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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>.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.3.0) |
| Imports: | randomForestSRC (≥ 3.6.2), varPro (≥ 3.1.0) |
| Suggests: | mlbench, interp, glmnet |
| Published: | 2026-05-11 |
| DOI: | 10.32614/CRAN.package.randomForestSGT |
| Author: | Min Lu [aut], Udaya B. Kogalur [aut, cre], Hemant Ishwaran [aut] |
| Maintainer: | Udaya B. Kogalur <ubk at kogalur.com> |
| BugReports: | https://github.com/kogalur/randomForestSGT/issues/ |
| License: | GPL (≥ 3) |
| URL: | https://ishwaran.org/ |
| NeedsCompilation: | yes |
| Citation: | randomForestSGT citation info |
| Materials: | NEWS |
| CRAN checks: | randomForestSGT results |
| Reference manual: | randomForestSGT.html , randomForestSGT.pdf |
| Package source: | randomForestSGT_1.0.0.tar.gz |
| Windows binaries: | r-devel: randomForestSGT_1.0.0.zip, r-release: randomForestSGT_1.0.0.zip, r-oldrel: randomForestSGT_1.0.0.zip |
| macOS binaries: | r-release (arm64): randomForestSGT_1.0.0.tgz, r-oldrel (arm64): randomForestSGT_1.0.0.tgz, r-release (x86_64): randomForestSGT_1.0.0.tgz, r-oldrel (x86_64): randomForestSGT_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.