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# AWS::SageMaker::AutoMLJob AutoMLDataSplitConfig
<a name="aws-properties-sagemaker-automljob-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.

## Syntax
<a name="aws-properties-sagemaker-automljob-automldatasplitconfig-syntax"></a>

To declare this entity in your Amazon CloudFormation template, use the following syntax:

### JSON
<a name="aws-properties-sagemaker-automljob-automldatasplitconfig-syntax.json"></a>

```
{
  "[ValidationFraction](#cfn-sagemaker-automljob-automldatasplitconfig-validationfraction)" : {{Number}}
}
```

### YAML
<a name="aws-properties-sagemaker-automljob-automldatasplitconfig-syntax.yaml"></a>

```
  [ValidationFraction](#cfn-sagemaker-automljob-automldatasplitconfig-validationfraction): {{Number}}
```

## Properties
<a name="aws-properties-sagemaker-automljob-automldatasplitconfig-properties"></a>

`ValidationFraction`  <a name="cfn-sagemaker-automljob-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.  
*Required*: No  
*Type*: Number  
*Minimum*: `0`  
*Maximum*: `1`  
*Update requires*: [Replacement](https://docs.amazonaws.cn/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-update-behaviors.html#update-replacement)