terms of configs I was thinking model checkpoints > might not be working right, even though I'm not sure what that does :) > > > > Met vriendelijke groet, > > Casper Rooker > [email protected] > > On Mon, Nov 2, 2015 at 4:30 PM, Matthew Taylor <[email protected]> wrote: >> >> Cas, >> >> You won't see an anomaly score out of the HTM Engine until it has seen >> 500 data points. Has it seen that much data yet? >> >> --------- >> Matt Taylor >> OS Community Flag-Bearer >> Numenta >> >> >> On Mon, Nov 2, 2015 at 4:25 AM, Cas <[email protected]> wrote: >> > As I said I'm trying out the HTM engine traffic tutorial where all the >> > model >> > params are generated automatically when the client starts offering data >> > to >> > the HTTP API. >> > >> > Now, I don't know exactly how to interpret the metric records, but I can >> > at >> > least tell that the inferencetype is what it should be. >> > >> > So I've concluded that part of the tutorial that runs the data through >> > HTM >> > Engine probably isn't doing it's job. The logs in supervisord tell me >> > all >> > the services are working fine (though I had to manually open the port >> > for >> > htmengine:model_scheduler). I would assume that the traffic tutorial is >> > configured to do postprocessing, based on the HTM engine's README. >> > >> > It's probably a silly oversight on my part, but right now I just dont >> > know >> > what to make of this. Hope someone can help out! >> > >> > Kind regards, >> > >> > Casper Rooker >> > [email protected] >> > >> > P.S.: >> > >> > One such model params record in the metrics table: >> > >> > { >> > "inferenceArgs": { >> > "predictionSteps": [ >> > 1 >> > ], >> > "predictedField": "c1", >> > "inputPredictedField": "auto" >> > }, >> > "modelConfig": { >> > "aggregationInfo": { >> > "seconds": 0, >> > "fields": [], >> > "months": 0, >> > "days": 0, >> > "years": 0, >> > "hours": 0, >> > "microseconds": 0, >> > "weeks": 0, >> > "minutes": 0, >> > "milliseconds": 0 >> > }, >> > "model": "CLA", >> > "version": 1, >> > "predictAheadTime": null, >> > "modelParams": { >> > "sensorParams": { >> > "verbosity": 0, >> > "encoders": { >> > "c0_dayOfWeek": null, >> > "c0_timeOfDay": { >> > "fieldname": "c0", >> > "timeOfDay": [ >> > 21, >> > 9.49122334747737 >> > ], >> > "type": "DateEncoder", >> > "name": "c0" >> > }, >> > "c1": { >> > "name": "c1", >> > "resolution": 0.7017543859649122, >> > "seed": 42, >> > "fieldname": "c1", >> > "type": "RandomDistributedScalarEncoder" >> > }, >> > "c0_weekend": null >> > }, >> > "sensorAutoReset": null >> > }, >> > "clEnable": false, >> > "spParams": { >> > "columnCount": 2048, >> > "spVerbosity": 0, >> > "maxBoost": 1.0, >> > "spatialImp": "cpp", >> > "inputWidth": 0, >> > "synPermInactiveDec": 0.0005, >> > "synPermConnected": 0.1, >> > "synPermActiveInc": 0.0015, >> > "seed": 1956, >> > "numActiveColumnsPerInhArea": 40, >> > "globalInhibition": 1, >> > "potentialPct": 0.8 >> > }, >> > "trainSPNetOnlyIfRequested": false, >> > "clParams": { >> > "alpha": 0.035828933612158, >> > "clVerbosity": 0, >> > "steps": "1", >> > "regionName": "CLAClassifierRegion" >> > }, >> > "tpParams": { >> > "columnCount": 2048, >> > "activationThreshold": 13, >> > "pamLength": 3, >> > "cellsPerColumn": 32, >> > "permanenceInc": 0.1, >> > "minThreshold": 10, >> > "verbosity": 0, >> > "maxSynapsesPerSegment": 32, >> > "outputType": "normal", >> > "globalDecay": 0.0, >> > "initialPerm": 0.21, >> > "permanenceDec": 0.1, >> > "seed": 1960, >> > "maxAge": 0, >> > "newSynapseCount": 20, >> > "maxSegmentsPerCell": 128, >> > "temporalImp": "cpp", >> > "inputWidth": 2048 >> > }, >> > "anomalyParams": { >> > "anomalyCacheRecords": null, >> > "autoDetectThreshold": null, >> > "autoDetectWaitRecords": 5030 >> > }, >> > "spEnable": true, >> > "inferenceType": "TemporalAnomaly", >> > "tpEnable": true >> > } >> > }, >> > "inputRecordSchema": [ >> > [ >> > "c0", >> > "datetime", >> > "T" >> > ], >> > [ >> > "c1", >> > "float", >> > "" >> > ] >> > ] >> > } >> > >> > On Mon, Nov 2, 2015 at 12:14 PM, Wakan Tanka <[email protected]> wrote: >> >> >> >> On 11/02/2015 11:31 AM, Cas wrote: >> >>> >> >>> Hello NuPIC, >> >>> >> >>> I was trying out the HTM engine traffic tutorial today and I got it >> >>> running. Unfortunately the anomaly score is 'none' for all data >> >>> points. >> >>> >> >>> Do you have any suggestions on how to troubleshoot this? >> >>> >> >>> I know all the services are running, from the looks of the supervisord >> >>> interface. I'd like to see how the data points are being offered to >> >>> the >> >>> HTM engine for starters, I'm just not sure how to do that. >> >>> >> >>> Kind regards, >> >>> >> >>> Casper Rooker >> >>> [email protected] <mailto:[email protected]> >> >> >> >> >> >> Hello Casper, >> >> >> >> Be sure that you've set "inferenceType": "TemporalAnomaly" if you have >> >> "inferenceType": "TemporalMultiStep" then you are unable to get anomaly >> >> score just predictions. >> >> >> >> regards >> >> >> >> Wakan Tanka >> >> >> > >> >
