funcml: Functional Machine Learning Framework

A compact and explicit machine learning framework for supervised learning, resampling-based evaluation, hyperparameter tuning, learner comparison, interpretation, and plug-in g-computation. The package uses standard formulas for model specification and provides stable S3 interfaces for fitting, evaluation, tuning, interpretation, and causal estimation across a learner registry with multiple backend engines. Implemented interpretation methods build on established approaches such as permutation-based variable importance, partial dependence, individual conditional expectation, accumulated local effects, SHAP, and LIME; see Friedman (2001) <doi:10.1214/aos/1013203451>, Goldstein et al. (2015) <doi:10.1080/10618600.2014.907095>, Apley and Zhu (2020) <doi:10.1111/rssb.12377>, Lundberg and Lee (2017) <doi:10.48550/arXiv.1705.07874>, and Ribeiro et al. (2016) <doi:10.48550/arXiv.1602.04938>. The framework is intentionally opinionated: preprocessing is expected to occur outside the modeling step, and the API emphasizes explicit inputs, consistent object contracts, and compact interfaces rather than feature-by-feature competition with larger machine learning ecosystems.

Version:	0.7.1
Depends:	R (≥ 3.5.0)
Imports:	stats, utils, methods, ggplot2, functionals, grDevices, tools, MASS, mgcv, nnet, rpart, glmnet, ranger, e1071, randomForest, gbm, C50, kknn, earth, naivebayes, mda, ada, pls, partykit, dbarts, xgboost, lightgbm, shapviz
Suggests:	testthat (≥ 3.1.0), knitr, rmarkdown, roxygen2, gggenes, ggfittext
Published:	2026-04-21
DOI:	10.32614/CRAN.package.funcml
Author:	Imad El Badisy [aut, cre]
Maintainer:	Imad El Badisy <elbadisyimad at gmail.com>
BugReports:	https://github.com/ielbadisy/funcml/issues
License:	GPL-3
URL:	https://github.com/ielbadisy/funcml
NeedsCompilation:	no
Citation:	funcml citation info
Materials:	README, NEWS
CRAN checks:	funcml results

Documentation:

Reference manual:	funcml.html , funcml.pdf
Vignettes:	funcml (source, R code)

Downloads:

Package source:	funcml_0.7.1.tar.gz
Windows binaries:	r-release: funcml_0.7.1.zip, r-oldrel: funcml_0.7.1.zip
macOS binaries:	r-release (arm64): funcml_0.7.1.tgz, r-oldrel (arm64): funcml_0.7.1.tgz, r-release (x86_64): not available, r-oldrel (x86_64): funcml_0.7.1.tgz

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