The <code>exprso</code> package includes these data process modules:
- <code><a rd-options="" href="/link/modSubset?package=exprso&version=0.2.0" data-mini-rdoc="exprso::modSubset">modSubset</a></code>
- <code><a rd-options="" href="/link/modFilter?package=exprso&version=0.2.0" data-mini-rdoc="exprso::modFilter">modFilter</a></code>
- <code><a rd-options="" href="/link/modTransform?package=exprso&version=0.2.0" data-mini-rdoc="exprso::modTransform">modTransform</a></code>
- <code><a rd-options="" href="/link/modNormalize?package=exprso&version=0.2.0" data-mini-rdoc="exprso::modNormalize">modNormalize</a></code>
- <code><a rd-options="" href="/link/modTMM?package=exprso&version=0.2.0" data-mini-rdoc="exprso::modTMM">modTMM</a></code>

Supervised machine learning has an increasingly important role in data
analysis. This package introduces a framework for rapidly implementing 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, including deep learning, with minimal programming
experience necessary.

Thomas Quinn

exprso

Rapid Implementation of Machine Learning Algorithms for Genomic
Data

Daniel Tylee

mod function

The <code>exprso</code> package includes these data process modules:
- <code><a rd-options='' href='modSubset'>modSubset</a></code>
- <code><a rd-options='' href='modFilter'>modFilter</a></code>
- <code><a rd-options='' href='modTransform'>modTransform</a></code>
- <code><a rd-options='' href='modNormalize'>modNormalize</a></code>
- <code><a rd-options='' href='modTMM'>modTMM</a></code>

mod: Process Data

Description

Arguments