Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
FSelector: a Ruby gem for feature selection. |
| Συγγραφείς: |
Cheng, Tiejun1, Wang, Yanli1, Bryant, Stephen H.1 |
| Πηγή: |
Bioinformatics. Nov2012, Vol. 28 Issue 21, p2851-2852. 2p. |
| Θεματικοί όροι: |
*Ruby (Computer program language), *Feature selection, *Missing data (Statistics), *Bioinformatics, *Machine learning, *Computational biology, *Open source software |
| Περίληψη: |
Summary: 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.Availability: 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).Contact: ywang@ncbi.nlm.nih.gov or bryant@ncbi.nlm.nih.govSupplementary Information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: |
Academic Search Index |