ExhaustiveSearch
1.0.2A Fast and Scalable Exhaustive Feature Selection Framework
Overview
The goal of this package is to provide an easy to use, fast and scalable exhaustive search framework. Exhaustive feature selections typically require a very large number of models to be fitted and evaluated. Execution speed and memory management are crucial factors here. This package provides solutions for both. Execution speed is optimized by using a multi-threaded C++ backend, and memory issues are solved by by only storing the best results during execution and thus keeping memory usage constant.
Install
Health
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Repository
Stars over time
Forks over time
Issues over time
PRs over time
Repository practices
4 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/rudolfjagdhuber/exhaustivesearch on 2026-07-30.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.2Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.12021-01-18 · diff ↗
- 1.0.02021-01-15
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-01-15
- Total releases
- 3 / 5 yrs
- License
- GPL (>= 3) OSI
- Download size
- 50 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet