Interface CreateAutoMlJobRequest.Builder

All Superinterfaces:

AwsRequest.Builder, Buildable, CopyableBuilder<CreateAutoMlJobRequest.Builder,CreateAutoMlJobRequest>, SageMakerRequest.Builder, SdkBuilder<CreateAutoMlJobRequest.Builder,CreateAutoMlJobRequest>, SdkPojo, SdkRequest.Builder

Enclosing class:

CreateAutoMlJobRequest

@Mutable
@NotThreadSafe
public static interface CreateAutoMlJobRequest.Builder
extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder<CreateAutoMlJobRequest.Builder,CreateAutoMlJobRequest>

Method Summary

Modifier and Type	Method	Description
default CreateAutoMlJobRequest.Builder	autoMLJobConfig(Consumer<AutoMLJobConfig.Builder> autoMLJobConfig)	A collection of settings used to configure an AutoML job.
CreateAutoMlJobRequest.Builder	autoMLJobConfig(AutoMLJobConfig autoMLJobConfig)	A collection of settings used to configure an AutoML job.
CreateAutoMlJobRequest.Builder	autoMLJobName(String autoMLJobName)	Identifies an Autopilot job.
default CreateAutoMlJobRequest.Builder	autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> autoMLJobObjective)	Specifies a metric to minimize or maximize as the objective of a job.
CreateAutoMlJobRequest.Builder	autoMLJobObjective(AutoMLJobObjective autoMLJobObjective)	Specifies a metric to minimize or maximize as the objective of a job.
CreateAutoMlJobRequest.Builder	generateCandidateDefinitionsOnly(Boolean generateCandidateDefinitionsOnly)	Generates possible candidates without training the models.
CreateAutoMlJobRequest.Builder	inputDataConfig(Collection<AutoMLChannel> inputDataConfig)	An array of channel objects that describes the input data and its location.
CreateAutoMlJobRequest.Builder	inputDataConfig(Consumer<AutoMLChannel.Builder>... inputDataConfig)	An array of channel objects that describes the input data and its location.
CreateAutoMlJobRequest.Builder	inputDataConfig(AutoMLChannel... inputDataConfig)	An array of channel objects that describes the input data and its location.
default CreateAutoMlJobRequest.Builder	modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig)	Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
CreateAutoMlJobRequest.Builder	modelDeployConfig(ModelDeployConfig modelDeployConfig)	Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
default CreateAutoMlJobRequest.Builder	outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig)	Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
CreateAutoMlJobRequest.Builder	outputDataConfig(AutoMLOutputDataConfig outputDataConfig)	Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
CreateAutoMlJobRequest.Builder	overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)	Add an optional request override configuration.
CreateAutoMlJobRequest.Builder	overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)	Add an optional request override configuration.
CreateAutoMlJobRequest.Builder	problemType(String problemType)	Defines the type of supervised learning problem available for the candidates.
CreateAutoMlJobRequest.Builder	problemType(ProblemType problemType)	Defines the type of supervised learning problem available for the candidates.
CreateAutoMlJobRequest.Builder	roleArn(String roleArn)	The ARN of the role that is used to access the data.
CreateAutoMlJobRequest.Builder	tags(Collection<Tag> tags)	An array of key-value pairs.
CreateAutoMlJobRequest.Builder	tags(Consumer<Tag.Builder>... tags)	An array of key-value pairs.
CreateAutoMlJobRequest.Builder	tags(Tag... tags)	An array of key-value pairs.

Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder

overrideConfiguration

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder

build

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFieldNameToField, sdkFields

Method Details

autoMLJobName

CreateAutoMlJobRequest.Builder autoMLJobName(String autoMLJobName)

Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Parameters:

autoMLJobName - Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

CreateAutoMlJobRequest.Builder inputDataConfig(Collection<AutoMLChannel> inputDataConfig)

An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Parameters:

inputDataConfig - An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

CreateAutoMlJobRequest.Builder inputDataConfig(AutoMLChannel... inputDataConfig)

An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Parameters:

inputDataConfig - An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

CreateAutoMlJobRequest.Builder inputDataConfig(Consumer<AutoMLChannel.Builder>... inputDataConfig)

An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

This is a convenience method that creates an instance of the AutoMLChannel.Builder avoiding the need to create one manually via AutoMLChannel.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to inputDataConfig(List<AutoMLChannel>).

