Defines the modifications that you are making to an attribute for a what-if forecast. For example, you can use this operation to create a what-if forecast that investigates a 10% off sale on all shoes. To do this, you specify "AttributeName": "shoes", "Operation": "MULTIPLY", and "Value": "0.90". Pair this operation with the "TimeSeriesCondition" operation within the "CreateWhatIfForecastRequest$TimeSeriesTransformations" operation to define a subset of attribute items that are modified.

Describes an additional dataset. This object is part of the "DataConfig" object. Forecast supports the Weather Index and Holidays additional datasets.

Provides information about the method used to transform attributes.

Metrics you can use as a baseline for comparison purposes. Use these metrics when you interpret monitoring results for an auto predictor.

An individual metric that you can use for comparison as you evaluate your monitoring results.

Specifies a categorical hyperparameter and it's range of tunable values. This object is part of the "ParameterRanges" object.

Specifies a continuous hyperparameter and it's range of tunable values. This object is part of the "ParameterRanges" object.

The data configuration for your dataset group and any additional datasets.

The destination for an export job. Provide an S3 path, an Identity and Access Management (IAM) role that allows Amazon Forecast to access the location, and an Key Management Service (KMS) key (optional).

Provides a summary of the dataset group properties used in the ListDatasetGroups operation. To get the complete set of properties, call the DescribeDatasetGroup operation, and provide the DatasetGroupArn.

Provides a summary of the dataset import job properties used in the ListDatasetImportJobs operation. To get the complete set of properties, call the DescribeDatasetImportJob operation, and provide the DatasetImportJobArn.

Provides a summary of the dataset properties used in the ListDatasets operation. To get the complete set of properties, call the DescribeDataset operation, and provide the DatasetArn.

The source of your data, an Identity and Access Management (IAM) role that allows Amazon Forecast to access the data and, optionally, an Key Management Service (KMS) key.

An Key Management Service (KMS) key and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key. You can specify this optional object in the "CreateDataset" and "CreatePredictor" requests.

Provides detailed error metrics to evaluate the performance of a predictor. This object is part of the "Metrics" object.

Parameters that define how to split a dataset into training data and testing data, and the number of iterations to perform. These parameters are specified in the predefined algorithms but you can override them in the "CreatePredictor" request.

The results of evaluating an algorithm. Returned as part of the "GetAccuracyMetrics" response.

The ExplainabilityConfig data type defines the number of time series and time points included in "CreateExplainability".

Provides a summary of the Explainability export properties used in the "ListExplainabilityExports" operation. To get a complete set of properties, call the "DescribeExplainabilityExport" operation, and provide the ExplainabilityExportArn.

Provides information about the Explainability resource.

Provides a summary of the Explainability properties used in the "ListExplainabilities" operation. To get a complete set of properties, call the "DescribeExplainability" operation, and provide the listed ExplainabilityArn.

Note: This object belongs to the "CreatePredictor" operation. If you created your predictor with "CreateAutoPredictor", see "AttributeConfig".

Note: This object belongs to the "CreatePredictor" operation. If you created your predictor with "CreateAutoPredictor", see "AttributeConfig".

Provides information about the method that featurizes (transforms) a dataset field. The method is part of the FeaturizationPipeline of the "Featurization" object.

Describes a filter for choosing a subset of objects. Each filter consists of a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the objects that match the statement, respectively. The match statement consists of a key and a value.

Provides a summary of the forecast export job properties used in the "ListForecastExportJobs" operation. To get the complete set of properties, call the "DescribeForecastExportJob" operation, and provide the listed ForecastExportJobArn.

Provides a summary of the forecast properties used in the "ListForecasts" operation. To get the complete set of properties, call the "DescribeForecast" operation, and provide the ForecastArn that is listed in the summary.

Configuration information for a hyperparameter tuning job. You specify this object in the "CreatePredictor" request.

Note: This object belongs to the "CreatePredictor" operation. If you created your predictor with "CreateAutoPredictor", see "DataConfig".

Specifies an integer hyperparameter and it's range of tunable values. This object is part of the "ParameterRanges" object.

An individual metric Forecast calculated when monitoring predictor usage. You can compare the value for this metric to the metric's value in the "Baseline" to see how your predictor's performance is changing.

Provides metrics that are used to evaluate the performance of a predictor. This object is part of the "WindowSummary" object.

