Evaluation (AWS SDK For Java for OSGi 1.10.1 API)

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

All Implemented Interfaces:

Serializable, Cloneable
```
public class Evaluation
extends Object
implements Serializable, Cloneable
```
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

Methods
Modifier and Type	Method and Description
`Evaluation`	`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 ID of the `DataSource` that is used to evaluate the `MLModel`.
`String`	`getEvaluationId()` The ID that is assigned to the `Evaluation` at creation.
`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`.
`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 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`	`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`	`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.
`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`	`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`	`withStatus(EntityStatus status)` The status of the evaluation.
`Evaluation`	`withStatus(String status)` The status of the evaluation.

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

- Constructor Detail
  - Evaluation
```
public Evaluation()
```
- Method Detail
  - getEvaluationId
```
public String getEvaluationId()
```
    The ID that is assigned to the Evaluation at creation.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Returns:
    The ID that is assigned to the Evaluation at creation.
  - setEvaluationId
```
public void setEvaluationId(String evaluationId)
```
    The ID that is assigned to the Evaluation at creation.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    evaluationId - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    evaluationId - The ID that is assigned to the Evaluation at creation.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - getMLModelId
```
public String getMLModelId()
```
    The ID of the MLModel that is the focus of the evaluation.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Returns:
    The ID of the MLModel that is the focus of the evaluation.
  - setMLModelId
```
public void setMLModelId(String mLModelId)
```
    The ID of the MLModel that is the focus of the evaluation.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    mLModelId - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    mLModelId - The ID of the MLModel that is the focus of the evaluation.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - getEvaluationDataSourceId
```
public String getEvaluationDataSourceId()
```
    The ID of the DataSource that is used to evaluate the MLModel.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Returns:
    The ID of the DataSource that is used to evaluate the MLModel.
  - setEvaluationDataSourceId
```
public void setEvaluationDataSourceId(String evaluationDataSourceId)
```
    The ID of the DataSource that is used to evaluate the MLModel.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    evaluationDataSourceId - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 1 - 64
    Pattern: [a-zA-Z0-9_.-]+
    
    Parameters:
    evaluationDataSourceId - The ID of the DataSource that is used to evaluate the MLModel.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - getInputDataLocationS3
```
public String getInputDataLocationS3()
```
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    Constraints:
    Length: 0 - 2048
    Pattern: s3://([^/]+)(/.*)?
    
    Returns:
    The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
  - 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.
    Constraints:
    Length: 0 - 2048
    Pattern: s3://([^/]+)(/.*)?
    
    Parameters:
    inputDataLocationS3 - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 0 - 2048
    Pattern: s3://([^/]+)(/.*)?
    
    Parameters:
    inputDataLocationS3 - The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - 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.
    Constraints:
    Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))
    
    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.
  - 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.
    Constraints:
    Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))
    
    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.
  - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))
    
    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:
    A reference to this updated object so that method calls can be chained together.
  - 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.
  - 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.
  - withCreatedAt
```
public Evaluation withCreatedAt(Date createdAt)
```
    The time that the Evaluation was created. The time is expressed in epoch time.
    Returns a reference to this object so that method calls can be chained together.
    
    Parameters:
    createdAt - The time that the Evaluation was created. The time is expressed in epoch time.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - 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.
  - 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.
  - withLastUpdatedAt
```
public Evaluation withLastUpdatedAt(Date lastUpdatedAt)
```
    The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
    Returns a reference to this object so that method calls can be chained together.
    
    Parameters:
    lastUpdatedAt - The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - getName
```
public String getName()
```
    A user-supplied name or description of the Evaluation.
    Constraints:
    Length: 0 - 1024
    Pattern: .*\S.*|^$
    
    Returns:
    A user-supplied name or description of the Evaluation.
  - setName
```
public void setName(String name)
```
    A user-supplied name or description of the Evaluation.
    Constraints:
    Length: 0 - 1024
    Pattern: .*\S.*|^$
    
    Parameters:
    name - A user-supplied name or description of the Evaluation.
  - withName
```
public Evaluation withName(String name)
```
    A user-supplied name or description of the Evaluation.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 0 - 1024
    Pattern: .*\S.*|^$
    
    Parameters:
    name - A user-supplied name or description of the Evaluation.
    
    Returns:
    A reference to this updated object so that method calls can be chained together.
  - 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.
    Constraints:
    Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    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
  - 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.
    Constraints:
    Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    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(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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    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:
    A reference to this updated 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.
    Constraints:
    Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    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:
    A reference to this updated object so that method calls can be chained together.
    See Also:
    EntityStatus
  - 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.
  - 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.
  - 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.
    Returns a reference to this object so that method calls can be chained together.
    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:
    A reference to this updated object so that method calls can be chained together.
  - getMessage
```
public String getMessage()
```
    A description of the most recent details about evaluating the MLModel.
    Constraints:
    Length: 0 - 10240
    
    Returns:
    A description of the most recent details about evaluating the MLModel.
  - setMessage
```
public void setMessage(String message)
```
    A description of the most recent details about evaluating the MLModel.
    Constraints:
    Length: 0 - 10240
    
    Parameters:
    message - 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.
    Returns a reference to this object so that method calls can be chained together.
    Constraints:
    Length: 0 - 10240
    
    Parameters:
    message - A description of the most recent details about evaluating the MLModel.
    
    Returns:
    A reference to this updated 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()
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - clone
```
public Evaluation clone()
```
    Overrides:
    
    clone in class Object

Class Evaluation

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Evaluation

Method Detail

getEvaluationId

setEvaluationId

withEvaluationId

getMLModelId

setMLModelId

withMLModelId

getEvaluationDataSourceId

setEvaluationDataSourceId

withEvaluationDataSourceId

getInputDataLocationS3

setInputDataLocationS3

withInputDataLocationS3

getCreatedByIamUser

setCreatedByIamUser

withCreatedByIamUser

getCreatedAt

setCreatedAt

withCreatedAt

getLastUpdatedAt

setLastUpdatedAt

withLastUpdatedAt

getName

setName

withName

getStatus

setStatus

withStatus

setStatus

withStatus

getPerformanceMetrics

setPerformanceMetrics

withPerformanceMetrics

getMessage

setMessage

withMessage

toString

hashCode

equals

clone