splitBoost: Sample by Boosting

In exprso: Rapid Deployment of Machine Learning Algorithms

Description

splitBoost builds a training and validation set by randomly up-sampling (with replacement) the smaller of two classes. This results in an equal representation of each class in the training set. For example, given 30 cases and 3 controls, a 2/3 split would place 20 cases and 20 controls in the training set. Of these 20 controls, only 2 are unique. The test set is not boosted. In this example, the test set would contain 10 cases and 1 control.

Usage

splitBoost(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 (i.e., based on the larger group). Subjects from the smaller group are up-sampled to match this number.

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