The configuration details for the predictor monitor.

The source of the data the monitor used during the evaluation.

Provides information about the monitor resource.

Provides a summary of the monitor properties used in the "ListMonitors" operation. To get a complete set of properties, call the "DescribeMonitor" operation, and provide the listed MonitorArn.

Specifies the categorical, continuous, and integer hyperparameters, and their ranges of tunable values. The range of tunable values determines which values that a hyperparameter tuning job can choose for the specified hyperparameter. This object is part of the "HyperParameterTuningJobConfig" object.

Provides a summary of the predictor backtest export job properties used in the "ListPredictorBacktestExportJobs" operation. To get a complete set of properties, call the "DescribePredictorBacktestExportJob" operation, and provide the listed PredictorBacktestExportJobArn.

Metrics you can use as a baseline for comparison purposes. Use these metrics when you interpret monitoring results for an auto predictor.

Provides details about a predictor event, such as a retraining.

The algorithm used to perform a backtest and the status of those tests.

Contains details on the backtests performed to evaluate the accuracy of the predictor. The tests are returned in descending order of accuracy, with the most accurate backtest appearing first. You specify the number of backtests to perform when you call the operation.

Describes the results of a monitor evaluation.

Provides a summary of the predictor properties that are used in the "ListPredictors" operation. To get the complete set of properties, call the "DescribePredictor" operation, and provide the listed PredictorArn.

Provides a summary of the reference predictor used when retraining or upgrading a predictor.

The path to the file(s) in an Amazon Simple Storage Service (Amazon S3) bucket, and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the file(s). Optionally, includes an Key Management Service (KMS) key. This object is part of the "DataSource" object that is submitted in the "CreateDatasetImportJob" request, and part of the "DataDestination" object.

Defines the fields of a dataset.

An attribute of a schema, which defines a dataset field. A schema attribute is required for every field in a dataset. The Schema object contains an array of SchemaAttribute objects.

Provides statistics for each data field imported into to an Amazon Forecast dataset with the CreateDatasetImportJob operation.

Note: This object belongs to the "CreatePredictor" operation. If you created your predictor with "CreateAutoPredictor", see "AdditionalDataset".

The optional metadata that you apply to a resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The status, start time, and end time of a backtest, as well as a failure reason if applicable.

The time boundary Forecast uses to align and aggregate your data to match your forecast frequency. Provide the unit of time and the time boundary as a key value pair. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.

Creates a subset of items within an attribute that are modified. For example, you can use this operation to create a subset of items that cost $5 or less. To do this, you specify "AttributeName": "price", "AttributeValue": "5", and "Condition": "LESS_THAN". Pair this operation with the "Action" operation within the "CreateWhatIfForecastRequest$TimeSeriesTransformations" operation to define how the attribute is modified.

Details about the import file that contains the time series for which you want to create forecasts.

A replacement dataset is a modified version of the baseline related time series that contains only the values that you want to include in a what-if forecast. The replacement dataset must contain the forecast dimensions and item identifiers in the baseline related time series as well as at least 1 changed time series. This dataset is merged with the baseline related time series to create a transformed dataset that is used for the what-if forecast.

Defines the set of time series that are used to create the forecasts in a TimeSeriesIdentifiers object.

A transformation function is a pair of operations that select and modify the rows in a related time series. You select the rows that you want with a condition operation and you modify the rows with a transformation operation. All conditions are joined with an AND operation, meaning that all conditions must be true for the transformation to be applied. Transformations are applied in the order that they are listed.

The weighted loss value for a quantile. This object is part of the "Metrics" object.

Provides a summary of the what-if analysis properties used in the "ListWhatIfAnalyses" operation. To get the complete set of properties, call the "DescribeWhatIfAnalysis" operation, and provide the WhatIfAnalysisArn that is listed in the summary.

Provides a summary of the what-if forecast export properties used in the "ListWhatIfForecastExports" operation. To get the complete set of properties, call the "DescribeWhatIfForecastExport" operation, and provide the WhatIfForecastExportArn that is listed in the summary.

Provides a summary of the what-if forecast properties used in the "ListWhatIfForecasts" operation. To get the complete set of properties, call the "DescribeWhatIfForecast" operation, and provide the WhatIfForecastArn that is listed in the summary.

The metrics for a time range within the evaluation portion of a dataset. This object is part of the "EvaluationResult" object.