taxi:
  DatasetGroup:
    Domain: CUSTOM

  Datasets:
    - Domain: CUSTOM
      DatasetType: TARGET_TIME_SERIES
      DataFrequency: H
      TimestampFormat: yyyy-MM-dd HH:mm:ss
      GeolocationFormat: LAT_LONG
      TimeZone: America/New_York
      Schema:
        Attributes:
          - AttributeName: timestamp
            AttributeType: timestamp
          - AttributeName: item_id
            AttributeType: string
          - AttributeName: target_value
            AttributeType: float
          - AttributeName: geolocation
            AttributeType: geolocation
    - Domain: CUSTOM
      DatasetType: ITEM_METADATA
      Schema:
        Attributes:
          - AttributeName: item_id
            AttributeType: string
          - AttributeName: borough
            AttributeType: string
          - AttributeName: taxi_zone
            AttributeType: string
          - AttributeName: taxi_service_zone
            AttributeType: string

  Predictor:
    MaxAge: 604800  # one week
    AlgorithmArn: arn:aws:forecast:::algorithm/Deep_AR_Plus
    ForecastHorizon: 168
    FeaturizationConfig:
      ForecastFrequency: H
      ForecastDimensions: ["geolocation"]
      Featurizations:
        - AttributeName: target_value
          FeaturizationPipeline:
            - FeaturizationMethodName: filling
              FeaturizationMethodParameters:
                aggregation: sum
                backfill: zero
                frontfill: none
                middlefill: zero
    InputDataConfig:
      SupplementaryFeatures:
        - Name: holiday
          Value: US
        - Name: weather
          Value: "true"
    EvaluationParameters:
      NumberOfBacktestWindows: 3
      BackTestWindowOffset: 168
    ForecastTypes:
      - "0.50"
      - "0.60"
      - "0.70"
    TrainingParameters:
      context_length: "63"
      epochs: "250"
      learning_rate: "0.014138165570842774"
      learning_rate_decay: "0.5"
      likelihood: negative-binomial
      max_learning_rate_decays: "0"
      num_averaged_models: "1"
      num_cells: "40"
      num_layers: "2"

  Forecast:
    ForecastTypes:
      - "0.50"
      - "0.60"
      - "0.70"

Default:
  DatasetGroup:
    Domain: RETAIL

  Datasets:
    - Domain: RETAIL
      DatasetType: TARGET_TIME_SERIES
      DataFrequency: D
      TimestampFormat: yyyy-MM-dd
      Schema:
        Attributes:
          - AttributeName: item_id
            AttributeType: string
          - AttributeName: timestamp
            AttributeType: timestamp
          - AttributeName: demand
            AttributeType: float

  Predictor:
    MaxAge: 604800  # one week
    AlgorithmArn: arn:aws:forecast:::algorithm/ARIMA
    ForecastHorizon: 30
    FeaturizationConfig:
      ForecastFrequency: D

  Forecast:
    ForecastTypes:
      - "0.10"
      - "0.50"
      - "0.90"