AutoMLDataSplitConfig - Amazon SageMaker


This structure specifies how to split the data into train and validation datasets. The validation and training datasets must contain the same headers. The validation dataset must be less than 2 GB in size.



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

For more information about using this API in one of the language-specific AWS SDKs, see the following: