java/README.md
In rmcfs: The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data.

Weka12 is a slightly modified Weka 3.6.10. All changes are necessary to work with Java implementation of MCFS-ID. Weka12 project is publicly available on bitbucket: https://bitbucket.org/mdraminski/weka12.

Original Weka project is available here: http://www.cs.waikato.ac.nz/ml/weka/

For more information about Weka data mining tool in Java please look here: Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten (2009); The WEKA Data Mining Software: An Update; SIGKDD Explorations, Volume 11, Issue 1.

Colt Java project provides a set of Open Source Libraries for High Performance Scientific and Technical Computing in Java. Source code is available here: https://dst.lbl.gov/ACSSoftware/colt/

JDistlib (Java library of statistical distribution) is a Java package that provides routines for various statistical distributions. Source code is available here: https://sourceforge.net/projects/jdistlib/