Package: randomForestSGT
Version: 1.0.0
Date: 2026-05-05
Title: Random Forest Super Greedy Trees
Authors@R: c(person("Min", "Lu", email = "luminwin@gmail.com", role = "aut"),
  person("Udaya B.", "Kogalur", email = "ubk@kogalur.com", role = c("aut", "cre")),
  person("Hemant", "Ishwaran", email = "hemant.ishwaran@gmail.com", role = "aut"))
Author: Min Lu [aut],
  Udaya B. Kogalur [aut, cre],
  Hemant Ishwaran [aut]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>
BugReports: https://github.com/kogalur/randomForestSGT/issues/
Depends: R (>= 4.3.0)
Imports: randomForestSRC (>= 3.6.2), varPro (>= 3.1.0)
Suggests: mlbench, interp, glmnet
Description: 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>.
License: GPL (>= 3)
URL: https://ishwaran.org/
NeedsCompilation: yes
Packaged: 2026-05-05 21:52:24 UTC; kogalur
Repository: CRAN
Date/Publication: 2026-05-11 18:50:07 UTC
