# AutoMLDataSplitConfig
<a name="API_AutoMLDataSplitConfig"></a>

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.

## Contents
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 ** ValidationFraction **   <a name="sagemaker-Type-AutoMLDataSplitConfig-ValidationFraction"></a>
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.  
Type: Float  
Valid Range: Minimum value of 0. Maximum value of 1.  
Required: No

## See Also
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For more information about using this API in one of the language-specific AWS SDKs, see the following:
+  [AWS SDK for C\$1\$1](https://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/AutoMLDataSplitConfig) 
+  [AWS SDK for Java V2](https://docs.aws.amazon.com/goto/SdkForJavaV2/sagemaker-2017-07-24/AutoMLDataSplitConfig) 
+  [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/sagemaker-2017-07-24/AutoMLDataSplitConfig)