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mlS3  

Unified S3 Interface to Machine Learning Models
View on CRAN: Click here


Download and install mlS3 package within the R console
Install from CRAN:
install.packages("mlS3")

Install from Github:
library("remotes")
install_github("cran/mlS3")

Install by package version:
library("remotes")
install_version("mlS3", "0.1.0")



Attach the package and use:
library("mlS3")
Maintained by
T. Moudiki
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-28
Latest Update: 2026-04-28
Description:
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.
How to cite:
T. Moudiki (2026). mlS3: Unified S3 Interface to Machine Learning Models. R package version 0.1.0, https://cran.r-project.org/web/packages/mlS3. Accessed 07 Jun. 2026.
Previous versions and publish date:
0.1.0 (2026-04-28 21:00)
Other packages that cited mlS3 R package
View mlS3 citation profile
Other R packages that mlS3 depends, imports, suggests or enhances
Complete documentation for mlS3
Functions, R codes and Examples using the mlS3 R package
Full mlS3 package functions and examples
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