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

Inherits:

Struct

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

Includes:

Structure

Defined in:

lib/aws-sdk-machinelearning/types.rb

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`.

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #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.

Returns:

• (Integer)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#created_at ⇒ Time

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

Returns:

• (Time)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#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.

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#evaluation_data_source_id ⇒ String

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

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#evaluation_id ⇒ String

The ID that is assigned to the ‘Evaluation` at creation.

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#finished_at ⇒ Time

A timestamp represented in epoch time.

Returns:

• (Time)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#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.

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#last_updated_at ⇒ Time

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

Returns:

• (Time)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#message ⇒ String

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

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#ml_model_id ⇒ String

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

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#name ⇒ String

A user-supplied name or description of the ‘Evaluation`.

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#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].

[1]: docs.aws.amazon.com/machine-learning/latest/dg

Returns:

• (Types::PerformanceMetrics)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#started_at ⇒ Time

A timestamp represented in epoch time.

Returns:

• (Time)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#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.

Returns:

• (String)

# File 'lib/aws-sdk-machinelearning/types.rb', line 1670

class Evaluation < Struct.new(
  :evaluation_id,
  :ml_model_id,
  :evaluation_data_source_id,
  :input_data_location_s3,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :performance_metrics,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end