KODAMA: Knowledge Discovery by Accuracy Maximization

An unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data.

Version: 1.4
Depends: R (≥ 2.10.0), stats
Imports: Rcpp (≥ 0.12.4)
LinkingTo: Rcpp, RcppArmadillo
Suggests: rgl, knitr, rmarkdown
Published: 2017-01-17
Author: Stefano Cacciatore, Leonardo Tenori, Claudio Luchinat, Phillip R. Bennett, and David A. MacIntyre
Maintainer: Stefano Cacciatore <tkcaccia at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: KODAMA results

Downloads:

Reference manual: KODAMA.pdf
Vignettes: Knowledge Discovery by Accuracy Maximization
Package source: KODAMA_1.4.tar.gz
Windows binaries: r-devel: KODAMA_1.4.zip, r-release: KODAMA_1.4.zip, r-oldrel: KODAMA_1.4.zip
OS X El Capitan binaries: r-release: KODAMA_1.4.tgz
OS X Mavericks binaries: r-oldrel: KODAMA_1.4.tgz
Old sources: KODAMA archive

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