com.amazonaws.services.sagemaker.model

Class AutoMLCandidateGenerationConfig

java.lang.Object

com.amazonaws.services.sagemaker.model.AutoMLCandidateGenerationConfig

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class AutoMLCandidateGenerationConfig
extends Object
implements Serializable, Cloneable, StructuredPojo

Stores the configuration information for how a candidate is generated (optional).

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors

Constructor and Description
AutoMLCandidateGenerationConfig()

Method Summary

Modifier and Type	Method and Description
AutoMLCandidateGenerationConfig	clone()
boolean	equals(Object obj)
List<AutoMLAlgorithmConfig>	getAlgorithmsConfig() Stores the configuration information for the selection of algorithms trained on tabular data.
String	getFeatureSpecificationS3Uri() A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job.
int	hashCode()
void	marshall(ProtocolMarshaller protocolMarshaller) Marshalls this structured data using the given ProtocolMarshaller.
void	setAlgorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig) Stores the configuration information for the selection of algorithms trained on tabular data.
void	setFeatureSpecificationS3Uri(String featureSpecificationS3Uri) A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job.
String	toString() Returns a string representation of this object.
AutoMLCandidateGenerationConfig	withAlgorithmsConfig(AutoMLAlgorithmConfig... algorithmsConfig) Stores the configuration information for the selection of algorithms trained on tabular data.
AutoMLCandidateGenerationConfig	withAlgorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig) Stores the configuration information for the selection of algorithms trained on tabular data.
AutoMLCandidateGenerationConfig	withFeatureSpecificationS3Uri(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 class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

AutoMLCandidateGenerationConfig

public AutoMLCandidateGenerationConfig()

Method Detail

setFeatureSpecificationS3Uri

public void setFeatureSpecificationS3Uri(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.

getFeatureSpecificationS3Uri

public String getFeatureSpecificationS3Uri()

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:

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.

withFeatureSpecificationS3Uri

public AutoMLCandidateGenerationConfig withFeatureSpecificationS3Uri(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.

getAlgorithmsConfig

public List<AutoMLAlgorithmConfig> getAlgorithmsConfig()

Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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

Returns:

Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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

setAlgorithmsConfig

public void setAlgorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig)

Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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 trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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

withAlgorithmsConfig

public AutoMLCandidateGenerationConfig withAlgorithmsConfig(AutoMLAlgorithmConfig... algorithmsConfig)

Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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

NOTE: This method appends the values to the existing list (if any). Use setAlgorithmsConfig(java.util.Collection) or withAlgorithmsConfig(java.util.Collection) if you want to override the existing values.

Parameters:

algorithmsConfig - Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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.

withAlgorithmsConfig

public AutoMLCandidateGenerationConfig withAlgorithmsConfig(Collection<AutoMLAlgorithmConfig> algorithmsConfig)

Stores the configuration information for the selection of algorithms trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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 trained on tabular data.

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

• AlgorithmsConfig should not be set if the training mode is set on AUTO.

• 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, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

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

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

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.

toString

public String toString()

Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.

Overrides:

toString in class Object

Returns:

A string representation of this object.

See Also:

Object.toString()

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

clone

public AutoMLCandidateGenerationConfig clone()

Overrides:

clone in class Object

marshall

public void marshall(ProtocolMarshaller protocolMarshaller)

Description copied from interface: StructuredPojo

Marshalls this structured data using the given ProtocolMarshaller.

Specified by:

marshall in interface StructuredPojo

Parameters:

protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.