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
>>
>

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