Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Bioinformatics. 2012 Nov 1;28(21):2851-2. doi: 10.1093/bioinformatics/bts528. Epub 2012 Aug 31.
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.
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).
FSelector 包包含了一整套特征选择算法，用于支持生物信息学和机器学习研究。FSelector 主要收集和实现了过滤型特征选择技术，这些技术在挖掘大型数据集方面具有计算效率。特别是，FSelector 允许集成特征选择，利用多种特征选择算法来获得更稳健的结果。FSelector 还提供了许多有用的辅助工具，包括归一化、离散化和缺失数据插补。
FSelector 是用 Ruby 编程语言编写的免费开源软件，可在所有支持 Ruby 的平台上运行，包括 Windows、Linux 和 Mac OS X。FSelector 可从 https://rubygems.org/gems/fselector 获得，并可通过命令 gem install fselector 轻松安装。源代码可从 (https://github.com/need47/fselector) 获取，并且具有完整的文档 (http://rubydoc.info/gems/fselector/frames)。
