GetEvaluationOutput
public struct GetEvaluationOutput : AWSShape
Undocumented
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Declaration
Swift
public static var _members: [AWSShapeMember]
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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.
Declaration
Swift
public let computeTime: Int64?
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The time that the Evaluation was created. The time is expressed in epoch time.
Declaration
Swift
public let createdAt: TimeStamp?
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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.
Declaration
Swift
public let createdByIamUser: String?
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The DataSource used for this evaluation.
Declaration
Swift
public let evaluationDataSourceId: String?
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The evaluation ID which is same as the EvaluationId in the request.
Declaration
Swift
public let evaluationId: String?
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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.
Declaration
Swift
public let finishedAt: TimeStamp?
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The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
Declaration
Swift
public let inputDataLocationS3: String?
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The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
Declaration
Swift
public let lastUpdatedAt: TimeStamp?
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A link to the file that contains logs of the CreateEvaluation operation.
Declaration
Swift
public let logUri: String?
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A description of the most recent details about evaluating the MLModel.
Declaration
Swift
public let message: String?
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The ID of the MLModel that was the focus of the evaluation.
Declaration
Swift
public let mLModelId: String?
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A user-supplied name or description of the Evaluation.
Declaration
Swift
public let name: String?
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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.
Declaration
Swift
public let performanceMetrics: PerformanceMetrics?
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The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn’t available if the Evaluation is in the PENDING state.
Declaration
Swift
public let startedAt: TimeStamp?
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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.
Declaration
Swift
public let status: EntityStatus?
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init(computeTime:createdAt:createdByIamUser:evaluationDataSourceId:evaluationId:finishedAt:inputDataLocationS3:lastUpdatedAt:logUri:message:mLModelId:name:performanceMetrics:startedAt:status:)
Undocumented
Declaration
Swift
public init(computeTime: Int64? = nil, createdAt: TimeStamp? = nil, createdByIamUser: String? = nil, evaluationDataSourceId: String? = nil, evaluationId: String? = nil, finishedAt: TimeStamp? = nil, inputDataLocationS3: String? = nil, lastUpdatedAt: TimeStamp? = nil, logUri: String? = nil, message: String? = nil, mLModelId: String? = nil, name: String? = nil, performanceMetrics: PerformanceMetrics? = nil, startedAt: TimeStamp? = nil, status: EntityStatus? = nil)