Evaluation

public struct Evaluation : AWSShape

Undocumented

  • Declaration

    Swift

    public static var _members: [AWSShapeMember]

  • Undocumented

    Declaration

    Swift

    public let computeTime: Int64?

  • The time that the Evaluation was created. The time is expressed in epoch time.

    Declaration

    Swift

    public let createdAt: TimeStamp?

  • 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?

  • The ID of the DataSource that is used to evaluate the MLModel.

    Declaration

    Swift

    public let evaluationDataSourceId: String?

  • The ID that is assigned to the Evaluation at creation.

    Declaration

    Swift

    public let evaluationId: String?

  • Undocumented

    Declaration

    Swift

    public let finishedAt: TimeStamp?

  • The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.

    Declaration

    Swift

    public let inputDataLocationS3: String?

  • The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

    Declaration

    Swift

    public let lastUpdatedAt: TimeStamp?

  • A description of the most recent details about evaluating the MLModel.

    Declaration

    Swift

    public let message: String?

  • The ID of the MLModel that is the focus of the evaluation.

    Declaration

    Swift

    public let mLModelId: String?

  • A user-supplied name or description of the Evaluation.

    Declaration

    Swift

    public let name: String?

  • 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.

    Declaration

    Swift

    public let performanceMetrics: PerformanceMetrics?

  • Undocumented

    Declaration

    Swift

    public let startedAt: TimeStamp?

  • 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.

    Declaration

    Swift

    public let status: EntityStatus?

  • 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, message: String? = nil, mLModelId: String? = nil, name: String? = nil, performanceMetrics: PerformanceMetrics? = nil, startedAt: TimeStamp? = nil, status: EntityStatus? = nil)