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Showing content from https://docs.aws.amazon.com/sdkforruby/api/Aws/MachineLearning/Types/Evaluation.html below:

Evaluation — AWS SDK for Ruby V2

You are viewing documentation for version 2 of the AWS SDK for Ruby. Version 3 documentation can be found here.

Class: Aws::MachineLearning::Types::Evaluation

Inherits:

Struct

Object
Struct
Aws::MachineLearning::Types::Evaluation

show all

Defined in:: (unknown)

Overview

Represents the output of GetEvaluation operation.

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

Instance Attribute Summary collapse

#compute_time ⇒ Integer Long integer type that is a 64-bit signed number. .
#created_at ⇒ Time The time that the Evaluation was created.
#created_by_iam_user ⇒ String The AWS user account that invoked the evaluation.
#evaluation_data_source_id ⇒ String The ID of the DataSource that is used to evaluate the MLModel.
#evaluation_id ⇒ String The ID that is assigned to the Evaluation at creation.
#finished_at ⇒ Time A timestamp represented in epoch time. .
#input_data_location_s3 ⇒ String The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
#last_updated_at ⇒ Time The time of the most recent edit to the Evaluation.
#message ⇒ String A description of the most recent details about evaluating the MLModel.
#ml_model_id ⇒ String The ID of the MLModel that is the focus of the evaluation.
#name ⇒ String A user-supplied name or description of the Evaluation.
#performance_metrics ⇒ Types::PerformanceMetrics Measurements of how well the MLModel performed, using observations referenced by the DataSource.
#started_at ⇒ Time A timestamp represented in epoch time. .
#status ⇒ String The status of the evaluation.

Instance Attribute Details #compute_time ⇒ Integer

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

#created_at ⇒ Time

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

#created_by_iam_user ⇒ String

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.

#evaluation_data_source_id ⇒ String

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

#evaluation_id ⇒ String

The ID that is assigned to the Evaluation at creation.

#finished_at ⇒ Time

A timestamp represented in epoch time.

#input_data_location_s3 ⇒ String

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

#last_updated_at ⇒ Time

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

#message ⇒ String

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

#ml_model_id ⇒ String

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

#name ⇒ String

A user-supplied name or description of the Evaluation.

#performance_metrics ⇒ Types::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.

#started_at ⇒ Time

A timestamp represented in epoch time.

#status ⇒ String

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.
Possible values:
- PENDING
- INPROGRESS
- FAILED
- COMPLETED
- DELETED

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