Bioconductor version: 2.6
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>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("CMA")
To cite this package in a publication, start R and enter:
citation("CMA")
R Script | CMA_vignette.pdf | |
Reference Manual |
biocViews | Statistics, Classification |
Depends | R (>= 2.5.1), methods, stats, Biobase |
Imports | |
Suggests | MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma |
System Requirements | |
License | GPL (>= 2) |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Version | 1.6.0 |
Since | Bioconductor 2.3 (R-2.8) |
Package Source | CMA_1.6.0.tar.gz |
Windows Binary | CMA_1.6.0.zip (32- & 64-bit) |
MacOS 10.5 (Leopard) binary | CMA_1.6.0.tgz |
Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
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