Package: rare 0.1.1
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.
Authors:
rare_0.1.1.tar.gz
rare_0.1.1.zip(r-4.7)rare_0.1.1.zip(r-4.6)rare_0.1.1.zip(r-4.5)
rare_0.1.1.tgz(r-4.6-x86_64)rare_0.1.1.tgz(r-4.6-arm64)rare_0.1.1.tgz(r-4.5-x86_64)rare_0.1.1.tgz(r-4.5-arm64)
rare_0.1.1.tar.gz(r-4.7-arm64)rare_0.1.1.tar.gz(r-4.7-x86_64)rare_0.1.1.tar.gz(r-4.6-arm64)rare_0.1.1.tar.gz(r-4.6-x86_64)
rare_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rare/json (API)
| # Install 'rare' in R: |
| install.packages('rare', repos = c('https://yanxht.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yanxht/rare/issues
- 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
Last updated from:93ce5266c9. Checks:11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 152 | ||
| linux-devel-x86_64 | NOTE | 162 | ||
| source / vignettes | OK | 235 | ||
| linux-release-arm64 | NOTE | 143 | ||
| linux-release-x86_64 | NOTE | 155 | ||
| macos-release-arm64 | NOTE | 135 | ||
| macos-release-x86_64 | NOTE | 239 | ||
| macos-oldrel-arm64 | NOTE | 250 | ||
| macos-oldrel-x86_64 | NOTE | 445 | ||
| windows-devel | NOTE | 154 | ||
| windows-release | NOTE | 162 | ||
| windows-oldrel | NOTE | 126 | ||
| wasm-release | OK | 153 |
Exports:find.leavesgroup.plotgroup.recoverrarefitrarefit.cvrarefit.predicttree.matrix
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival
