software.amazon.awssdk.services.sagemaker.model

Interface AutoMLCandidateGenerationConfig.Builder

All Superinterfaces:

Buildable, CopyableBuilder<AutoMLCandidateGenerationConfig.Builder,AutoMLCandidateGenerationConfig>, SdkBuilder<AutoMLCandidateGenerationConfig.Builder,AutoMLCandidateGenerationConfig>, SdkPojo

Enclosing class:

AutoMLCandidateGenerationConfig

public static interface AutoMLCandidateGenerationConfig.Builder
extends SdkPojo, CopyableBuilder<AutoMLCandidateGenerationConfig.Builder,AutoMLCandidateGenerationConfig>

Method Summary

Modifier and Type	Method and Description
AutoMLCandidateGenerationConfig.Builder	algorithmsConfig(AutoMLAlgorithmConfig... algorithmsConfig) Stores the configuration information for the selection of algorithms used to train the model candidates.
AutoMLCandidateGenerationConfig.Builder	algorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig) Stores the configuration information for the selection of algorithms used to train the model candidates.
AutoMLCandidateGenerationConfig.Builder	algorithmsConfig(Consumer<AutoMLAlgorithmConfig.Builder>... algorithmsConfig) Stores the configuration information for the selection of algorithms used to train the model candidates.
AutoMLCandidateGenerationConfig.Builder	featureSpecificationS3Uri(String featureSpecificationS3Uri) A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job.

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

equalsBySdkFields, sdkFields

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

copy

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

applyMutation, build

Method Detail

featureSpecificationS3Uri

AutoMLCandidateGenerationConfig.Builder featureSpecificationS3Uri(String featureSpecificationS3Uri)

A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:

{ "FeatureAttributeNames":["col1", "col2", ...] }.

You can also specify the data type of the feature (optional) in the format shown below:

{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }

These column keys may not include the target column.

In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.

If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.

If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.

The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.

Parameters:

featureSpecificationS3Uri - A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:

{ "FeatureAttributeNames":["col1", "col2", ...] }.

You can also specify the data type of the feature (optional) in the format shown below:

{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }

These column keys may not include the target column.

In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.

If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.

If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.

The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.

Returns:

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

algorithmsConfig

AutoMLCandidateGenerationConfig.Builder algorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig)

Stores the configuration information for the selection of algorithms used to train the model candidates.

The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .

• AlgorithmsConfig should not be set in AUTO training mode.

• When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

  If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

• When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per training mode, see .

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

Parameters:

algorithmsConfig - Stores the configuration information for the selection of algorithms used to train the model candidates.

The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .

• AlgorithmsConfig should not be set in AUTO training mode.

• When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

  If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

• When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per training mode, see .

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

Returns:

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

algorithmsConfig

AutoMLCandidateGenerationConfig.Builder algorithmsConfig(AutoMLAlgorithmConfig... algorithmsConfig)

Stores the configuration information for the selection of algorithms used to train the model candidates.

The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .

• AlgorithmsConfig should not be set in AUTO training mode.

• When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

  If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

• When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per training mode, see .

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

Parameters:

algorithmsConfig - Stores the configuration information for the selection of algorithms used to train the model candidates.

The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .

• AlgorithmsConfig should not be set in AUTO training mode.

• When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

  If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

• When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per training mode, see .

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

Returns:

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

algorithmsConfig

AutoMLCandidateGenerationConfig.Builder algorithmsConfig(Consumer<AutoMLAlgorithmConfig.Builder>... algorithmsConfig)

Stores the configuration information for the selection of algorithms used to train the model candidates.

The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .

• AlgorithmsConfig should not be set in AUTO training mode.

• When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

  If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

• When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per training mode, see .

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

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

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #algorithmsConfig(List).

Parameters:

algorithmsConfig - a consumer that will call methods on AutoMLAlgorithmConfig.Builder

Returns:

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

See Also:

#algorithmsConfig(java.util.Collection)