Class: Aws::SageMaker::Types::CreateAutoMLJobRequest
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::CreateAutoMLJobRequest
- Includes:
- Aws::Structure
- Defined in:
- lib/aws-sdk-sagemaker/types.rb
Overview
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobObjective.html
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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 [ Amazon SageMaker Autopilot problem types].
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 4727 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 |