Parameters:

inputDataConfig - a consumer that will call methods on AutoMLChannel.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• inputDataConfig(java.util.Collection<AutoMLChannel>)

outputDataConfig

CreateAutoMlJobRequest.Builder outputDataConfig(AutoMLOutputDataConfig outputDataConfig)

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

Parameters:

outputDataConfig - Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

Returns:

Returns a reference to this object so that method calls can be chained together.

outputDataConfig

default CreateAutoMlJobRequest.Builder outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig)

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

This is a convenience method that creates an instance of the AutoMLOutputDataConfig.Builder avoiding the need to create one manually via AutoMLOutputDataConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to outputDataConfig(AutoMLOutputDataConfig).

Parameters:

outputDataConfig - a consumer that will call methods on AutoMLOutputDataConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• outputDataConfig(AutoMLOutputDataConfig)

problemType

CreateAutoMlJobRequest.Builder problemType(String problemType)

Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Parameters:

problemType - Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• ProblemType
• ProblemType

problemType

CreateAutoMlJobRequest.Builder problemType(ProblemType problemType)

Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Parameters:

problemType - Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• ProblemType
• ProblemType

autoMLJobObjective

CreateAutoMlJobRequest.Builder autoMLJobObjective(AutoMLJobObjective 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.

Parameters:

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.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobObjective

default CreateAutoMlJobRequest.Builder autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> 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.

This is a convenience method that creates an instance of the AutoMLJobObjective.Builder avoiding the need to create one manually via AutoMLJobObjective.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to autoMLJobObjective(AutoMLJobObjective).

Parameters:

autoMLJobObjective - a consumer that will call methods on AutoMLJobObjective.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• autoMLJobObjective(AutoMLJobObjective)

autoMLJobConfig

CreateAutoMlJobRequest.Builder autoMLJobConfig(AutoMLJobConfig autoMLJobConfig)

A collection of settings used to configure an AutoML job.

Parameters:

autoMLJobConfig - A collection of settings used to configure an AutoML job.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobConfig

default CreateAutoMlJobRequest.Builder autoMLJobConfig(Consumer<AutoMLJobConfig.Builder> autoMLJobConfig)

A collection of settings used to configure an AutoML job.

This is a convenience method that creates an instance of the AutoMLJobConfig.Builder avoiding the need to create one manually via AutoMLJobConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to autoMLJobConfig(AutoMLJobConfig).

Parameters:

autoMLJobConfig - a consumer that will call methods on AutoMLJobConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• autoMLJobConfig(AutoMLJobConfig)

roleArn

CreateAutoMlJobRequest.Builder roleArn(String roleArn)

The ARN of the role that is used to access the data.

Parameters:

roleArn - The ARN of the role that is used to access the data.

Returns:

Returns a reference to this object so that method calls can be chained together.

generateCandidateDefinitionsOnly

CreateAutoMlJobRequest.Builder generateCandidateDefinitionsOnly(Boolean generateCandidateDefinitionsOnly)

Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

Parameters:

generateCandidateDefinitionsOnly - Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobRequest.Builder tags(Collection<Tag> 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.

Parameters:

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.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobRequest.Builder tags(Tag... 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.

Parameters:

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.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobRequest.Builder tags(Consumer<Tag.Builder>... 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.

This is a convenience method that creates an instance of the Tag.Builder avoiding the need to create one manually via Tag.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to tags(List<Tag>).

Parameters:

tags - a consumer that will call methods on Tag.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• tags(java.util.Collection<Tag>)

modelDeployConfig

CreateAutoMlJobRequest.Builder modelDeployConfig(ModelDeployConfig modelDeployConfig)

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Parameters:

modelDeployConfig - Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Returns:

Returns a reference to this object so that method calls can be chained together.

modelDeployConfig

default CreateAutoMlJobRequest.Builder modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig)

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

This is a convenience method that creates an instance of the ModelDeployConfig.Builder avoiding the need to create one manually via ModelDeployConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to modelDeployConfig(ModelDeployConfig).

Parameters:

modelDeployConfig - a consumer that will call methods on ModelDeployConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

• modelDeployConfig(ModelDeployConfig)

overrideConfiguration

CreateAutoMlJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)

Description copied from interface: AwsRequest.Builder

Add an optional request override configuration.

Specified by:

overrideConfiguration in interface AwsRequest.Builder

Parameters:

overrideConfiguration - The override configuration.

Returns:

This object for method chaining.

overrideConfiguration

CreateAutoMlJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)

Description copied from interface: AwsRequest.Builder

Add an optional request override configuration.

Specified by:

overrideConfiguration in interface AwsRequest.Builder

Parameters:

builderConsumer - A Consumer to which an empty AwsRequestOverrideConfiguration.Builder will be given.

Returns:

This object for method chaining.