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randomForestSGT

Random Forest Super Greedy Trees

Implements random forest Super Greedy Trees (SGTs) for regression. SGTs extend classification and regression tree splitting by fitting lasso-penalized local parametric models at tree nodes, producing sparse univariate and multivariate geometric cuts such as axis-aligned splits, hyperplanes, ellipsoids, hyperboloids, and interaction-based cuts. Trees are grown best-split-first by selecting cuts that reduce empirical risk, and ensembles provide out-of-bag error estimation, prediction on new data, variable filtering, tuning of the hcut complexity parameter, coordinate-descent lasso fitting, variable importance, and local coefficient summaries. For the underlying method, see Ishwaran (2026) <doi:10.1007/s10462-026-11541-6>.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 randomForestSGT_1.0.0.tar.gz 327.1 KiB
1.0.0 rolling linux/noble R-4.5 randomForestSGT_1.0.0.tar.gz 328.8 KiB
1.0.0 rolling source/ R- randomForestSGT_1.0.0.tar.gz 166.1 KiB
1.0.0 latest linux/jammy R-4.5 randomForestSGT_1.0.0.tar.gz 327.1 KiB
1.0.0 latest linux/noble R-4.5 randomForestSGT_1.0.0.tar.gz 328.8 KiB
1.0.0 latest source/ R- randomForestSGT_1.0.0.tar.gz 166.1 KiB
1.0.0 2026-04-23 source/ R- randomForestSGT_1.0.0.tar.gz 0 B

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