Package com.amazonaws.services.machinelearning.model

Class GetEvaluationResult

java.lang.Object

com.amazonaws.services.machinelearning.model.GetEvaluationResult

All Implemented Interfaces:

Serializable, Cloneable

public class GetEvaluationResult
extends Object
implements Serializable, Cloneable

Represents the output of a GetEvaluation operation and describes an Evaluation.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor	Description
GetEvaluationResult()

Method Summary

Modifier and Type	Method	Description
GetEvaluationResult	clone()
boolean	equals(Object obj)
Date	getCreatedAt()	The time that the Evaluation was created.
String	getCreatedByIamUser()	The AWS user account that invoked the evaluation.
String	getEvaluationDataSourceId()	The DataSource used for this evaluation.
String	getEvaluationId()	The evaluation ID which is same as the EvaluationId in the request.
String	getInputDataLocationS3()	The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
Date	getLastUpdatedAt()	The time of the most recent edit to the BatchPrediction.
String	getLogUri()	A link to the file that contains logs of the CreateEvaluation operation.
String	getMessage()	A description of the most recent details about evaluating the MLModel.
String	getMLModelId()	The ID of the MLModel that was the focus of the evaluation.
String	getName()	A user-supplied name or description of the Evaluation.
PerformanceMetrics	getPerformanceMetrics()	Measurements of how well the MLModel performed using observations referenced by the DataSource.
String	getStatus()	The status of the evaluation.
int	hashCode()
void	setCreatedAt(Date createdAt)	The time that the Evaluation was created.
void	setCreatedByIamUser(String createdByIamUser)	The AWS user account that invoked the evaluation.
void	setEvaluationDataSourceId(String evaluationDataSourceId)	The DataSource used for this evaluation.
void	setEvaluationId(String evaluationId)	The evaluation ID which is same as the EvaluationId in the request.
void	setInputDataLocationS3(String inputDataLocationS3)	The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
void	setLastUpdatedAt(Date lastUpdatedAt)	The time of the most recent edit to the BatchPrediction.
void	setLogUri(String logUri)	A link to the file that contains logs of the CreateEvaluation operation.
void	setMessage(String message)	A description of the most recent details about evaluating the MLModel.
void	setMLModelId(String mLModelId)	The ID of the MLModel that was the focus of the evaluation.
void	setName(String name)	A user-supplied name or description of the Evaluation.
void	setPerformanceMetrics(PerformanceMetrics performanceMetrics)	Measurements of how well the MLModel performed using observations referenced by the DataSource.
void	setStatus(EntityStatus status)	The status of the evaluation.
void	setStatus(String status)	The status of the evaluation.
String	toString()	Returns a string representation of this object; useful for testing and debugging.
GetEvaluationResult	withCreatedAt(Date createdAt)	The time that the Evaluation was created.
GetEvaluationResult	withCreatedByIamUser(String createdByIamUser)	The AWS user account that invoked the evaluation.
GetEvaluationResult	withEvaluationDataSourceId(String evaluationDataSourceId)	The DataSource used for this evaluation.
GetEvaluationResult	withEvaluationId(String evaluationId)	The evaluation ID which is same as the EvaluationId in the request.
GetEvaluationResult	withInputDataLocationS3(String inputDataLocationS3)	The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
GetEvaluationResult	withLastUpdatedAt(Date lastUpdatedAt)	The time of the most recent edit to the BatchPrediction.
GetEvaluationResult	withLogUri(String logUri)	A link to the file that contains logs of the CreateEvaluation operation.
GetEvaluationResult	withMessage(String message)	A description of the most recent details about evaluating the MLModel.
GetEvaluationResult	withMLModelId(String mLModelId)	The ID of the MLModel that was the focus of the evaluation.
GetEvaluationResult	withName(String name)	A user-supplied name or description of the Evaluation.
GetEvaluationResult	withPerformanceMetrics(PerformanceMetrics performanceMetrics)	Measurements of how well the MLModel performed using observations referenced by the DataSource.
GetEvaluationResult	withStatus(EntityStatus status)	The status of the evaluation.
GetEvaluationResult	withStatus(String status)	The status of the evaluation.

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

GetEvaluationResult

public GetEvaluationResult()

Method Detail

setEvaluationId

public void setEvaluationId(String evaluationId)

The evaluation ID which is same as the EvaluationId in the request.

Parameters:

evaluationId - The evaluation ID which is same as the EvaluationId in the request.

getEvaluationId

public String getEvaluationId()

The evaluation ID which is same as the EvaluationId in the request.

Returns:

The evaluation ID which is same as the EvaluationId in the request.

withEvaluationId

public GetEvaluationResult withEvaluationId(String evaluationId)

The evaluation ID which is same as the EvaluationId in the request.

Parameters:

evaluationId - The evaluation ID which is same as the EvaluationId in the request.

Returns:

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

setMLModelId

public void setMLModelId(String mLModelId)

The ID of the MLModel that was the focus of the evaluation.

Parameters:

mLModelId - The ID of the MLModel that was the focus of the evaluation.

getMLModelId

public String getMLModelId()

The ID of the MLModel that was the focus of the evaluation.

