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Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
For .NET Core this operation is only available in asynchronous form. Please refer to CreateHyperParameterTuningJobAsync.
Namespace: Amazon.SageMaker
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public abstract CreateHyperParameterTuningJobResponse CreateHyperParameterTuningJob( CreateHyperParameterTuningJobRequest request )
Container for the necessary parameters to execute the CreateHyperParameterTuningJob service method.
| Exception | Condition |
|---|---|
| ResourceInUseException | Resource being accessed is in use. |
| ResourceLimitExceededException | You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. |
.NET Framework:
Supported in: 4.5, 4.0, 3.5