splitBalanced

An <code>ExprsArray</code> object to split.

object

Specifies the percent of the total number
of subjects to include in the training set.

percent.include

Arguments passed to both <code>splitStratify</code> calls.

<code>splitBalance</code> is a wrapper that calls <code>splitStratify</code>
 twice. In the first call, <code>splitStratify</code> is used to create a
 balanced training set from the total data. In the second call,
 <code>splitStratify</code> 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.

Supervised machine learning has an increasingly important role in data
analysis. This package introduces a framework for rapidly building and deploying
supervised machine learning in a high-throughput manner. This package provides a
user-friendly interface that empowers investigators to execute state-of-the-art
binary and multi-class classification, as well as regression, with minimal
programming experience necessary.

splitBalanced: Split by Balanced Sampling

Description

Usage

Arguments

Value