Evaluation

import type { Evaluation } from "https://aws-api.deno.dev/v0.3/services/machinelearning.ts?docs=full";

Represents the output of GetEvaluation operation.

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

interface Evaluation {

ComputeTime?: number | null;

CreatedAt?: Date | number | null;

CreatedByIamUser?: string | null;

EvaluationDataSourceId?: string | null;

EvaluationId?: string | null;

FinishedAt?: Date | number | null;

InputDataLocationS3?: string | null;

LastUpdatedAt?: Date | number | null;

Message?: string | null;

MLModelId?: string | null;

Name?: string | null;

PerformanceMetrics?: PerformanceMetrics | null;

StartedAt?: Date | number | null;

Status?: EntityStatus | null;

}

§Properties

ComputeTime?: number | null

[src]

CreatedAt?: Date | number | null

[src]

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

CreatedByIamUser?: string | null

[src]

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.

EvaluationDataSourceId?: string | null

[src]

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

EvaluationId?: string | null

[src]

The ID that is assigned to the Evaluation at creation.

FinishedAt?: Date | number | null

[src]

InputDataLocationS3?: string | null

[src]

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

LastUpdatedAt?: Date | number | null

[src]

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

Message?: string | null

[src]

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

MLModelId?: string | null

[src]

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

Name?: string | null

[src]

A user-supplied name or description of the Evaluation.

PerformanceMetrics?: PerformanceMetrics | null

[src]

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.

StartedAt?: Date | number | null

[src]

Status?: EntityStatus | null

[src]

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.