Example Model Params

This raw model params file is used in the Quick Start. These parameters are used to create an HTMPredictionModel, which will create an HTM with specified encoders and connect them to both a SpatialPooler and BacktrackingTM (or BacktrackingTMCPP if modelParams.tmParams.temporalImp==cpp).

To see detailed algorithm parameters for the algorithms see their API documentation at:

• SpatialPooler
• BacktrackingTM
• SDRClassifier

# Type of model that the rest of these parameters apply to.
model: HTMPrediction

# Version that specifies the format of the config.
version: 1

# The section "aggregationInfo" specifies what field to aggregate with which
# aggregation method.
#
# Example of how to aggregate the field "consumption" with the method "mean"
# and the field "gym" with the method "first". Both field will be
# aggregated over a period of 1h 15m, according to their respective
# aggregation methods.
#
#   aggregationInfo:
#     fields:
#     - [consumption, sum]
#     - [gym, first]
#     minutes: 15
#     hours: 1
#
# See nupic.data.aggregator for more info about supported aggregation methods.
aggregationInfo:
  # "fields" should be a list of pairs. Each pair is a field name and an
  # aggregation function (e.g. sum). The function will be used to aggregate
  # multiple values of this field over the aggregation period.
  fields:
  - [consumption, mean]
  # If a time unit is not listed, 0 will be its default value.
  microseconds: 0
  milliseconds: 0
  minutes: 0
  months: 0
  seconds: 0
  hours: 1
  days: 0
  weeks: 0
  years: 0

predictAheadTime: null

# Parameters of the model to be created.
modelParams:

  # The type of inference that this model will perform.
  # Supported values are :
  # - TemporalNextStep
  # - TemporalClassification
  # - NontemporalClassification
  # - TemporalAnomaly
  # - NontemporalAnomaly
  # - TemporalMultiStep
  # - NontemporalMultiStep
  inferenceType: TemporalMultiStep

  # Parameters of the Sensor region
  sensorParams:
    # Sensor diagnostic output verbosity control:
    # - verbosity == 0: silent
    # - verbosity in [1 .. 6]: increasing level of verbosity
    verbosity: 0

    # List of encoders and their parameters.
    encoders:
      consumption:
        fieldname: consumption
        name: consumption
        resolution: 0.88
        seed: 1
        type: RandomDistributedScalarEncoder
      timestamp_timeOfDay:
        fieldname: timestamp
        name: timestamp_timeOfDay
        timeOfDay: [21, 1]
        type: DateEncoder
      timestamp_weekend:
        fieldname: timestamp
        name: timestamp_weekend
        type: DateEncoder
        weekend: 21

    # The "sensorAutoReset" specifies the period for automatically generated
    # resets from a RecordSensor.
    #
    # If None, disable automatically generated resets. Also disable for all
    # values that evaluate to 0. Example:
    #   sensorAutoReset: null
    #
    #
    # Valid keys for the "sensorAutoReset" option:
    #   sensorAutoReset:
    #    days: <int>
    #     hours: <int>
    #     minutes: <int>
    #     seconds: <int>
    #     milliseconds: <int>
    #     microseconds: <int>
    #     weeks: <int>
    #
    # Example for an automated reset every 1.5 days:
    #   sensorAutoReset:
    #     days: 1
    #     hours: 12
    #
    sensorAutoReset: null


  # Controls whether the Spatial Pooler (SP) region is enabled.
  spEnable: true

  # Parameters of the SP region. For detailed descriptions of each
  # parameter, see the API docs for
  # nupic.algorithms.spatial_pooler.SpatialPooler. Note that the OPF
  # will only create one-dimensional input and spatial pooling
  # structures, so during SP creation `columnCount` translates to
  # `columnDimensions=(columnCount,)` and
  # `inputDimensions=(inputWidth,)`.
  spParams:
    inputWidth: 946
    columnCount: 2048
    spVerbosity: 0
    spatialImp: cpp
    globalInhibition: 1
    localAreaDensity: -1.0
    numActiveColumnsPerInhArea: 40
    seed: 1956
    potentialPct: 0.85
    synPermConnected: 0.1
    synPermActiveInc: 0.04
    synPermInactiveDec: 0.005
    boostStrength: 3.0

  # Controls whether the Temporal Memory (TM) region is enabled.
  tmEnable: true

  # Parameters of the TM region. For detailed descriptions of each
  # parameter, see the API docs for
  # nupic.algorithms.backtracking_tm.BacktrackingTM.
  tmParams:
    verbosity: 0
    columnCount: 2048
    cellsPerColumn: 32
    inputWidth: 2048
    seed: 1960
    temporalImp: cpp
    newSynapseCount: 20
    initialPerm: 0.21
    permanenceInc: 0.1
    permanenceDec: 0.1
    maxAge: 0
    globalDecay: 0.0
    maxSynapsesPerSegment: 32
    maxSegmentsPerCell: 128
    minThreshold: 12
    activationThreshold: 16
    outputType: normal
    pamLength: 1

  # Classifier parameters. For detailed descriptions of each parameter, see
  # the API docs for nupic.algorithms.sdr_classifier.SDRClassifier.
  clParams:
    verbosity: 0
    regionName: SDRClassifierRegion
    alpha: 0.1
    steps: '1,5'
    maxCategoryCount: 1000
    implementation: cpp

  # If set, don't create the SP network unless the user requests SP metrics.
  trainSPNetOnlyIfRequested: false