randomForestSGT
1.0.0Random Forest Super Greedy Trees
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-128 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 67%
- Documented parameters
- 89%
- Return-value docs
- 100%
- References docs
- 50%
Downloads
Repository
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Repository practices
Checks run against github.com/kogalur/randomforestsgt on 2026-08-16.
No development-tooling practices detected in the upstream repository.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- 1.0.0Latest2026-05-11 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-11
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.3.0
- Download size
- 166 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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