rare: Linear Model with Tree-Based Lasso Regularization for Rare Features

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2018) <arXiv:1803.06675>. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

Version: 0.1.0
Depends: R (≥ 3.2.1)
Imports: Matrix, glmnet, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, dendextend, rmarkdown
Published: 2018-03-22
Author: Xiaohan Yan [aut, cre], Jacob Bien [aut, cre]
Maintainer: Xiaohan Yan <xy257 at cornell.edu>
BugReports: https://github.com/yanxht/rare/issues
License: GPL-3
URL: https://github.com/yanxht/rare
NeedsCompilation: yes
CRAN checks: rare results

Downloads:

Reference manual: rare.pdf
Vignettes: Using the rare package
Package source: rare_0.1.0.tar.gz
Windows binaries: r-prerel: rare_0.1.0.zip, r-release: rare_0.1.0.zip, r-oldrel: rare_0.1.0.zip
OS X binaries: r-prerel: rare_0.1.0.tgz, r-release: rare_0.1.0.tgz

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