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
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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 6011 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 |