Class: Aws::SageMaker::Types::MetricDefinition

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::MetricDefinition

Includes:

Aws::Structure

Defined in:

lib/aws-sdk-sagemaker/types.rb

Overview

Specifies a metric that the training algorithm writes to ‘stderr` or `stdout`. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the

TuningObjective][1

parameter in the

‘HyperParameterTrainingJobDefinition` API to evaluate job performance during hyperparameter tuning.

[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html#sagemaker-Type-HyperParameterTrainingJobDefinition-TuningObjective

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #name ⇒ String

  The name of the metric.

• #regex ⇒ String

  A regular expression that searches the output of a training job and gets the value of the metric.

Instance Attribute Details

#name ⇒ String

The name of the metric.

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 31746

class MetricDefinition < Struct.new(
  :name,
  :regex)
  SENSITIVE = []
  include Aws::Structure
end

#regex ⇒ String

A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see [Defining metrics and environment variables].

[1]: docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 31746

class MetricDefinition < Struct.new(
  :name,
  :regex)
  SENSITIVE = []
  include Aws::Structure
end