Package: RSSRMR 0.1.0
Abdul Wahid
RSSRMR: Robust Self-Representation Sparse Reconstruction and Manifold Regularization
Feature selection and clustering classification under the presence of multivariate outliers in high-dimensional unlabeled data.
Authors:
RSSRMR_0.1.0.tar.gz
RSSRMR_0.1.0.tar.gz(r-4.7-any)RSSRMR_0.1.0.tar.gz(r-4.6-any)
RSSRMR_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RSSRMR/json (API)
| # Install 'RSSRMR' in R: |
| install.packages('RSSRMR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:0cec30e1a4. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 112 | ||
| source / vignettes | OK | 237 | ||
| linux-release-x86_64 | OK | 119 | ||
| wasm-release | OK | 107 |
Dependencies:DEoptimRrobustbase
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Robust Distance Weights | dweight |
| Robust Self-Representation Sparse Reconstruction and Manifold Regularization | RSSRMR |