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 |