Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles
This is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have be...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/664050 |
| Acceso en línea: | http://hdl.handle.net/10486/664050 https://dx.doi.org/10.1016/j.neucom.2011.03.001 |
| Access Level: | acceso abierto |
| Palabra clave: | Bagging Boosting Ensemble learning Ensemble pruning Regression Semidefinite programming Informática |
| Sumario: | This is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neurocomputing 74.12-13 (2011) DOI: 10.1016/j.neucom.2011.03.001 |
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