sagemaker/aws.sdk.kotlin.services.sagemaker.model/AutoMlDataSplitConfig

AutoMlDataSplitConfig

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.

Types

Builder

class Builder

Companion

object Companion

Properties

validationFraction

val validationFraction: 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.

Functions

copy

inline fun copy(block: AutoMlDataSplitConfig.Builder.() -> Unit = {}): AutoMlDataSplitConfig

equals

open operator override fun equals(other: Any?): Boolean

hashCode

open override fun hashCode(): Int

toString

open override fun toString(): String