Evaluation (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.machinelearning.model.Evaluation

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class Evaluation
extends Object
implements Serializable, Cloneable, StructuredPojo
```
Represents the output of GetEvaluation operation.

The content consists of the detailed metadata and data file information and the current status of the Evaluation.

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor and Description

Evaluation()

Constructors
Constructor and Description
`Evaluation()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Evaluation`	`clone()`
`boolean`	`equals(Object obj)`
`Long`	`getComputeTime()`
`Date`	`getCreatedAt()` The time that the `Evaluation` was created.
`String`	`getCreatedByIamUser()` The AWS user account that invoked the evaluation.
`String`	`getEvaluationDataSourceId()` The ID of the `DataSource` that is used to evaluate the `MLModel`.
`String`	`getEvaluationId()` The ID that is assigned to the `Evaluation` at creation.
`Date`	`getFinishedAt()`
`String`	`getInputDataLocationS3()` The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
`Date`	`getLastUpdatedAt()` The time of the most recent edit to the `Evaluation`.
`String`	`getMessage()` A description of the most recent details about evaluating the `MLModel`.
`String`	`getMLModelId()` The ID of the `MLModel` that is 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()`
`String`	`getStatus()` The status of the evaluation.
`int`	`hashCode()`
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setComputeTime(Long computeTime)`
`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 ID of the `DataSource` that is used to evaluate the `MLModel`.
`void`	`setEvaluationId(String evaluationId)` The ID that is assigned to the `Evaluation` at creation.
`void`	`setFinishedAt(Date finishedAt)`
`void`	`setInputDataLocationS3(String inputDataLocationS3)` The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
`void`	`setLastUpdatedAt(Date lastUpdatedAt)` The time of the most recent edit to the `Evaluation`.
`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 is 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)`
`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.
`Evaluation`	`withComputeTime(Long computeTime)`
`Evaluation`	`withCreatedAt(Date createdAt)` The time that the `Evaluation` was created.
`Evaluation`	`withCreatedByIamUser(String createdByIamUser)` The AWS user account that invoked the evaluation.
`Evaluation`	`withEvaluationDataSourceId(String evaluationDataSourceId)` The ID of the `DataSource` that is used to evaluate the `MLModel`.
`Evaluation`	`withEvaluationId(String evaluationId)` The ID that is assigned to the `Evaluation` at creation.
`Evaluation`	`withFinishedAt(Date finishedAt)`
`Evaluation`	`withInputDataLocationS3(String inputDataLocationS3)` The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
`Evaluation`	`withLastUpdatedAt(Date lastUpdatedAt)` The time of the most recent edit to the `Evaluation`.
`Evaluation`	`withMessage(String message)` A description of the most recent details about evaluating the `MLModel`.
`Evaluation`	`withMLModelId(String mLModelId)` The ID of the `MLModel` that is the focus of the evaluation.
`Evaluation`	`withName(String name)` A user-supplied name or description of the `Evaluation`.
`Evaluation`	`withPerformanceMetrics(PerformanceMetrics performanceMetrics)` Measurements of how well the `MLModel` performed, using observations referenced by the `DataSource`.
`Evaluation`	`withStartedAt(Date startedAt)`
`Evaluation`	`withStatus(EntityStatus status)` The status of the evaluation.
`Evaluation`	`withStatus(String status)` The status of the evaluation.

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - Evaluation
```
public Evaluation()
```
- Method Detail
  - setEvaluationId
```
public void setEvaluationId(String evaluationId)
```
    The ID that is assigned to the Evaluation at creation.
    
    Parameters:
    
    evaluationId - The ID that is assigned to the Evaluation at creation.
  - getEvaluationId
```
public String getEvaluationId()
```
    The ID that is assigned to the Evaluation at creation.
    
    Returns:
    
    The ID that is assigned to the Evaluation at creation.
  - withEvaluationId
```
public Evaluation withEvaluationId(String evaluationId)
```
    The ID that is assigned to the Evaluation at creation.
    
    Parameters:
    
    evaluationId - The ID that is assigned to the Evaluation at creation.
    
    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 is the focus of the evaluation.
    
    Parameters:
    
    mLModelId - The ID of the MLModel that is the focus of the evaluation.
  - getMLModelId
```
public String getMLModelId()
```
    The ID of the MLModel that is the focus of the evaluation.
    
    Returns:
    
    The ID of the MLModel that is the focus of the evaluation.
  - withMLModelId
```
public Evaluation withMLModelId(String mLModelId)
```
    The ID of the MLModel that is the focus of the evaluation.
    
    Parameters:
    
    mLModelId - The ID of the MLModel that is 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 ID of the DataSource that is used to evaluate the MLModel.
    
    Parameters:
    
    evaluationDataSourceId - The ID of the DataSource that is used to evaluate the MLModel.
  - getEvaluationDataSourceId
```
public String getEvaluationDataSourceId()
```
    The ID of the DataSource that is used to evaluate the MLModel.
    
    Returns:
    
    The ID of the DataSource that is used to evaluate the MLModel.
  - withEvaluationDataSourceId
```
public Evaluation withEvaluationDataSourceId(String evaluationDataSourceId)
```
    The ID of the DataSource that is used to evaluate the MLModel.
    
    Parameters:
    
    evaluationDataSourceId - The ID of the DataSource that is used to evaluate the MLModel.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setInputDataLocationS3
```
public void setInputDataLocationS3(String inputDataLocationS3)
```
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    
    Parameters:
    
    inputDataLocationS3 - The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
  - getInputDataLocationS3
```
public String getInputDataLocationS3()
```
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    
    Returns:
    
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
  - withInputDataLocationS3
```
public Evaluation withInputDataLocationS3(String inputDataLocationS3)
```
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    
    Parameters:
    
    inputDataLocationS3 - The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    
    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 Evaluation 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 Evaluation 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 Evaluation 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 Evaluation 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 Learning (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 Learning (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 Learning (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 Learning (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 Evaluation withStatus(String status)
```
    The status of the evaluation. This element can have one of the following values:
    - PENDING - Amazon Machine Learning (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 Learning (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 Learning (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 Learning (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 Evaluation withStatus(EntityStatus status)
```
    The status of the evaluation. This element can have one of the following values:
    - PENDING - Amazon Machine Learning (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 Learning (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 metrics 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 metrics 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 metrics 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 metrics 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 Evaluation withPerformanceMetrics(PerformanceMetrics performanceMetrics)
```
    Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics 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 metrics 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.
  - 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 Evaluation 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)
```
    Parameters:
    
    computeTime -
  - getComputeTime
```
public Long getComputeTime()
```
    Returns:
  - withComputeTime
```
public Evaluation withComputeTime(Long computeTime)
```
    Parameters:
    
    computeTime -
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setFinishedAt
```
public void setFinishedAt(Date finishedAt)
```
    Parameters:
    
    finishedAt -
  - getFinishedAt
```
public Date getFinishedAt()
```
    Returns:
  - withFinishedAt
```
public Evaluation withFinishedAt(Date finishedAt)
```
    Parameters:
    
    finishedAt -
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setStartedAt
```
public void setStartedAt(Date startedAt)
```
    Parameters:
    
    startedAt -
  - getStartedAt
```
public Date getStartedAt()
```
    Returns:
  - withStartedAt
```
public Evaluation withStartedAt(Date startedAt)
```
    Parameters:
    
    startedAt -
    
    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 Evaluation 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.

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Class Evaluation

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Evaluation

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

setMessage

getMessage

withMessage

setComputeTime

getComputeTime

withComputeTime

setFinishedAt

getFinishedAt

withFinishedAt

setStartedAt

getStartedAt

withStartedAt

toString

equals

hashCode

clone

marshall