figsr: Fast Interpretable Greedy-Tree Sums for Tree Ensembles

Flexible, interpretable machine learning algorithm for additive tree sums (FIGS). Fits a sum of shallow classification and regression trees (CART) by greedily minimizing residual impurity, growing a new tree or deepening an existing one at each step, whichever reduces the residuals most. Supports regression and two-class classification, variable importance, 'ggplot2' graphics, bootstrap ensembling and seamless integration with 'parsnip' and 'tidymodels' workflows. The method is described in Tan et al. (2023) <doi:10.1073/pnas.2310151122>.

Version:	0.2.0
Depends:	R (≥ 4.1)
Imports:	dials, ggplot2 (≥ 4.0.0), graphics, parsnip, rlang, stats, tibble
Suggests:	ggiraph, knitr, recipes, rmarkdown, testthat (≥ 3.0.0), workflows
Published:	2026-10-28
DOI:	10.32614/CRAN.package.figsr
Author:	João Paulo Assis Bonifácio [aut, cre, cph], Geraldo Magela da Cruz Pereira [aut, cph], Pedro Mambelli Fernandes [aut, cph], João Vitor Andrade Alves de Souza [aut, cph]
Maintainer:	João Paulo Assis Bonifácio <jpab.27 at hotmail.com>
BugReports:	https://github.com/bonijoao/figsr/issues
License:	MIT + file LICENSE
URL:	https://bonijoao.github.io/figsr/, https://github.com/bonijoao/figsr
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	figsr results

Documentation:

Reference manual:	figsr.html , figsr.pdf
Vignettes:	Getting Started with figsr (source, R code) Missing Values in figsr: A Worked Example (source, R code)

Downloads:

Package source:	figsr_0.2.0.tar.gz
Windows binaries:	r-devel: figsr_0.1.1.zip, r-release: figsr_0.1.1.zip, r-oldrel: figsr_0.1.1.zip
macOS binaries:	r-release (arm64): figsr_0.2.0.tgz, r-oldrel (arm64): figsr_0.2.0.tgz, r-release (x86_64): figsr_0.2.0.tgz, r-oldrel (x86_64): figsr_0.2.0.tgz
Old sources:	figsr archive

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