GetEvaluationResult (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceResult<ResponseMetadata>
- - com.amazonaws.services.machinelearning.model.GetEvaluationResult

All Implemented Interfaces:: Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class GetEvaluationResult
extends AmazonWebServiceResult<ResponseMetadata>
implements Serializable, Cloneable

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

See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

GetEvaluationResult()

Constructors
Constructor and Description
`GetEvaluationResult()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`GetEvaluationResult`	`clone()`
`boolean`	`equals(Object obj)`
`Long`	`getComputeTime()` The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the `Evaluation`, normalized and scaled on computation resources.
`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.
`Date`	`getFinishedAt()` The epoch time when Amazon Machine Learning marked the `Evaluation` as `COMPLETED` or `FAILED`.
`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 `Evaluation`.
`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`.
`Date`	`getStartedAt()` The epoch time when Amazon Machine Learning marked the `Evaluation` as `INPROGRESS`.
`String`	`getStatus()` The status of the evaluation.
`int`	`hashCode()`
`void`	`setComputeTime(Long computeTime)` The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the `Evaluation`, normalized and scaled on computation resources.
`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`	`setFinishedAt(Date finishedAt)` The epoch time when Amazon Machine Learning marked the `Evaluation` as `COMPLETED` or `FAILED`.
`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 `Evaluation`.
`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`	`setStartedAt(Date startedAt)` The epoch time when Amazon Machine Learning marked the `Evaluation` as `INPROGRESS`.
`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.
`GetEvaluationResult`	`withComputeTime(Long computeTime)` The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the `Evaluation`, normalized and scaled on computation resources.
`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`	`withFinishedAt(Date finishedAt)` The epoch time when Amazon Machine Learning marked the `Evaluation` as `COMPLETED` or `FAILED`.
`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 `Evaluation`.
`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`	`withStartedAt(Date startedAt)` The epoch time when Amazon Machine Learning marked the `Evaluation` as `INPROGRESS`.
`GetEvaluationResult`	`withStatus(EntityStatus status)` The status of the evaluation.
`GetEvaluationResult`	`withStatus(String status)` The status of the evaluation.

Methods inherited from class com.amazonaws.AmazonWebServiceResult
getSdkHttpMetadata, getSdkResponseMetadata, setSdkHttpMetadata, setSdkResponseMetadata

Methods inherited from class java.lang.Object
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 Evaluation. The time is expressed in epoch time.
    
    Parameters:
    
    lastUpdatedAt - The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
  - getLastUpdatedAt
```
public Date getLastUpdatedAt()
```
    The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
    
    Returns:
    
    The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
  - withLastUpdatedAt
```
public GetEvaluationResult withLastUpdatedAt(Date lastUpdatedAt)
```
    The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
    
    Parameters:
    
    lastUpdatedAt - The time of the most recent edit to the Evaluation. 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.
  - setComputeTime
```
public void setComputeTime(Long computeTime)
```
    The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
    
    Parameters:
    
    computeTime - The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
  - getComputeTime
```
public Long getComputeTime()
```
    The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
    
    Returns:
    
    The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
  - withComputeTime
```
public GetEvaluationResult withComputeTime(Long computeTime)
```
    The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
    
    Parameters:
    
    computeTime - The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setFinishedAt
```
public void setFinishedAt(Date finishedAt)
```
    The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
    
    Parameters:
    
    finishedAt - The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
  - getFinishedAt
```
public Date getFinishedAt()
```
    The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
    
    Returns:
    
    The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
  - withFinishedAt
```
public GetEvaluationResult withFinishedAt(Date finishedAt)
```
    The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
    
    Parameters:
    
    finishedAt - The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setStartedAt
```
public void setStartedAt(Date startedAt)
```
    The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.
    
    Parameters:
    
    startedAt - The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.
  - getStartedAt
```
public Date getStartedAt()
```
    The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.
    
    Returns:
    
    The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS . StartedAt isn't available if the Evaluation is in the PENDING state.
  - withStartedAt
```
public GetEvaluationResult withStartedAt(Date startedAt)
```
    The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.
    
    Parameters:
    
    startedAt - The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.
    
    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 GetEvaluationResult clone()
```
    Overrides:
    
    clone in class Object

AWS SDK for Java 1.x API Reference - 1.12.792

Class GetEvaluationResult

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.AmazonWebServiceResult

Methods inherited from class java.lang.Object

Constructor Detail

GetEvaluationResult

Method Detail

setEvaluationId

getEvaluationId

withEvaluationId

setMLModelId

getMLModelId

withMLModelId

setEvaluationDataSourceId

getEvaluationDataSourceId

withEvaluationDataSourceId

setInputDataLocationS3

getInputDataLocationS3

withInputDataLocationS3

setCreatedByIamUser

getCreatedByIamUser

withCreatedByIamUser

setCreatedAt

getCreatedAt

withCreatedAt

setLastUpdatedAt

getLastUpdatedAt

withLastUpdatedAt

setName

getName

withName

setStatus

getStatus

withStatus

setStatus

withStatus

setPerformanceMetrics

getPerformanceMetrics

withPerformanceMetrics

setLogUri

getLogUri

withLogUri

setMessage

getMessage

withMessage

setComputeTime

getComputeTime

withComputeTime

setFinishedAt

getFinishedAt

withFinishedAt

setStartedAt

getStartedAt

withStartedAt

toString

equals

hashCode

clone