4.7 Article

FSelector: a Ruby gem for feature selection

Journal

BIOINFORMATICS
Volume 28, Issue 21, Pages 2851-2852

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts528

Keywords

-

Funding

  1. Intramural Research Program of the National Institutes of Health, National Library of Medicine

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available