Interpretable Boosted Linear Models
Overview
Implements Interpretable Boosted Linear Models (IBLMs). These combine a conventional generalized linear model (GLM) with a machine learning component, such as XGBoost. The package also provides tools within for explaining and analyzing these models. For more details see Gawlowski and Wang (2025) https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf.
Major changes
iblmclass model objects now require factor variables for categorical features. Users should explicitly convert character columns to factors before training.
New features
- Added "IBLM" vignette providing a comprehensive walkthrough of package functionality.
Bug fixes
- Fixed bug where all variable types were converted to numeric before training and predicting of booster model, which could lead to improper handling of categorical features.
Internal changes
- Updated to maintain compatibility with xgboost v3.1.2.1. Package now requires xgboost >= 3.1.2.1.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-11
- ERROR12 OK, 1 ERROR2026-06-09
- OK14 OK2026-03-10
Documentation
- Help pages
- 26 (1 internal)
- Examples that run
- 96%23 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 96%
- Documented parameters
- 96%
- Return-value docs
- 100%
- Help pages citing references
- 4%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 9
- Median days to close, 50 most recently updated closed PRs
- 29
Stars over time
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9 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/ifoa-adswp/iblm on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2026-05-23 · The repository has a site deploy workflow
pkgdown site last built 2026-05-23
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This repository shows signs of AI coding tools.
- Claude Codefirst seen 2026-04-10Pull request it wrote: opened by a project member
Dependencies
Installing IBLM adds 67 packages (34 with compiled code, 65 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
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Package metadata
- First published
- 2025-11-19
- Total releases
- 2 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 82 KB / 1 file
- Download size
- 1.2 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("IBLM")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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