AWS services or capabilities described in AWS Documentation may vary by region/location. Click Getting Started with Amazon AWS to see specific differences applicable to the China (Beijing) Region.
Container for the parameters to the CreateHyperParameterTuningJob operation. 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.
Namespace: Amazon.SageMaker.Model
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public class CreateHyperParameterTuningJobRequest : AmazonSageMakerRequest IAmazonWebServiceRequest
The CreateHyperParameterTuningJobRequest type exposes the following members
Name | Description | |
---|---|---|
CreateHyperParameterTuningJobRequest() |
Name | Type | Description | |
---|---|---|---|
Autotune | Amazon.SageMaker.Model.Autotune |
Gets and sets the property Autotune. Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
|
|
HyperParameterTuningJobConfig | Amazon.SageMaker.Model.HyperParameterTuningJobConfig |
Gets and sets the property HyperParameterTuningJobConfig. The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works. |
|
HyperParameterTuningJobName | System.String |
Gets and sets the property HyperParameterTuningJobName. The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive. |
|
Tags | System.Collections.Generic.List<Amazon.SageMaker.Model.Tag> |
Gets and sets the property Tags. An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches. |
|
TrainingJobDefinition | Amazon.SageMaker.Model.HyperParameterTrainingJobDefinition |
Gets and sets the property TrainingJobDefinition. The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition. |
|
TrainingJobDefinitions | System.Collections.Generic.List<Amazon.SageMaker.Model.HyperParameterTrainingJobDefinition> |
Gets and sets the property TrainingJobDefinitions. A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job. |
|
WarmStartConfig | Amazon.SageMaker.Model.HyperParameterTuningJobWarmStartConfig |
Gets and sets the property WarmStartConfig. Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using
the objective metric. If you specify All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job. |
.NET:
Supported in: 8.0 and newer, Core 3.1
.NET Standard:
Supported in: 2.0
.NET Framework:
Supported in: 4.5 and newer, 3.5