<p>Provides metrics on the accuracy of the models that were trained by the <a>CreatePredictor</a> 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 <a href="https://docs.aws.amazon.com/forecast/latest/dg/metrics.html">Predictor Metrics</a>.</p> <p>This operation generates metrics for each backtest window that was evaluated. The number of backtest windows (<code>NumberOfBacktestWindows</code>) is specified using the <a>EvaluationParameters</a> object, which is optionally included in the <code>CreatePredictor</code> request. If <code>NumberOfBacktestWindows</code> isn't specified, the number defaults to one.</p> <p>The parameters of the <code>filling</code> method determine which items contribute to the metrics. If you want all items to contribute, specify <code>zero</code>. If you want only those items that have complete data in the range being evaluated to contribute, specify <code>nan</code>. For more information, see <a>FeaturizationMethod</a>.</p> <note> <p>Before you can get accuracy metrics, the <code>Status</code> of the predictor must be <code>ACTIVE</code>, signifying that training has completed. To get the status, use the <a>DescribePredictor</a> operation.</p> </note>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}

<p>Provides metrics on the accuracy of the models that were trained by the <a>CreatePredictor</a> 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 <a href="https://docs.aws.amazon.com/forecast/latest/dg/metrics.html">Predictor Metrics</a>.</p> <p>This operation generates metrics for each backtest window that was evaluated. The number of backtest windows (<code>NumberOfBacktestWindows</code>) is specified using the <a>EvaluationParameters</a> object, which is optionally included in the <code>CreatePredictor</code> request. If <code>NumberOfBacktestWindows</code> isn't specified, the number defaults to one.</p> <p>The parameters of the <code>filling</code> method determine which items contribute to the metrics. If you want all items to contribute, specify <code>zero</code>. If you want only those items that have complete data in the range being evaluated to contribute, specify <code>nan</code>. For more information, see <a>FeaturizationMethod</a>.</p> <note> <p>Before you can get accuracy metrics, the <code>Status</code> of the predictor must be <code>ACTIVE</code>, signifying that training has completed. To get the status, use the <a>DescribePredictor</a> operation.</p> </note>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}