Package: RMSS 1.1.2
RMSS: Robust Multi-Model Subset Selection
Efficient algorithms for generating ensembles of robust, sparse and diverse models via robust multi-model subset selection (RMSS). The robust ensembles are generated by minimizing the sum of the least trimmed square loss of the models in the ensembles under constraints for the size of the models and the sharing of the predictors. Tuning parameters for the robustness, sparsity and diversity of the robust ensemble are selected by cross-validation.
Authors:
RMSS_1.1.2.tar.gz
RMSS_1.1.2.tar.gz(r-4.5-noble)RMSS_1.1.2.tar.gz(r-4.4-noble)
RMSS_1.1.2.tgz(r-4.4-emscripten)RMSS_1.1.2.tgz(r-4.3-emscripten)
RMSS.pdf |RMSS.html✨
RMSS/json (API)
NEWS
# Install 'RMSS' in R: |
install.packages('RMSS', 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 11 days agofrom:c2cf6da14e. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 20 2024 |
R-4.5-linux-x86_64 | OK | Dec 20 2024 |
Exports:cv.RMSSRMSStrimmed_samples
Dependencies:cellWiseclicodetoolscolorspaceDEoptimRfansifarverforeachggplot2glmnetgluegridExtragtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmepcaPPpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangrobStepSplitRegrobustbaserrcovscalesshapesrlarsstringistringrsurvivalsvdtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Coefficients for cv.RMSS Object | coef.cv.RMSS |
Coefficients for RMSS Object | coef.RMSS |
Cross-Validatoin for Robust Multi-Model Subset Selection | cv.RMSS |
Predictions for cv.RMSS Object | predict.cv.RMSS |
Predictions for RMSS Object | predict.RMSS |
Robust Multi-Model Subset Selection | RMSS |
Trimmed samples for RMSS or cv.RMSS Object | trimmed_samples |