ONAM: Fitting Interpretable Neural Additive Models Using Orthogonalization
An algorithm for fitting interpretable additive neural networks for identifiable and visualizable feature effects using post hoc orthogonalization. Fit custom neural networks intuitively using established 'R' 'formula' notation, including interaction effects of arbitrary order while preserving identifiability to enable a functional decomposition of the prediction function. For more details see Koehler et al. (2025) <doi:10.1038/s44387-025-00033-7>.
| Version: | 1.0.1 |
| Depends: | keras3, reticulate |
| Imports: | dplyr, scales, rlang, ggplot2, pROC |
| Suggests: | akima, RColorBrewer, testthat (≥ 3.0.0) |
| Published: | 2026-01-26 |
| DOI: | 10.32614/CRAN.package.ONAM |
| Author: | David Köhler 
[aut, cre] |
| Maintainer: | David Köhler <koehler at imbie.uni-bonn.de> |
| BugReports: | https://github.com/Koehlibert/ONAM_R/issues |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | ONAM results |
Documentation:
| Reference manual: | ONAM.html , ONAM.pdf |
Downloads:
| Package source: | ONAM_1.0.1.tar.gz |
| Windows binaries: | r-devel: ONAM_1.0.1.zip, r-release: ONAM_1.0.1.zip, r-oldrel: ONAM_1.0.1.zip |
| macOS binaries: | r-release (arm64): ONAM_1.0.1.tgz, r-oldrel (arm64): ONAM_1.0.1.tgz, r-release (x86_64): ONAM_1.0.1.tgz, r-oldrel (x86_64): ONAM_1.0.1.tgz |
| Old sources: | ONAM archive |
Linking:
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