RTT_multivariate_model.yaml

# 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:
  - [RTT, mean]
  - [RSRP,mean]
  - [RSRQ,mean]
  - [RSSI,mean]
  # If a time unit is not listed, 0 will be its default value.
  microseconds: 0
  milliseconds: 0
  minutes: 0
  months: 0
  seconds: 1
  hours: 0
  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:
      RTT:
        fieldname: RTT
        name: RTT
        resolution: 0.88
        seed: 1
        type: RandomDistributedScalarEncoder
      RSRP:
          fieldname: RSRP
          name: RSPP
          resolution: 0.88
          seed: 1
          type: RandomDistributedScalarEncoder
      RSRQ:
        fieldname: RSRQ
        name: RSRQ
        resolution: 0.88
        seed: 1
        type: RandomDistributedScalarEncoder
      RSSI:
        fieldname: RSSI
        name: RSSI
        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