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.
| Version: | 0.1.8 |
| Depends: | R (≥ 3.2.2), kernlab |
| Imports: | affy, Biobase, cluster, MASS, e1071, lattice, methods, mRMRe, nnet, pathClass, plyr, stats, randomForest, ROCR, sampling |
| Suggests: | GEOquery, h2o, golubEsets, knitr, limma, magrittr, rmarkdown, testthat |
| Published: | 2016-12-23 |
| Author: | Thomas Quinn [aut, cre], Daniel Tylee [ctb] |
| Maintainer: | Thomas Quinn <contacttomquinn at gmail.com> |
| BugReports: | http://github.com/tpq/exprso/issues |
| License: | GPL-2 |
| URL: | http://github.com/tpq/exprso |
| NeedsCompilation: | no |
| Citation: | exprso citation info |
| Materials: | README NEWS |
| CRAN checks: | exprso results |
| Reference manual: | exprso.pdf |
| Vignettes: |
Advanced Topics for the exprso Package The exprso Cheatsheet An Introduction to the exprso Package Use Disclaimer, Please Read |
| Package source: | exprso_0.1.8.tar.gz |
| Windows binaries: | r-devel: exprso_0.1.8.zip, r-release: exprso_0.1.8.zip, r-oldrel: exprso_0.1.8.zip |
| OS X El Capitan binaries: | r-release: exprso_0.1.8.tgz |
| OS X Mavericks binaries: | r-oldrel: exprso_0.1.8.tgz |
| Old sources: | exprso archive |
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