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 CreateAutoMLJob operation.
Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
We recommend using the new versions CreateAutoMLJobV2
and DescribeAutoMLJobV2,
which offer backward compatibility.
Find guidelines about how to migrate a CreateAutoMLJobV2
can manage tabular problem types identical to those of its
previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular
problem types such as image or text classification, and text generation (LLMs fine-tuning).
CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate
a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
Namespace: Amazon.SageMaker.Model
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public class CreateAutoMLJobRequest : AmazonSageMakerRequest IAmazonWebServiceRequest
The CreateAutoMLJobRequest type exposes the following members
Name | Description | |
---|---|---|
CreateAutoMLJobRequest() |
Name | Type | Description | |
---|---|---|---|
AutoMLJobConfig | Amazon.SageMaker.Model.AutoMLJobConfig |
Gets and sets the property AutoMLJobConfig. A collection of settings used to configure an AutoML job. |
|
AutoMLJobName | System.String |
Gets and sets the property AutoMLJobName. Identifies an Autopilot job. The name must be unique to your account and is case insensitive. |
|
AutoMLJobObjective | Amazon.SageMaker.Model.AutoMLJobObjective |
Gets and sets the property AutoMLJobObjective. Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values. |
|
GenerateCandidateDefinitionsOnly | System.Boolean |
Gets and sets the property GenerateCandidateDefinitionsOnly. Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings. |
|
InputDataConfig | System.Collections.Generic.List<Amazon.SageMaker.Model.AutoMLChannel> |
Gets and sets the property InputDataConfig.
An array of channel objects that describes the input data and its location. Each channel
is a named input source. Similar to |
|
ModelDeployConfig | Amazon.SageMaker.Model.ModelDeployConfig |
Gets and sets the property ModelDeployConfig. Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment. |
|
OutputDataConfig | Amazon.SageMaker.Model.AutoMLOutputDataConfig |
Gets and sets the property OutputDataConfig. Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV. |
|
ProblemType | Amazon.SageMaker.ProblemType |
Gets and sets the property ProblemType. Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types. |
|
RoleArn | System.String |
Gets and sets the property RoleArn. The ARN of the role that is used to access the data. |
|
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 ServicesResources. Tag keys must be unique per resource. |
.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