On sparse ensemble methods : an application to short-term predictions of the evolution of COVID-19
Sandra Benítez-Peña, Emilio Carrizosa, Vanesa Guerrero, M. Dolores Jiménez-Gamero, Belén Martín-Barragán, Cristina Molero-Río, Pepa Ramírez-Cobo, Dolores Romero Morales, M. Remedios Sillero-Denamiel
| Year of publication: |
2021
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|---|---|
| Authors: | Benítez-Peña, Sandra ; Carrizosa, Emilio ; Guerrero, Vanesa ; Jiménez-Gamero, M. Dolores ; Martín-Barragán, Belén ; Molero-Río, Cristina ; Ramírez-Cobo, Pepa ; Romero Morales, María Dolores ; Sillero-Denamiel, M. Remedios |
| Published in: |
European journal of operational research : EJOR. - Amsterdam : Elsevier, ISSN 0377-2217, ZDB-ID 243003-4. - Vol. 295.2021, 2 (1.12.), p. 648-663
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| Subject: | Machine Learning | Ensemble Method | Mathematical Optimization | Selective Sparsity | COVID-19 | Coronavirus | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Mathematische Optimierung | Mathematical programming | Theorie | Theory |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ejor.2021.04.016 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013205980