CMA

Synthesis of microarray-based classification

Bioconductor version: 2.10

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")

Documentation

PDF R Script CMA_vignette.pdf
PDF   Reference Manual

Details

biocViews Classification, Software
Depends R (>= 2.10), methods, stats, Biobase
Imports
Suggests MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma, st
System Requirements
License GPL (>= 2)
URL
Depends On Me
Imports Me
Suggests Me
Version 1.14.0
Since Bioconductor 2.3 (R-2.8)

Package Downloads

Package Source CMA_1.14.0.tar.gz
Windows Binary CMA_1.14.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary CMA_1.14.0.tgz
Package Downloads Report Download Stats

Workflows »

Common Bioconductor workflows include:

 

Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Fred Hutchinson Cancer Research Center