mlS3: Unified S3 Interface to Machine Learning Models

Provides a unified and consistent S3 interface for training and predicting with a variety of machine learning models in R. The package wraps popular algorithms (e.g., from 'glmnet', 'lightgbm', 'ranger', 'e1071', and 'caret') under a common workflow based on simple wrap_*() and predict() functions, allowing users to switch between models without changing their code structure. It supports both classification and regression tasks and facilitates rapid experimentation, benchmarking, and comparison of models. By abstracting away package-specific APIs while preserving flexibility in parameter specification, the package streamlines machine learning workflows and promotes reproducibility.

Version:	0.1.0
Imports:	e1071, glmnet, lightgbm, ranger
Suggests:	caret, knitr, randomForest, kernlab
Published:	2026-04-28
DOI:	10.32614/CRAN.package.mlS3
Author:	T. Moudiki [aut, cre]
Maintainer:	T. Moudiki <thierry.moudiki at gmail.com>
License:	GPL-3
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	mlS3 results

Documentation:

Reference manual:	mlS3.html , mlS3.pdf
Vignettes:	Introduction to R package 'mlS3' (source, R code) Introduction to R package 'mlS3' – with caret (source, R code)

Downloads:

Package source:	mlS3_0.1.0.tar.gz
Windows binaries:	r-devel: mlS3_0.1.0.zip, r-release: mlS3_0.1.0.zip, r-oldrel: mlS3_0.1.0.zip
macOS binaries:	r-release (arm64): mlS3_0.1.0.tgz, r-oldrel (arm64): mlS3_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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