To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("CMA")
In most cases, you don't need to download the package archive at all.
Bioconductor version: Release (3.1)
This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.
Author: Martin Slawski <ms at cs.uni-sb.de>, Anne-Laure Boulesteix <boulesteix at ibe.med.uni-muenchen.de>, Christoph Bernau <bernau at ibe.med.uni-muenchen.de>.
Maintainer: Christoph Bernau <bernau at ibe.med.uni-muenchen.de>
Citation (from within R,
enter citation("CMA")
):
To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("CMA")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CMA")
R Script | CMA_vignette.pdf | |
Reference Manual |
biocViews | Classification, DecisionTree, Software |
Version | 1.26.0 |
In Bioconductor since | BioC 2.3 (R-2.8) (7 years) |
License | GPL (>= 2) |
Depends | R (>= 2.10), methods, stats, Biobase |
Imports | |
LinkingTo | |
Suggests | MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma, st, mvtnorm |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | CMA_1.26.0.tar.gz |
Windows Binary | CMA_1.26.0.zip |
Mac OS X 10.6 (Snow Leopard) | CMA_1.26.0.tgz |
Mac OS X 10.9 (Mavericks) | CMA_1.26.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/CMA/tree/release-3.1 |
Package Short Url | http://bioconductor.org/packages/CMA/ |
Package Downloads Report | Download Stats |
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