Algorithm 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
- 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
- 21 (7 internal)
- Examples that run
- 73%8 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
- Exported functions with examples
- 30%
- Documented parameters
- 100%
- Return-value docs
- 30%
- Help pages citing references
- 5%
Downloads
Dependencies
Installing ASML adds 72 packages (35 with compiled code, 56 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
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- 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
Cite
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