ASML: Algorithm Portfolio Selection with Machine Learning
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>).
| Version: |
1.1.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
caret, ggplot2, DALEX, dplyr, purrr, tibble, tidyr, reshape2, Polychrome, scales, rlang |
| Suggests: |
snow |
| Published: |
2025-09-29 |
| DOI: |
10.32614/CRAN.package.ASML |
| Author: |
Brais González-Rodríguez
 [aut, cre],
Ignacio Gómez-Casares
[aut],
Beatriz Pateiro-López
[aut],
Julio González-Díaz
[aut],
María Caseiro-Arias [ctb],
Antonio Fariña-Elorza [ctb],
Manuel Timiraos-López [ctb] |
| Maintainer: |
Brais González-Rodríguez <brais.gonzalez.rodriguez at uvigo.gal> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| CRAN checks: |
ASML results |
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