v1

latestOpenAPI 3.0.0Apache 2.0 License2026-07-1463278347.3 KB

Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation. Use metrics to see how well the model performed and to decide whether to use the predictor to generate a forecast. For more information, see Predictor Metrics.

This operation generates metrics for each backtest window that was evaluated. The number of backtest windows (NumberOfBacktestWindows) is specified using the EvaluationParameters object, which is optionally included in the CreatePredictor request. If NumberOfBacktestWindows isn't specified, the number defaults to one.

The parameters of the filling method determine which items contribute to the metrics. If you want all items to contribute, specify zero. If you want only those items that have complete data in the range being evaluated to contribute, specify nan. For more information, see FeaturizationMethod.

Before you can get accuracy metrics, the Status of the predictor must be ACTIVE, signifying that training has completed. To get the status, use the DescribePredictor operation.

post/#X-Amz-Target=AmazonForecast.GetAccuracyMetrics

Headers

X-Amz-Target'AmazonForecast.GetAccuracyMetrics' required

Request body

PredictorArnstring required

The Amazon Resource Name (ARN) of the predictor to get metrics for.

Response

Success

IsAutoPredictorboolean

Whether the predictor was created with <a>CreateAutoPredictor</a>.

AutoMLOverrideStrategy'LatencyOptimized' | 'AccuracyOptimized'

<note> <p> The <code>LatencyOptimized</code> AutoML override strategy is only available in private beta. Contact Amazon Web Services Support or your account manager to learn more about access privileges. </p> </note> <p>The AutoML strategy used to train the predictor. Unless <code>LatencyOptimized</code> is specified, the AutoML strategy optimizes predictor accuracy.</p> <p>This parameter is only valid for predictors trained using AutoML.</p>

OptimizationMetric'WAPE' | 'RMSE' | 'AverageWeightedQuantileLoss' | 'MASE' | 'MAPE'

The accuracy metric used to optimize the predictor.