Class: Aws::SageMaker::Types::CreateAutoMLJobRequest

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::CreateAutoMLJobRequest

Defined in:

gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb

Overview

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #auto_ml_job_config ⇒ Types::AutoMLJobConfig

  A collection of settings used to configure an AutoML job.

• #auto_ml_job_name ⇒ String

  Identifies an Autopilot job.

• #auto_ml_job_objective ⇒ Types::AutoMLJobObjective

  Specifies a metric to minimize or maximize as the objective of a job.

• #generate_candidate_definitions_only ⇒ Boolean

  Generates possible candidates without training the models.

• #input_data_config ⇒ Array<Types::AutoMLChannel>

  An array of channel objects that describes the input data and its location.

• #model_deploy_config ⇒ Types::ModelDeployConfig

  Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

• #output_data_config ⇒ Types::AutoMLOutputDataConfig

  Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.

• #problem_type ⇒ String

  Defines the type of supervised learning problem available for the candidates.

• #role_arn ⇒ String

  The ARN of the role that is used to access the data.

• #tags ⇒ Array<Types::Tag>

  An array of key-value pairs.

Instance Attribute Details

#auto_ml_job_config ⇒ Types::AutoMLJobConfig

A collection of settings used to configure an AutoML job.

Returns:

• (Types::AutoMLJobConfig)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#auto_ml_job_name ⇒ String

Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#auto_ml_job_objective ⇒ Types::AutoMLJobObjective

Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.

Returns:

• (Types::AutoMLJobObjective)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#generate_candidate_definitions_only ⇒ Boolean

Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

Returns:

• (Boolean)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#input_data_config ⇒ Array<Types::AutoMLChannel>

An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

Returns:

• (Array<Types::AutoMLChannel>)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#model_deploy_config ⇒ Types::ModelDeployConfig

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Returns:

• (Types::ModelDeployConfig)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#output_data_config ⇒ Types::AutoMLOutputDataConfig

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

Returns:

• (Types::AutoMLOutputDataConfig)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#problem_type ⇒ String

Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#role_arn ⇒ String

The ARN of the role that is used to access the data.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end

#tags ⇒ Array<Types::Tag>

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

Returns:

• (Array<Types::Tag>)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 9823

class CreateAutoMLJobRequest < Struct.new(
  :auto_ml_job_name,
  :input_data_config,
  :output_data_config,
  :problem_type,
  :auto_ml_job_objective,
  :auto_ml_job_config,
  :role_arn,
  :generate_candidate_definitions_only,
  :tags,
  :model_deploy_config)
  SENSITIVE = []
  include Aws::Structure
end