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 .

See also

Useful links:

• https://bonijoao.github.io/figsr/

• https://github.com/bonijoao/figsr

• Report bugs at https://github.com/bonijoao/figsr/issues

Author

Maintainer: João Paulo Assis Bonifácio jpab.27@hotmail.com (ORCID) [copyright holder]

Authors:

• Geraldo Magela da Cruz Pereira geraldo.pereira@ufla.br (ORCID) [copyright holder]

• Pedro Mambelli Fernandes (ORCID) [copyright holder]

• João Vitor Andrade Alves de Souza joaovitor.alvez16@gmail.com (ORCID) [copyright holder]