Interface GetEvaluationResponse.Builder

All Superinterfaces:
AwsResponse.Builder, Buildable, CopyableBuilder<GetEvaluationResponse.Builder,GetEvaluationResponse>, MachineLearningResponse.Builder, SdkBuilder<GetEvaluationResponse.Builder,GetEvaluationResponse>, SdkPojo, SdkResponse.Builder
Enclosing class:
GetEvaluationResponse
@Mutable @NotThreadSafe public static interface GetEvaluationResponse.Builder extends MachineLearningResponse.Builder, SdkPojo, CopyableBuilder<GetEvaluationResponse.Builder,GetEvaluationResponse>

  • Method Details

    • evaluationId

      GetEvaluationResponse.Builder evaluationId(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.

    • mlModelId

      GetEvaluationResponse.Builder mlModelId(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.

    • evaluationDataSourceId

      GetEvaluationResponse.Builder evaluationDataSourceId(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.

    • inputDataLocationS3

      GetEvaluationResponse.Builder inputDataLocationS3(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.

    • createdByIamUser

      GetEvaluationResponse.Builder createdByIamUser(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.

    • createdAt

      GetEvaluationResponse.Builder createdAt(Instant 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.

    • lastUpdatedAt

      GetEvaluationResponse.Builder lastUpdatedAt(Instant 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.

    • name

      GetEvaluationResponse.Builder name(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.

    • status

      GetEvaluationResponse.Builder status(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:

    • status

      GetEvaluationResponse.Builder status(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:

    • performanceMetrics

      GetEvaluationResponse.Builder performanceMetrics(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.

    • performanceMetrics

      default GetEvaluationResponse.Builder performanceMetrics(Consumer<PerformanceMetrics.Builder> 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.

      This is a convenience method that creates an instance of the PerformanceMetrics.Builder avoiding the need to create one manually via PerformanceMetrics.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to performanceMetrics(PerformanceMetrics).

      Parameters:
      performanceMetrics - a consumer that will call methods on PerformanceMetrics.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • logUri

      GetEvaluationResponse.Builder logUri(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.

    • message

      GetEvaluationResponse.Builder message(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.

    • computeTime

      GetEvaluationResponse.Builder computeTime(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.

    • finishedAt

      GetEvaluationResponse.Builder finishedAt(Instant 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.

    • startedAt

      GetEvaluationResponse.Builder startedAt(Instant 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.