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rare  

Linear Model with Tree-Based Lasso Regularization for Rare Features
View on CRAN: Click here


Download and install rare package within the R console
Install from CRAN:
install.packages("rare")

Install from Github:
library("remotes")
install_github("cran/rare")

Install by package version:
library("remotes")
install_version("rare", "0.1.2")



Attach the package and use:
library("rare")
Maintained by
Xiaohan Yan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-22
Latest Update: 2025-06-16
Description:
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) . 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.
How to cite:
Xiaohan Yan (2018). rare: Linear Model with Tree-Based Lasso Regularization for Rare Features. R package version 0.1.2, https://cran.r-project.org/web/packages/rare. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1.0 (2018-03-22 11:05), 0.1.1 (2018-08-03 18:50)
Other packages that cited rare R package
View rare citation profile
Other R packages that rare depends, imports, suggests or enhances
Complete documentation for rare
Functions, R codes and Examples using the rare R package
Some associated functions: data.dtm . data.hc . data.rating . find.leaves . group.plot . group.recover . rare-package . rarefit.cv . rarefit . rarefit.predict . tree.matrix . 
Some associated R codes: RcppExports.R . rare-package.R . rare.cv.R . rare.data.R . rare.fit.R . rare.group.R .  Full rare package functions and examples
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