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

Inherits:
Struct
  • Object
show all
Defined in:
gems/aws-sdk-machinelearning/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 collapse

SENSITIVE =
[]

Instance Attribute Summary collapse

Instance Attribute Details

#compute_timeInteger

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

Returns:

  • (Integer)


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# File 'gems/aws-sdk-machinelearning/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_atTime

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

Returns:

  • (Time)


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# File 'gems/aws-sdk-machinelearning/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_userString

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)


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# File 'gems/aws-sdk-machinelearning/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_idString

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

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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_idString

The ID that is assigned to the Evaluation at creation.

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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_atTime

A timestamp represented in epoch time.

Returns:

  • (Time)


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# File 'gems/aws-sdk-machinelearning/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_s3String

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

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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_atTime

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

Returns:

  • (Time)


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# File 'gems/aws-sdk-machinelearning/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

#messageString

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

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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_idString

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

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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

#nameString

A user-supplied name or description of the Evaluation.

Returns:

  • (String)


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# File 'gems/aws-sdk-machinelearning/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_metricsTypes::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.



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# File 'gems/aws-sdk-machinelearning/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_atTime

A timestamp represented in epoch time.

Returns:

  • (Time)


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# File 'gems/aws-sdk-machinelearning/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

#statusString

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)


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# File 'gems/aws-sdk-machinelearning/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