Small margin ensembles can be robust to class-label noise
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 documento: | artigo |
| Data de publicação: | 2015 |
| País: | España |
| Recursos: | Universidad Autónoma de Madrid |
| Repositório: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglês |
| OAI Identifier: | oai:repositorio.uam.es:10486/676218 |
| Acesso em linha: | http://hdl.handle.net/10486/676218 https://dx.doi.org/10.1016/j.neucom.2014.12.086 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Bagging Bootstrap sampling Label noise Small margin classifiers Informática |
| Resumo: | 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, VOL 160 (2015) DOI 10.1016/j.neucom.2014.12.086 |
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