exprso: Rapid Implementation of Machine Learning Algorithms for Genomic Data
Version 0.1.8

Supervised machine learning has an increasingly important role in biological studies. However, the sheer complexity of classification pipelines poses a significant barrier to the expert biologist unfamiliar with machine learning. Moreover, many biologists lack the time or technical skills necessary to establish their own pipelines. This package introduces a framework for the rapid implementation of high-throughput supervised machine learning built with the biologist user in mind. Written by biologists, for biologists, 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.

Package details

AuthorThomas Quinn [aut, cre], Daniel Tylee [ctb]
Date of publication2016-12-23 17:35:21
MaintainerThomas Quinn <[email protected]>
URL http://github.com/tpq/exprso
Package repositoryView on CRAN
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exprso documentation built on May 29, 2017, 9:13 a.m.