Class: Aws::SageMaker::Types::AutoMLDataSplitConfig
- Inherits:
 - 
      Struct
      
        
- Object
 - Struct
 - Aws::SageMaker::Types::AutoMLDataSplitConfig
 
 
- Includes:
 - Aws::Structure
 
- Defined in:
 - lib/aws-sdk-sagemaker/types.rb
 
Overview
This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling ‘CreateAutoMLJob`, the validation dataset must be less than 2 GB in size.
Constant Summary collapse
- SENSITIVE =
 []
Instance Attribute Summary collapse
- 
  
    
      #validation_fraction  ⇒ Float 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    
The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation.
 
Instance Attribute Details
#validation_fraction ⇒ Float
The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
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      # File 'lib/aws-sdk-sagemaker/types.rb', line 2234 class AutoMLDataSplitConfig < Struct.new( :validation_fraction) SENSITIVE = [] include Aws::Structure end  |