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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>).
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Package details |
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| Author | Brais González-Rodríguez [aut, cre] (<https://orcid.org/0000-0001-5276-2320>), Ignacio Gómez-Casares [aut] (<https://orcid.org/0000-0003-0420-7319>), Beatriz Pateiro-López [aut] (<https://orcid.org/0000-0002-7714-1835>), Julio González-Díaz [aut] (<https://orcid.org/0000-0002-4667-4348>), María Caseiro-Arias [ctb], Antonio Fariña-Elorza [ctb], Manuel Timiraos-López [ctb] |
| Maintainer | Brais González-Rodríguez <brais.gonzalez.rodriguez@uvigo.gal> |
| License | GPL-3 |
| Version | 1.0.0 |
| Package repository | View on CRAN |
| Installation |
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