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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.

Versions across snapshots

VersionRepositoryFileSize
1.2.4 rolling linux/jammy R-4.5 RMSS_1.2.4.tar.gz 228.1 KiB
1.2.4 rolling linux/noble R-4.5 RMSS_1.2.4.tar.gz 235.3 KiB
1.2.4 rolling source/ R- RMSS_1.2.4.tar.gz 61.5 KiB
1.2.4 latest linux/jammy R-4.5 RMSS_1.2.4.tar.gz 228.1 KiB
1.2.4 latest linux/noble R-4.5 RMSS_1.2.4.tar.gz 235.3 KiB
1.2.4 latest source/ R- RMSS_1.2.4.tar.gz 61.5 KiB
1.2.4 2026-04-26 source/ R- RMSS_1.2.4.tar.gz 61.5 KiB
1.2.4 2026-04-23 source/ R- RMSS_1.2.4.tar.gz 61.5 KiB
1.2.4 2026-04-09 windows/windows R-4.5 RMSS_1.2.4.zip 629.4 KiB
1.1.2 2025-04-20 source/ R- RMSS_1.1.2.tar.gz 59.0 KiB

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