@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class CreateSolutionRequest extends AmazonWebServiceRequest implements Serializable, Cloneable
NOOP
Constructor and Description |
---|
CreateSolutionRequest() |
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.
|
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
public void setName(String name)
The name for the solution.
name
- The name for the solution.public String getName()
The name for the solution.
public CreateSolutionRequest withName(String name)
The name for the solution.
name
- The name for the solution.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
.
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
.
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
.
false
.
When performing AutoML, this parameter is always true
and you should not set it to
false
.
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
.
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
.
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
.
false
.
When performing AutoML, this parameter is always true
and you should not set it to
false
.
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.
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.
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.
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.
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.
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.
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.
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.
public void setRecipeArn(String recipeArn)
The ARN of the recipe to use for model training. Only specified when performAutoML
is false.
recipeArn
- The ARN of the recipe to use for model training. Only specified when performAutoML
is false.public String getRecipeArn()
The ARN of the recipe to use for model training. Only specified when performAutoML
is false.
performAutoML
is false.public CreateSolutionRequest withRecipeArn(String recipeArn)
The ARN of the recipe to use for model training. Only specified when performAutoML
is false.
recipeArn
- The ARN of the recipe to use for model training. Only specified when performAutoML
is false.public void setDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
datasetGroupArn
- The Amazon Resource Name (ARN) of the dataset group that provides the training data.public String getDatasetGroupArn()
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
public CreateSolutionRequest withDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
datasetGroupArn
- The Amazon Resource Name (ARN) of the dataset group that provides the training data.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.
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.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.
EVENT_TYPE
schema field), this parameter
specifies which event type (for example, 'click' or 'like') is used for training the model.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.
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.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.
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.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.
performAutoML
is set to true, Amazon
Personalize only evaluates the autoMLConfig
section of the solution configuration.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.
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.public String toString()
toString
in class Object
Object.toString()
public CreateSolutionRequest clone()
AmazonWebServiceRequest
clone
in class AmazonWebServiceRequest
Object.clone()
Copyright © 2013 Amazon Web Services, Inc. All Rights Reserved.