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:
  • Constructor Details

    • GetEvaluationResult

      public GetEvaluationResult()
  • Method Details

    • 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:
    • 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:
    • 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:
    • 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:
    • 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:
    • 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:
    • 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