Bioconductor version: Release (3.6)
Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes.
Author: Camille Maumet <Rmagpie at gmail.com>, with contributions from C. Ambroise J. Zhu
Maintainer: Camille Maumet <Rmagpie at gmail.com>
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R Script | Rmagpie Examples | |
Reference Manual |
biocViews | Classification, Microarray, Software |
Version | 1.34.0 |
In Bioconductor since | BioC 2.4 (R-2.9) (9 years) |
License | GPL (>= 3) |
Depends | R (>= 2.6.1), Biobase(>= 2.5.5) |
Imports | Biobase(>= 2.5.5), e1071, graphics, grDevices, kernlab, methods, pamr, stats, utils |
LinkingTo | |
Suggests | xtable |
SystemRequirements | |
Enhances | |
URL | http://www.bioconductor.org/ |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | Rmagpie_1.34.0.tar.gz |
Windows Binary | Rmagpie_1.34.0.zip |
Mac OS X 10.11 (El Capitan) | Rmagpie_1.34.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/Rmagpie |
Package Short Url | http://bioconductor.org/packages/Rmagpie/ |
Package Downloads Report | Download Stats |
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