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: an R package for knowledge discovery and data mining / Cacciatore, Stefano; Tenori, Leonardo; Luchinat, Claudio; Bennett, Phillip R; Macintyre, David A.. - In: BIOINFORMATICS. - ISSN 1367-4803. - STAMPA. - 33:(2016), pp. 621-623. [10.1093/bioinformatics/btw705]
KODAMA: an R package for knowledge discovery and data mining
CACCIATORE, STEFANO;TENORI, LEONARDO;LUCHINAT, CLAUDIO;
2016
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.
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