Fast Algorithms for Best Subset Selection

Highly optimized toolkit for approximately solving L0-regularized learning problems (aka best subset selection). The algorithms are based on coordinate descent and local combinatorial search. For more details, check the paper by Hazimeh and Mazumder (2018) ; the link is provided in the URL field below.


Reference manual

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1.2.0 by Hussein Hazimeh, a year ago

Browse source code at

Authors: Hussein Hazimeh , Rahul Mazumder

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, Matrix, methods, ggplot2, reshape2

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

See at CRAN