com.amazonaws.services.personalize.model

Class CreateSolutionRequest

java.lang.Object

com.amazonaws.AmazonWebServiceRequest

com.amazonaws.services.personalize.model.CreateSolutionRequest

All Implemented Interfaces:

HandlerContextAware, ReadLimitInfo, Serializable, Cloneable

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

See Also:

AWS API Documentation, Serialized Form

Field Summary

Fields inherited from class com.amazonaws.AmazonWebServiceRequest

NOOP

Constructor Summary

Constructors

Constructor and Description
CreateSolutionRequest()

Method Summary

Modifier and Type	Method and Description
CreateSolutionRequest	clone() Creates a shallow clone of this object for all fields except the handler context.
boolean	equals(Object obj)
String	getDatasetGroupArn() The Amazon Resource Name (ARN) of the dataset group that provides the training data.
String	getEventType() When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
String	getName() The name for the solution.
Boolean	getPerformAutoML() Whether to perform automated machine learning (AutoML).
Boolean	getPerformHPO() Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe.
String	getRecipeArn() The ARN of the recipe to use for model training.
SolutionConfig	getSolutionConfig() The configuration to use with the solution.
int	hashCode()
Boolean	isPerformAutoML() Whether to perform automated machine learning (AutoML).
Boolean	isPerformHPO() Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe.
void	setDatasetGroupArn(String datasetGroupArn) The Amazon Resource Name (ARN) of the dataset group that provides the training data.
void	setEventType(String eventType) When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
void	setName(String name) The name for the solution.
void	setPerformAutoML(Boolean performAutoML) Whether to perform automated machine learning (AutoML).
void	setPerformHPO(Boolean performHPO) Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe.
void	setRecipeArn(String recipeArn) The ARN of the recipe to use for model training.
void	setSolutionConfig(SolutionConfig solutionConfig) The configuration to use with the solution.
String	toString() Returns a string representation of this object.
CreateSolutionRequest	withDatasetGroupArn(String datasetGroupArn) The Amazon Resource Name (ARN) of the dataset group that provides the training data.
CreateSolutionRequest	withEventType(String eventType) When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
CreateSolutionRequest	withName(String name) The name for the solution.
CreateSolutionRequest	withPerformAutoML(Boolean performAutoML) Whether to perform automated machine learning (AutoML).
CreateSolutionRequest	withPerformHPO(Boolean performHPO) Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe.
CreateSolutionRequest	withRecipeArn(String recipeArn) The ARN of the recipe to use for model training.
CreateSolutionRequest	withSolutionConfig(SolutionConfig solutionConfig) The configuration to use with the solution.

Methods inherited from class com.amazonaws.AmazonWebServiceRequest

addHandlerContext, getCloneRoot, getCloneSource, getCustomQueryParameters, getCustomRequestHeaders, getGeneralProgressListener, getHandlerContext, getReadLimit, getRequestClientOptions, getRequestCredentials, getRequestCredentialsProvider, getRequestMetricCollector, getSdkClientExecutionTimeout, getSdkRequestTimeout, putCustomQueryParameter, putCustomRequestHeader, setGeneralProgressListener, setRequestCredentials, setRequestCredentialsProvider, setRequestMetricCollector, setSdkClientExecutionTimeout, setSdkRequestTimeout, withGeneralProgressListener, withRequestCredentialsProvider, withRequestMetricCollector, withSdkClientExecutionTimeout, withSdkRequestTimeout

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

CreateSolutionRequest

public CreateSolutionRequest()

Method Detail

setName

public void setName(String name)

The name for the solution.

Parameters:

name - The name for the solution.

getName

public String getName()

The name for the solution.

Returns:

The name for the solution.

withName

public CreateSolutionRequest withName(String name)

The name for the solution.

Parameters:

name - The name for the solution.

Returns:

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

setPerformHPO

public void setPerformHPO(Boolean performHPO)

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

Parameters:

performHPO - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

getPerformHPO

public Boolean getPerformHPO()

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

Returns:

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

withPerformHPO

public CreateSolutionRequest withPerformHPO(Boolean performHPO)

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

Parameters:

performHPO - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

Returns:

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

isPerformHPO

public Boolean isPerformHPO()

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

Returns:

Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false.

When performing AutoML, this parameter is always true and you should not set it to false.

setPerformAutoML

public void setPerformAutoML(Boolean performAutoML)

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

Parameters:

performAutoML - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

getPerformAutoML

public Boolean getPerformAutoML()

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

Returns:

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

withPerformAutoML

public CreateSolutionRequest withPerformAutoML(Boolean performAutoML)

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

Parameters:

performAutoML - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

Returns:

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

isPerformAutoML

public Boolean isPerformAutoML()

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

Returns:

Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.

When set to true, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

setRecipeArn

public void setRecipeArn(String recipeArn)

The ARN of the recipe to use for model training. Only specified when performAutoML is false.

Parameters:

recipeArn - The ARN of the recipe to use for model training. Only specified when performAutoML is false.

getRecipeArn

public String getRecipeArn()

The ARN of the recipe to use for model training. Only specified when performAutoML is false.

Returns:

The ARN of the recipe to use for model training. Only specified when performAutoML is false.

withRecipeArn

public CreateSolutionRequest withRecipeArn(String recipeArn)

The ARN of the recipe to use for model training. Only specified when performAutoML is false.

Parameters:

recipeArn - The ARN of the recipe to use for model training. Only specified when performAutoML is false.

Returns:

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

setDatasetGroupArn

public void setDatasetGroupArn(String datasetGroupArn)

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

Parameters:

datasetGroupArn - The Amazon Resource Name (ARN) of the dataset group that provides the training data.

getDatasetGroupArn

public String getDatasetGroupArn()

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

Returns:

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

withDatasetGroupArn

public CreateSolutionRequest withDatasetGroupArn(String datasetGroupArn)

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

Parameters:

datasetGroupArn - The Amazon Resource Name (ARN) of the dataset group that provides the training data.

Returns:

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

setEventType

public void setEventType(String eventType)

When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

Parameters:

eventType - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

getEventType

public String getEventType()

When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

Returns:

When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

withEventType

public CreateSolutionRequest withEventType(String eventType)

When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

Parameters:

eventType - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

Returns:

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

setSolutionConfig

public void setSolutionConfig(SolutionConfig solutionConfig)

The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

Parameters:

solutionConfig - The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

getSolutionConfig

public SolutionConfig getSolutionConfig()

The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

Returns:

The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

withSolutionConfig

public CreateSolutionRequest withSolutionConfig(SolutionConfig solutionConfig)

The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

Parameters:

solutionConfig - The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

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 CreateSolutionRequest clone()

Description copied from class: AmazonWebServiceRequest

Creates a shallow clone of this object for all fields except the handler context. Explicitly does not clone the deep structure of the other fields in the message.

Overrides:

clone in class AmazonWebServiceRequest

See Also:

Object.clone()