Minimally overfitted learners: A general framework for ensemble learning-Reference-Cited by-同舟云学术

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Minimally overfitted learners: A general framework for ensemble learning

Published:2022-10 Issue: Volume:254 Page:109669
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Aceña Víctor^ORCID,Martín de Diego Isaac,R. Fernández Rubén^ORCID,M. Moguerza Javier^ORCID

Funder

Ministerio de Economía y Competitividad

Nvidia

Comunidad de Madrid

España Ministerio de Ciencia e Innovación

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference44 articles.

1. Random aggregated and bagged ensembles of svms: an empirical bias–variance analysis;Valentini,2004

2. Bagging predictors;Breiman;Mach. Learn.,1996

3. Experiments with a new boosting algorithm;Freund,1996

4. The strength of weak learnability;Schapire;Mach. Learn.,1990

5. Random forests;Breiman;Mach. Learn.,2001

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