split

The <code>exprso</code> package includes these split modules:
- <code><a rd-options="" href="/link/splitSample?package=exprso&version=0.5.1" data-mini-rdoc="exprso::splitSample">splitSample</a></code>
- <code><a rd-options="" href="/link/splitStratify?package=exprso&version=0.5.1" data-mini-rdoc="exprso::splitStratify">splitStratify</a></code>
- <code><a rd-options="" href="/link/splitBalanced?package=exprso&version=0.5.1" data-mini-rdoc="exprso::splitBalanced">splitBalanced</a></code>
- <code><a rd-options="" href="/link/splitBoost?package=exprso&version=0.5.1" data-mini-rdoc="exprso::splitBoost">splitBoost</a></code>
- <code><a rd-options="" href="/link/splitBy?package=exprso&version=0.5.1" data-mini-rdoc="exprso::splitBy">splitBy</a></code>

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.

Thomas Quinn

exprso

Rapid Deployment of Machine Learning Algorithms

Daniel Tylee

Samuel Lee

split function

The <code>exprso</code> package includes these split modules:
- <code><a rd-options='' href='splitSample'>splitSample</a></code>
- <code><a rd-options='' href='splitStratify'>splitStratify</a></code>
- <code><a rd-options='' href='splitBalanced'>splitBalanced</a></code>
- <code><a rd-options='' href='splitBoost'>splitBoost</a></code>
- <code><a rd-options='' href='splitBy'>splitBy</a></code>

split: Split Data

Description

Arguments