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 destination for an export job. Provide an S3 path, an AWS Identity and Access Management (IAM) role that allows Amazon Forecast to access the location, and an AWS 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 training data, an AWS Identity and Access Management (IAM) role that allows Amazon Forecast to access the data and, optionally, an AWS Key Management Service (KMS) key. This object is submitted in the "CreateDatasetImportJob" request.

An AWS Key Management Service (KMS) key and an AWS 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.

Provides featurization (transformation) information for a dataset field. This object is part of the "FeaturizationConfig" object.

In a "CreatePredictor" operation, the specified algorithm trains a model using the specified dataset group. You can optionally tell the operation to modify data fields prior to training a model. These modifications are referred to as featurization.

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.

The data used to train a predictor. The data includes a dataset group and any supplementary features. You specify this object in the "CreatePredictor" request.

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

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

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.

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.

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.

The path to the file(s) in an Amazon Simple Storage Service (Amazon S3) bucket, and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the file(s). Optionally, includes an AWS 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. You specify this object in the "CreateDataset" request.

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.

Describes a supplementary feature of a dataset group. This object is part of the "InputDataConfig" object. Forecast supports the Weather Index and Holidays built-in featurizations.

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

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