Data Leakage Detection Tools for Machine Learning
Overview
Provides utilities to detect common data leakage patterns including train/test contamination, temporal leakage, and data duplication, enhancing model reliability and reproducibility in machine learning workflows. Generates diagnostic reports and visual summaries to support data validation. Methods based on best practices from Hastie, Tibshirani, and Friedman (2009, ISBN:978-0387848570).
- Initial CRAN submission
- Core functionality for detecting data leakage in ML workflows:
- Train/test contamination detection
- Target leakage identification
- Duplicate record detection
- Temporal misalignment checks
- Comprehensive reporting with visual summaries
- Integration support for caret, mlr3, and tidymodels
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 51 (28 internal)includes a package overview page
- Examples that run
- 25%2 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran) · 4 never run
- Exported functions with examples
- 30%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing leakr adds 74 packages (37 with compiled code, 55 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2025-10-26 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-26
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 113 KB
Cite
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