Package: RMSS 1.1.1

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:Anthony Christidis [aut, cre], Gabriela Cohen-Freue [aut]

RMSS_1.1.1.tar.gz
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RMSS_1.1.1.tgz(r-4.4-x86_64)RMSS_1.1.1.tgz(r-4.4-arm64)RMSS_1.1.1.tgz(r-4.3-x86_64)RMSS_1.1.1.tgz(r-4.3-arm64)
RMSS_1.1.1.tar.gz(r-4.5-noble)RMSS_1.1.1.tar.gz(r-4.4-noble)
RMSS_1.1.1.tgz(r-4.4-emscripten)RMSS_1.1.1.tgz(r-4.3-emscripten)
RMSS.pdf |RMSS.html✨
RMSS/json (API)
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Bug tracker:https://github.com/anthonychristidis/rmss/issues

On CRAN:

3 exports 1 stars 0.93 score 52 dependencies 4 scripts 168 downloads

Last updated 15 days agofrom:53096181c8. Checks:OK: 9. Indexed: yes.

Exports:cv.RMSSRMSStrimmed_samples

Dependencies:cellWiseclicodetoolscolorspaceDEoptimRfansifarverforeachggplot2glmnetgluegridExtragtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmepcaPPpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangrobStepSplitRegrobustbaserrcovscalesshapesrlarsstringistringrsurvivalsvdtibbleutf8vctrsviridisLitewithr