splitBalanced: Split by Balanced Sampling

In exprso: Rapid Deployment of Machine Learning Algorithms

Description

splitBalance is a wrapper that calls splitStratify twice. In the first call, splitStratify is used to create a balanced training set from the total data. In the second call, splitStratify is used to create a balanced validation set from the leftover data. This function ensures that there are always an equal number of samples from each class in the split.

Usage

splitBalanced(object, percent.include = 67, ...)

Arguments

object	An ExprsArray object to split.
percent.include	Specifies the percent of the total number of subjects to include in the training set.
...	Arguments passed to both splitStratify calls.

Value

Returns a list of two ExprsArray objects.

exprso documentation built on May 1, 2019, 7:11 p.m.