ASML
1.1.0Algorithm Portfolio Selection with Machine Learning
Overview
A wrapper for machine learning (ML) methods to select among a portfolio of algorithms based on the value of a key performance indicator (KPI). A number of features is used to adjust a model to predict the value of the KPI for each algorithm, then, for a new value of the features the KPI is estimated and the algorithm with the best one is chosen. To learn it can use the regression methods in 'caret' package or a custom function defined by the user. Several graphics available to analyze the results obtained. This library has been used in Ghaddar et al. (2023) doi:10.1287/ijoc.2022.0090).
Install
Health
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 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
- 73%
- Documented parameters
- 100%
- Return-value docs
- 30%
- References docs
- 5%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 5.0 median / 30 max
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
19 10 exported
Complexity
8.3 avg / 30 max
Call network
19 nodes / 11 edges
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1.0Latest
- RR 4.5.0 released · 2025-04-11
- 1.0.02025-02-19
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2025-02-19
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 487 KB / 3 files
- Download size
- 513 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet