Evaluation - MachineLearning

Evaluation

Represents the output of GetEvaluation operation.

The content consists of the detailed metadata and data file information and the current status of the Evaluation.

Contents

ComputeTime

Long integer type that is a 64-bit signed number.

Type: Long

Required: No

CreatedAt

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

Type: Timestamp

Required: No

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.

Type: String

Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))

Required: No

EvaluationDataSourceId

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

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+

Required: No

EvaluationId

The ID that is assigned to the Evaluation at creation.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+

Required: No

FinishedAt

A timestamp represented in epoch time.

Type: Timestamp

Required: No

InputDataLocationS3

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

Type: String

Length Constraints: Maximum length of 2048.

Pattern: s3://([^/]+)(/.*)?

Required: No

LastUpdatedAt

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

Type: Timestamp

Required: No

Message

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

Type: String

Length Constraints: Maximum length of 10240.

Required: No

MLModelId

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

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+

Required: No

Name

A user-supplied name or description of the Evaluation.

Type: String

Length Constraints: Maximum length of 1024.

Pattern: .*\S.*|^$

Required: No

PerformanceMetrics

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.

Type: PerformanceMetrics object

Required: No

StartedAt

A timestamp represented in epoch time.

Type: Timestamp

Required: No

Status

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.

Type: String

Valid Values: PENDING | INPROGRESS | FAILED | COMPLETED | DELETED

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: