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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