KODAMA: an R package for knowledge discovery and data mining

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Abstract

Summary:

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.

Availability and Implementation:

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).

Contact:

s.cacciatore@imperial.ac.uk

Supplementary information:

Supplementary data are available at Bioinformatics online.

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