KODAMA: an R package for knowledge discovery and data mining

Bioinformatics
Stefano CacciatoreDavid A MacIntyre

Abstract

KODAMA, a novel learning algorithm for unsupervised feature extraction, is specifically designed for analysing noisy and high-dimensional datasets. Here we present an R package of the algorithm with additional functions that allow improved interpretation of high-dimensional data. The package requires no additional software and runs on all major platforms. KODAMA is freely available from the R archive CRAN ( http://cran.r-project.org ). The software is distributed under the GNU General Public License (version 3 or later). s.cacciatore@imperial.ac.uk. Supplementary data are available at Bioinformatics online.

Citations

Apr 8, 2014·Proceedings of the National Academy of Sciences of the United States of America·Stefano CacciatoreLeonardo Tenori
Oct 18, 2014·Cancer Research·Carmen PrioloMassimo Loda

Related Concepts

Computer Software
Urinalysis
In Vivo NMR Spectroscopy
2-Dimensional
Unsupervised Machine Learning
Bio-Informatics
Computer Programs and Programming
Extraction
Analysis
R Programming Language

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