KODAMA: Knowledge discovery by accuracy maximization

KODAMA (KnOwledge Discovery by Accuracy MAximization) is an unsupervised and semisupervised learning algorithm that performs feature extraction from noisy and high-dimensional data.

Version: 0.0.1
Depends: R (≥ 2.10.0), e1071, plsgenomics, class
Suggests: rgl
Published: 2014-11-25
Author: Stefano Cacciatore, Claudio Luchinat, Leonardo Tenori
Maintainer: Stefano Cacciatore <tkcaccia at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: KODAMA results


Reference manual: KODAMA.pdf
Package source: KODAMA_0.0.1.tar.gz
Windows binaries: r-devel: KODAMA_0.0.1.zip, r-release: KODAMA_0.0.1.zip, r-oldrel: KODAMA_0.0.1.zip
OS X Snow Leopard binaries: r-release: KODAMA_0.0.1.tgz, r-oldrel: not available
OS X Mavericks binaries: r-release: KODAMA_0.0.1.tgz