Returns:

The ID of the MLModel that was the focus of the evaluation.

withMLModelId

public GetEvaluationResult withMLModelId(String mLModelId)

The ID of the MLModel that was the focus of the evaluation.

Parameters:

mLModelId - The ID of the MLModel that was the focus of the evaluation.

Returns:

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

setEvaluationDataSourceId

public void setEvaluationDataSourceId(String evaluationDataSourceId)

The DataSource used for this evaluation.

Parameters:

evaluationDataSourceId - The DataSource used for this evaluation.

getEvaluationDataSourceId

public String getEvaluationDataSourceId()

The DataSource used for this evaluation.

Returns:

The DataSource used for this evaluation.

withEvaluationDataSourceId

public GetEvaluationResult withEvaluationDataSourceId(String evaluationDataSourceId)

The DataSource used for this evaluation.

Parameters:

evaluationDataSourceId - The DataSource used for this evaluation.

Returns:

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

setInputDataLocationS3

public void setInputDataLocationS3(String inputDataLocationS3)

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

Parameters:

inputDataLocationS3 - The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

getInputDataLocationS3

public String getInputDataLocationS3()

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

Returns:

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

withInputDataLocationS3

public GetEvaluationResult withInputDataLocationS3(String inputDataLocationS3)

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

Parameters:

inputDataLocationS3 - The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

Returns:

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

setCreatedByIamUser

public void setCreatedByIamUser(String createdByIamUser)

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Parameters:

createdByIamUser - The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

getCreatedByIamUser

public String getCreatedByIamUser()

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Returns:

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

withCreatedByIamUser

public GetEvaluationResult withCreatedByIamUser(String createdByIamUser)

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Parameters:

createdByIamUser - The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Returns:

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

setCreatedAt

public void setCreatedAt(Date createdAt)

The time that the Evaluation was created. The time is expressed in epoch time.

Parameters:

createdAt - The time that the Evaluation was created. The time is expressed in epoch time.

getCreatedAt

public Date getCreatedAt()

The time that the Evaluation was created. The time is expressed in epoch time.

Returns:

The time that the Evaluation was created. The time is expressed in epoch time.

withCreatedAt

public GetEvaluationResult withCreatedAt(Date createdAt)

The time that the Evaluation was created. The time is expressed in epoch time.

Parameters:

createdAt - The time that the Evaluation was created. The time is expressed in epoch time.

Returns:

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

setLastUpdatedAt

public void setLastUpdatedAt(Date lastUpdatedAt)

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

Parameters:

lastUpdatedAt - The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

getLastUpdatedAt

public Date getLastUpdatedAt()

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

Returns:

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

withLastUpdatedAt

public GetEvaluationResult withLastUpdatedAt(Date lastUpdatedAt)

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

Parameters:

lastUpdatedAt - The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

Returns:

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

setName

public void setName(String name)

A user-supplied name or description of the Evaluation.

Parameters:

name - A user-supplied name or description of the Evaluation .

getName

public String getName()

A user-supplied name or description of the Evaluation.

Returns:

A user-supplied name or description of the Evaluation.

withName

public GetEvaluationResult withName(String name)

A user-supplied name or description of the Evaluation.

Parameters:

name - A user-supplied name or description of the Evaluation .

Returns:

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

setStatus

public void setStatus(String status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

See Also:

EntityStatus

getStatus

public String getStatus()

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Returns:

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

See Also:

EntityStatus

withStatus

public GetEvaluationResult withStatus(String status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Returns:

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

See Also:

EntityStatus

setStatus

public void setStatus(EntityStatus status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

See Also:

EntityStatus

withStatus

public GetEvaluationResult withStatus(EntityStatus status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Returns:

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

See Also:

EntityStatus

setPerformanceMetrics

public void setPerformanceMetrics(PerformanceMetrics performanceMetrics)

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Parameters:

performanceMetrics - Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

getPerformanceMetrics

public PerformanceMetrics getPerformanceMetrics()

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Returns:

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

withPerformanceMetrics

public GetEvaluationResult withPerformanceMetrics(PerformanceMetrics performanceMetrics)

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Parameters:

performanceMetrics - Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Returns:

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

setLogUri

public void setLogUri(String logUri)

A link to the file that contains logs of the CreateEvaluation operation.

Parameters:

logUri - A link to the file that contains logs of the CreateEvaluation operation.

getLogUri

public String getLogUri()

A link to the file that contains logs of the CreateEvaluation operation.

Returns:

A link to the file that contains logs of the CreateEvaluation operation.

withLogUri

public GetEvaluationResult withLogUri(String logUri)

A link to the file that contains logs of the CreateEvaluation operation.

Parameters:

logUri - A link to the file that contains logs of the CreateEvaluation operation.

Returns:

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

setMessage

public void setMessage(String message)

A description of the most recent details about evaluating the MLModel.

Parameters:

message - A description of the most recent details about evaluating the MLModel.

getMessage

public String getMessage()

A description of the most recent details about evaluating the MLModel.

Returns:

A description of the most recent details about evaluating the MLModel.

withMessage

public GetEvaluationResult withMessage(String message)

A description of the most recent details about evaluating the MLModel.

Parameters:

message - A description of the most recent details about evaluating the MLModel.

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; useful for testing and debugging.

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 GetEvaluationResult clone()

Overrides:

clone in class Object