Unified S3 Interface to Machine Learning Models
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- NOTE12 OK, 1 NOTE2026-06-07
Show 1 earlier changeHide 1 earlier change
- OK5 OK2026-04-29
Documentation
- Help pages
- 7
- Examples that run
- 83%5 run in a plain check · 1 never run
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing mlS3 adds 13 packages (9 with compiled code, 16 MB of source tarballs). Heaviest: data.table 5.7 MB, glmnet 2.7 MB, Rcpp 1.8 MB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- 0.1.1Latest
- 0.1.02026-04-28
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-04-28
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Download size
- 72 KB
Cite
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