Package: ONAM 1.1.0

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>.

Authors:David Köhler [aut, cre]

ONAM_1.1.0.tar.gz
ONAM_1.1.0.zip(r-4.7-any)ONAM_1.1.0.zip(r-4.6-any)ONAM_1.1.0.zip(r-4.5-any)
ONAM_1.1.0.tgz(r-4.6-any)ONAM_1.1.0.tgz(r-4.5-any)
ONAM_1.1.0.tar.gz(r-4.7-any)ONAM_1.1.0.tar.gz(r-4.6-any)
ONAM_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ONAM/json (API)

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

Bug tracker:https://github.com/koehlibert/onam_r/issues

On CRAN:

Conda:

deep-learninginterpretable-machine-learningmachine-learningstatistical-learning

3.92 score 12 scripts 285 downloads 9 exports 51 dependencies

Last updated from:1aab3f41f0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK151
source / vignettesOK230
linux-releaseOK145
macos-releaseOK161
macos-oldrelOK149
windows-develOK111
windows-releaseOK113
windows-oldrelOK99
wasm-releaseOK107

Exports:build_dnngen_sobolinstall_conda_envload_onamonamplot_inter_effectplot_main_effectsave_onamvar_decomp

Dependencies:backportsbase64enccliconfigcpp11dottydplyrfarverfastmapgenericsggplot2gluegtablehereisobandjsonlitekeras3labelinglatticelifecyclemagrittrMatrixpillarpkgconfigpngpROCprocessxpsR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootrstudioapiS7scalestensorflowtfautographtfrunstibbletidyselectutf8vctrsviridisLitewhiskerwithryamlzeallot