Class: Aws::SageMaker::Types::AutoMLJobConfig
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::AutoMLJobConfig
- Defined in:
- gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb
Overview
A collection of settings used for an AutoML job.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#candidate_generation_config ⇒ Types::AutoMLCandidateGenerationConfig
The configuration for generating a candidate for an AutoML job (optional).
-
#completion_criteria ⇒ Types::AutoMLJobCompletionCriteria
How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
-
#data_split_config ⇒ Types::AutoMLDataSplitConfig
The configuration for splitting the input training dataset.
-
#mode ⇒ String
The method that Autopilot uses to train the data.
-
#security_config ⇒ Types::AutoMLSecurityConfig
The security configuration for traffic encryption or Amazon VPC settings.
Instance Attribute Details
#candidate_generation_config ⇒ Types::AutoMLCandidateGenerationConfig
The configuration for generating a candidate for an AutoML job (optional).
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2410 class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end |
#completion_criteria ⇒ Types::AutoMLJobCompletionCriteria
How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2410 class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end |
#data_split_config ⇒ Types::AutoMLDataSplitConfig
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2410 class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end |
#mode ⇒ String
The method that Autopilot uses to train the data. You can either
specify the mode manually or let Autopilot choose for you based on
the dataset size by selecting AUTO
. In AUTO
mode, Autopilot
chooses ENSEMBLING
for datasets smaller than 100 MB, and
HYPERPARAMETER_TUNING
for larger ones.
The ENSEMBLING
mode uses a multi-stack ensemble model to predict
classification and regression tasks directly from your dataset. This
machine learning mode combines several base models to produce an
optimal predictive model. It then uses a stacking ensemble method to
combine predictions from contributing members. A multi-stack
ensemble model can provide better performance over a single model by
combining the predictive capabilities of multiple models. See
Autopilot algorithm support for a list of algorithms supported
by ENSEMBLING
mode.
The HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters
to train the best version of a model. HPO automatically selects an
algorithm for the type of problem you want to solve. Then HPO finds
the best hyperparameters according to your objective metric. See
Autopilot algorithm support for a list of algorithms supported
by HYPERPARAMETER_TUNING
mode.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2410 class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end |
#security_config ⇒ Types::AutoMLSecurityConfig
The security configuration for traffic encryption or Amazon VPC settings.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2410 class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end |