Multi-objective neural network model selection with a graph-based large margin approach.

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorTorres, Luiz Carlos Bambirra-
Autor(es): dc.creatorCastro, Cristiano Leite de-
Autor(es): dc.creatorRocha, Honovan Paz-
Autor(es): dc.creatorAlmeida, Gustavo Matheus de-
Autor(es): dc.creatorBraga, Antônio de Pádua-
Data de aceite: dc.date.accessioned2025-08-21T15:57:22Z-
Data de disponibilização: dc.date.available2025-08-21T15:57:22Z-
Data de envio: dc.date.issued2022-09-15-
Data de envio: dc.date.issued2022-09-15-
Data de envio: dc.date.issued2021-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/15315-
Fonte completa do material: dc.identifierhttps://www.sciencedirect.com/science/article/pii/S0020025522002195-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.ins.2022.03.019-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1028501-
Descrição: dc.descriptionThis work presents a new decision-making strategy for multi-objective learning problem of artificial neural networks (ANN). The proposed decision-maker searches for the solution that minimizes a margin-based validation error amongst Pareto set solutions. The proposal is based on a geometric approximation to find the large margin (distance) of separation among the classes. Several benchmarks commonly available in the literature were used for testing. The obtained results showed that the proposal is more efficient in controlling the generalization capacity of neural models than other learning machines. It yields smooth (noise robustness) and well-fitted models straightforwardly, i.e., without the necessity of parameter set definition in advance or validation data use, as often required by learning machines.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectClassification-
Palavras-chave: dc.subjectDecision making-
Palavras-chave: dc.subjectArtificial neural networks-
Palavras-chave: dc.subjectMulti objective decision learning-
Título: dc.titleMulti-objective neural network model selection with a graph-based large margin approach.-
Aparece nas coleções:Repositório Institucional - UFOP

Não existem arquivos associados a este item.