<p>Creates an Amazon Forecast predictor.</p> <p>Amazon Forecast creates predictors with AutoPredictor, which involves applying the optimal combination of algorithms to each time series in your datasets. You can use <a>CreateAutoPredictor</a> to create new predictors or upgrade/retrain existing predictors.</p> <p> <b>Creating new predictors</b> </p> <p>The following parameters are required when creating a new predictor:</p> <ul> <li> <p> <code>PredictorName</code> - A unique name for the predictor.</p> </li> <li> <p> <code>DatasetGroupArn</code> - The ARN of the dataset group used to train the predictor.</p> </li> <li> <p> <code>ForecastFrequency</code> - The granularity of your forecasts (hourly, daily, weekly, etc).</p> </li> <li> <p> <code>ForecastHorizon</code> - The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.</p> </li> </ul> <p>When creating a new predictor, do not specify a value for <code>ReferencePredictorArn</code>.</p> <p> <b>Upgrading and retraining predictors</b> </p> <p>The following parameters are required when retraining or upgrading a predictor:</p> <ul> <li> <p> <code>PredictorName</code> - A unique name for the predictor.</p> </li> <li> <p> <code>ReferencePredictorArn</code> - The ARN of the predictor to retrain or upgrade.</p> </li> </ul> <p>When upgrading or retraining a predictor, only specify values for the <code>ReferencePredictorArn</code> and <code>PredictorName</code>. </p>

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

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

<p>Creates an Amazon Forecast predictor.</p> <p>Amazon Forecast creates predictors with AutoPredictor, which involves applying the optimal combination of algorithms to each time series in your datasets. You can use <a>CreateAutoPredictor</a> to create new predictors or upgrade/retrain existing predictors.</p> <p> <b>Creating new predictors</b> </p> <p>The following parameters are required when creating a new predictor:</p> <ul> <li> <p> <code>PredictorName</code> - A unique name for the predictor.</p> </li> <li> <p> <code>DatasetGroupArn</code> - The ARN of the dataset group used to train the predictor.</p> </li> <li> <p> <code>ForecastFrequency</code> - The granularity of your forecasts (hourly, daily, weekly, etc).</p> </li> <li> <p> <code>ForecastHorizon</code> - The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.</p> </li> </ul> <p>When creating a new predictor, do not specify a value for <code>ReferencePredictorArn</code>.</p> <p> <b>Upgrading and retraining predictors</b> </p> <p>The following parameters are required when retraining or upgrading a predictor:</p> <ul> <li> <p> <code>PredictorName</code> - A unique name for the predictor.</p> </li> <li> <p> <code>ReferencePredictorArn</code> - The ARN of the predictor to retrain or upgrade.</p> </li> </ul> <p>When upgrading or retraining a predictor, only specify values for the <code>ReferencePredictorArn</code> and <code>PredictorName</code>. </p>

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

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