A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
Motivation With the growth of big data, variable selection has become one of the critical challenges in statistics. Although many methods have been proposed in the literature their performance in terms of recall (sensitivity) and precision (PPV) is limited in a context where the number of variables by far exceeds the number of observations or in a highly correlated setting. Results In this article, we propose a general algorithm which improves the precision of any existing variable selectiondoi:10.1093/bioinformatics/btaa855 pmid:33016991 pmcid:PMC8097688 fatcat:u6efdyuptfemtcfxrz2yqfo2f4