Default: Tags: - Key: owner Value: owner-default Predictor: MaxAge: 604800 # one week PerformAutoML: False PerformHPO: False AlgorithmArn: arn:aws:forecast:::algorithm/NPTS ForecastHorizon: 72 FeaturizationConfig: ForecastFrequency: D Tags: - Key: solution_predictor Value: predictor State: Present - Key: solution_predictor_absent State: Absent Forecast: ForecastTypes: - "0.10" - "0.50" - "0.90" Tags: - Key: solution_forecast Value: forecast State: Present - Key: solution_forecast_absent State: Absent DatasetGroup: Domain: RETAIL Tags: - Key: solution_dsg Value: dsg - Key: solution_dsg_absent State: Absent 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 - Domain: RETAIL DatasetType: RELATED_TIME_SERIES DataFrequency: D TimestampFormat: yyyy-MM-dd Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: price AttributeType: float - Domain: RETAIL DatasetType: ITEM_METADATA Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: category AttributeType: string - AttributeName: brand AttributeType: string 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: 72 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: 72 ForecastTypes: - "0.50" - "0.60" - "0.70" TrainingParameters: context_length: "63" epochs: "250" learning_rate: "0.014138165570842774" learning_rate_decay: "0.5" likelihood: student-t max_learning_rate_decays: "0" num_averaged_models: "1" num_cells: "40" num_layers: "2" prediction_length: "72" Forecast: ForecastTypes: - "0.50" - "0.60" - "0.70" Override: DatasetGroup: Domain: WEB_TRAFFIC Datasets: - Domain: WEB_TRAFFIC DatasetType: TARGET_TIME_SERIES DataFrequency: 15min TimestampFormat: yyyy-MM-dd HH:mm:ss Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: demand AttributeType: float - Domain: WEB_TRAFFIC DatasetType: RELATED_TIME_SERIES DataFrequency: 15min TimestampFormat: yyyy-MM-dd HH:mm:ss Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: pageloadtime AttributeType: float - Domain: RETAIL DatasetType: ITEM_METADATA Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: category AttributeType: string Predictor: MaxAge: 604800 # one week PerformAutoML: False PerformHPO: False AlgorithmArn: arn:aws:forecast:::algorithm/NPTS ForecastHorizon: 72 FeaturizationConfig: ForecastFrequency: D Forecast: ForecastTypes: - "0.10" - "0.50" - "0.90" Mismatch: DatasetGroup: Domain: WEB_TRAFFIC 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 PerformAutoML: False PerformHPO: False AlgorithmArn: arn:aws:forecast:::algorithm/NPTS ForecastHorizon: 72 FeaturizationConfig: ForecastFrequency: D Forecast: ForecastTypes: - "0.10" - "0.50" - "0.90" # Some YAML references for testing __Testing__: DataTypes: TargetTimeSeries: &TargetTimeSeries TARGET_TIME_SERIES RelatedTimeSeries: &RelatedTimeSeries RELATED_TIME_SERIES ItemMetadata: &ItemMetadata ITEM_METADATA TimestampFormats: YMD: &YMD yyyy-MM-dd YMDHMS: &YMDHMS yyyy-MM-dd HH:mm:ss Domains: Retail: &Retail RETAIL InventoryPlanning: &InventoryPlanning INVENTORY_PLANNING EC2Capacity: &EC2Capacity EC2_CAPACITY WorkForce: &WorkForce WORK_FORCE WebTraffic: &WebTraffic WEB_TRAFFIC Metrics: &Metrics METRICS Custom: &Custom CUSTOM DataFrequency: Yearly: &Yearly Y Monthly: &Monthly M Weekly: &Weekly W Daily: &Daily D Hourly: &Hourly H HalfHourly: &HalfHourly "30min" QuarterHourly: &QuarterHourly "15min" SixthHourly: &SixthHourly "10min" TwelfthHourly: &TwelfthHourly "5min" Minutely: &Minutely "1min" ForecastDefaults: &ForecastDefaults ForecastTypes: - "0.10" - "0.50" - "0.90" PredictorDefaults: &PredictorDefaults MaxAge: 604800 # one week PerformAutoML: True ForecastHorizon: 30 FeaturizationConfig: ForecastFrequency: D RetailTargetTimeSeriesSchema: &RetailTargetTimeSeriesSchema Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: demand AttributeType: float RetailRelatedTimeSeriesSchema: &RetailRelatedTimeSeriesSchema Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: price AttributeType: float RetailItemMetadataSchema: &RetailItemMetadataSchema Attributes: - AttributeName: item_id AttributeType: string - AttributeName: category AttributeType: string - AttributeName: brand AttributeType: string RetailTargetTimeSeries: &RetailTargetTimeSeries Domain: *Retail DatasetType: *TargetTimeSeries DataFrequency: *Daily TimestampFormat: *YMD Schema: *RetailTargetTimeSeriesSchema Tags: - Key: type Value: target RetailRelatedTimeSeries: &RetailRelatedTimeSeries Domain: *Retail DatasetType: *RelatedTimeSeries DataFrequency: *Daily TimestampFormat: *YMD Schema: *RetailRelatedTimeSeriesSchema Tags: - Key: type Value: related RetailItemMetadata: &RetailMetadata Domain: *Retail DatasetType: *ItemMetadata DataFrequency: *Daily Schema: *RetailItemMetadataSchema Tags: - Key: type Value: metadata RetailDemandTRM: DatasetGroup: Domain: *Retail Datasets: - *RetailMetadata - *RetailRelatedTimeSeries - *RetailTargetTimeSeries Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandTM: DatasetGroup: Domain: *Retail Datasets: - *RetailTargetTimeSeries - *RetailMetadata Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandTR: DatasetGroup: Domain: *Retail Datasets: - *RetailRelatedTimeSeries - *RetailTargetTimeSeries Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandT: DatasetGroup: Domain: *Retail Datasets: - *RetailTargetTimeSeries Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandForgottenDatasets: DatasetGroup: Domain: *Retail Datasets: - *RetailRelatedTimeSeries Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandDuplicateDatasets: DatasetGroup: Domain: *Retail Datasets: - *RetailTargetTimeSeries - *RetailTargetTimeSeries Forecast: *ForecastDefaults Predictor: *PredictorDefaults RetailDemandTNPTS: DatasetGroup: Domain: *Retail Datasets: - *RetailTargetTimeSeries Predictor: ForecastHorizon: 72 MaxAge: 1 FeaturizationConfig: ForecastFrequency: D AlgorithmArn: arn:aws:forecast:::algorithm/NPTS Forecast: ForecastTypes: - "0.01" - "0.50" - "0.99" DatasetsFromRetailDemandTRMProphet: DatasetGroup: Domain: *Retail Datasets: From: RetailDemandTRMProphet Predictor: AlgorithmArn: arn:aws:forecast:::algorithm/CNN-QR ForecastHorizon: 72 FeaturizationConfig: ForecastFrequency: D Featurizations: - AttributeName: price FeaturizationPipeline: - FeaturizationMethodName: filling FeaturizationMethodParameters: futurefill: max middlefill: median backfill: median Forecast: ForecastTypes: - "0.01" - "0.50" - "0.99" RetailDemandTRMProphet: Tags: - Key: owner Value: finance DatasetGroup: Domain: *Retail Tags: - Key: contact Value: username - Key: owner Value: marketing Datasets: - *RetailMetadata - *RetailRelatedTimeSeries - *RetailTargetTimeSeries Predictor: AlgorithmArn: arn:aws:forecast:::algorithm/Prophet ForecastHorizon: 72 FeaturizationConfig: ForecastFrequency: D Featurizations: - AttributeName: price FeaturizationPipeline: - FeaturizationMethodName: filling FeaturizationMethodParameters: futurefill: max middlefill: median backfill: median Forecast: ForecastTypes: - "0.01" - "0.50" - "0.99" RetailDimensions: DatasetGroup: Domain: RETAIL Datasets: - Domain: RETAIL DatasetType: TARGET_TIME_SERIES DataFrequency: 5min TimestampFormat: yyyy-MM-dd HH:mm:ss Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: timestamp AttributeType: timestamp - AttributeName: demand AttributeType: float - AttributeName: location AttributeType: string - Domain: RETAIL DatasetType: ITEM_METADATA Schema: Attributes: - AttributeName: item_id AttributeType: string - AttributeName: brand AttributeType: string Predictor: AlgorithmArn: arn:aws:forecast:::algorithm/Prophet MaxAge: 604800 # one week ForecastHorizon: 96 FeaturizationConfig: ForecastFrequency: 5min ForecastDimensions: ["location"] Forecast: ForecastTypes: - "0.10" - "0.50" - "0.90"