Class GetEvaluationResult

    • 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 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:
        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.
      • 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