Package: ROOT 0.2.1

Peter Liu

ROOT: Rashomon Set of Optimal Trees

Implements a general framework for globally optimizing user-specified objective functionals over interpretable binary weight functions represented as sparse decision trees, called ROOT (Rashomon Set of Optimal Trees). It searches over candidate trees to construct a Rashomon set of near-optimal solutions and derives a summary tree highlighting stable patterns in the optimized weights. ROOT includes a built-in generalizability mode for identifying subgroups in trial settings for transportability analyses (Parikh et al. (2025) <doi:10.1080/01621459.2025.2495319>).

Authors:Yiren Hou [aut], Peter Liu [aut, cre], Sean McGrath [aut], Harsh Parikh [aut]

ROOT_0.2.1.tar.gz
ROOT_0.2.1.zip(r-4.7-any)ROOT_0.2.1.zip(r-4.6-any)ROOT_0.2.1.zip(r-4.5-any)
ROOT_0.2.1.tgz(r-4.6-any)ROOT_0.2.1.tgz(r-4.5-any)
ROOT_0.2.1.tar.gz(r-4.7-any)ROOT_0.2.1.tar.gz(r-4.6-any)
ROOT_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ROOT/json (API)

# Install 'ROOT' in R:
install.packages('ROOT', repos = c('https://peterliu599.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/peterliu599/root/issues

Datasets:

On CRAN:

Conda:

8.22 score 1 stars 4.3k scripts 234 downloads 2 exports 8 dependencies

Last updated from:46b98c4c7e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK131
source / vignettesOK374
linux-releaseOK114
macos-releaseOK131
macos-oldrelOK116
windows-develOK74
windows-releaseOK116
windows-oldrelOK71
wasm-releaseOK114

Exports:characterizing_underrepROOT

Dependencies:gbmlatticeMASSMatrixrpartrpart.plotsurvivalwithr

Generalizability Path Example: Characterizing Underrepresented Populations
Overview | The diabetes_data Dataset | How the data were generated | Checking Covariate Overlap | Fitting ROOT in Generalizability Mode | Inspecting the Results | Print summary | Detailed summary | Terminal node rules | Visualizing the Characterization Tree | Interpreting the Output | How well does the summary tree describe the ensemble rule? | Checking the estimates against the truth | Key Parameters | Reference
Rendered fromgeneralizability_path_example.Rmdusingknitr::rmarkdown

Last update: 2026-10-21
Started: 2026-01-22

Optimization Path Example: Portfolio Selection via Variance Minimization
Overview | Problem Setup | Why portfolio selection? | A globally coupled objective | Simulating the Data | The objective function | Distribution of asset risk | Fitting ROOT | Inspecting the Results | Print summary | Detailed summary | Visualizing the Characterized Tree | Examining the Weights | Visualizing the inclusion decision | The Default Objective | Using Other Custom Objectives | Key Parameters | Reference
Rendered fromoptimization_path_example.Rmdusingknitr::rmarkdown

Last update: 2026-10-20
Started: 2026-01-22

Quickstart Guide to ROOT
Installation | What is ROOT? | Basic usage | Inspecting results | Next steps
Rendered fromquickstart.Rmdusingknitr::rmarkdown

Last update: 2026-10-20
Started: 2026-01-22