Supervised Learning with Mandatory Splits and Seeds
Overview
Implements the split-fit-evaluate-assess workflow from Hastie, Tibshirani, and Friedman (2009, ISBN:978-0-387-84857-0) "The Elements of Statistical Learning", Chapter 7. Provides three-way data splitting with automatic stratification, mandatory seeds for reproducibility, automatic data type handling, and 10 algorithms out of the box. Uses 'Rust' backend for cross-language deterministic splitting. Designed for tabular supervised learning with minimal ceremony. Polyglot parity with the 'Python' 'mlw' package on 'PyPI'.
Fixed
- Per-holdout assess enforcement:
ml_assess()now rejects a second call on the same test partition regardless of which model calls it. The provenance registry tracks spent holdouts via content-addressed fingerprinting. - Fixed
ml_prepare()return value extraction (X and norm fields).
New
ml_cv(),ml_cv_temporal(),ml_cv_group()for cross-validation.ml_verify()for post-fit model verification.ml_prepare()for explicit preprocessing.- Content-addressed provenance registry (
rlang::hashfingerprinting). - Cross-verb provenance checks (train/test from same split).
From NEWS.md in the release
Install
Health
- OK13 OK2026-10-20
- ERROR12 OK, 1 ERROR2026-10-17
- OK13 OK2026-08-06
- ERROR11 OK, 1 NOTE, 1 ERROR2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
Show 27 earlier changesHide 27 earlier changes
- OK13 OK2026-07-23
- ERROR12 OK, 1 ERROR2026-07-19
- OK13 OK2026-07-18
- ERROR12 OK, 1 ERROR2026-07-16
- OK13 OK2026-07-07
- ERROR11 OK, 2 ERROR2026-07-03
- OK13 OK2026-06-30
- ERROR12 OK, 1 ERROR2026-06-29
- OK13 OK2026-06-27
- ERROR12 OK, 1 ERROR2026-06-24
- OK13 OK2026-06-18
- ERROR12 OK, 1 ERROR2026-06-16
- OK13 OK2026-06-06
- ERROR10 OK, 3 ERROR2026-06-01
- OK13 OK2026-05-26
- ERROR12 OK, 1 ERROR2026-05-24
- OK13 OK2026-05-17
- ERROR12 OK, 1 ERROR2026-05-09
- OK13 OK2026-05-05
- ERROR11 OK, 2 ERROR2026-04-28
- OK14 OK2026-04-24
- ERROR13 OK, 1 ERROR2026-04-16
- OK14 OK2026-04-15
- ERROR13 OK, 1 ERROR2026-04-11
- OK14 OK2026-03-30
- ERROR13 OK, 1 ERROR2026-03-29
- OK5 OK2026-03-20
Documentation
- Help pages
- 70 (16 internal)includes a package overview page
- Examples that run
- 73%29 run in a plain check · 11 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 50%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Forks over time
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7 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/epagogy/ml on 2026-10-18.
The R CMD check workflow runs on Linux
This repository shows signs of AI coding tools.
- Claude Codefirst seen on or before 2026-03-14Named in .gitignore: .claude, CLAUDE.mdCommits: at least 1 crediting it in the message
- Claude Opus 4.61 commit · Mar 2026
Dependencies
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.2Latest2026-03-19 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-03-19
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 156 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("ml")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.5281/zenodo.19023838.
The repository also keeps a CITATION.cff.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.