Package: rare 0.1.2

Xiaohan Yan

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 (2020) <doi:10.1080/01621459.2020.1796677>. 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.

Authors:Xiaohan Yan [aut, cre], Jacob Bien [aut]

rare_0.1.2.tar.gz
rare_0.1.2.tar.gz(r-4.7-arm64)rare_0.1.2.tar.gz(r-4.7-x86_64)rare_0.1.2.tar.gz(r-4.6-arm64)rare_0.1.2.tar.gz(r-4.6-x86_64)
rare_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rare/json (API)

# Install 'rare' in R:
install.packages('rare', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yanxht/rare/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • data.dtm - Document-term matrix for adjectives in TripAdvisor hotel reviews
  • data.hc - Hierarchical clustering tree for adjectives in TripAdvisor data set
  • data.rating - TripAdvisor hotel review ratings

On CRAN:

Conda:

openblascpp

3.45 score 1 packages 19 scripts 184 downloads 1 mentions 7 exports 11 dependencies

Last updated from:fa367f2bfc. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK148
source / vignettesOK284
linux-release-arm64OK149
linux-release-x86_64OK147
wasm-releaseOK128

Exports:find.leavesgroup.plotgroup.recoverrarefitrarefit.cvrarefit.predicttree.matrix

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival

Using the rare package

Rendered fromrare-vignette.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2018-08-03
Started: 2018-03-22