fru
1.0.0A Blazing Fast Implementation of Random Forest
Overview
Yet another implementation of the Random Forest method by Breiman (2001) doi:10.1023/A:1010933404324, written in Rust and tailored towards stability, correctness, efficiency and scalability on modern multi-core machines. Handles both classification and regression, as well as provides permutation feature importance via a novel, highly optimised algorithm.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-07-30
- NOTE12 OK, 1 NOTE2026-07-29
- OK12 OK2026-04-25
Show 1 earlier changeHide 1 earlier change
- ERROR11 OK, 3 ERROR2026-03-10
Documentation
- Help pages
- 6
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 17%
Downloads
Repository
Repository gitlab.com/mbq/fru is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.
Dependencies
Installing fru adds no packages beyond those that come with R.
Code & Tests
People & History
Package metadata
- First published
- 2026-02-04
- Total releases
- 7 / 1 yrs
- License
- GPL-3 OSI
- Download size
- 45 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("fru")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1016/j.softx.2026.102918.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.