title: FSelector: a Ruby gem for feature selection.
abstract: CONCLUSIONS
  The FSelector package contains a comprehensive list of feature selection algorithms for supporting bioinformatics and machine learning research. FSelector primarily collects and implements the filter type of feature selection techniques, which are computationally efficient for mining large datasets. In particular, FSelector allows ensemble feature selection that takes advantage of multiple feature selection algorithms to yield more robust results. FSelector also provides many useful auxiliary tools, including normalization, discretization and missing data imputation.
  
  
  BACKGROUND
  FSelector, written in the Ruby programming language, is free and open-source software that runs on all Ruby supporting platforms, including Windows, Linux and Mac OS X. FSelector is available from https://rubygems.org/gems/fselector and can be installed like a breeze via the command gem install fselector. The source code is available (https://github.com/need47/fselector) and is fully documented (http://rubydoc.info/gems/fselector/frames).
authors.affiliation: Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: Tiejun
authors.initials: T
authors.lastname: Cheng
authors.forename: Yanli
authors.initials: Y
authors.lastname: Wang
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Bryant
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D011381:Programming Languages; D012984:Software