Reject option paradigm for the reduction of support vectors
Reject option paradigm for the reduction of support vectors
dc.contributor.author | Sousa,R | en |
dc.contributor.author | Da Rocha Neto,AR | en |
dc.contributor.author | Barreto,GA | en |
dc.contributor.author | Jaime Cardoso | en |
dc.contributor.author | Coimbra,MT | en |
dc.date.accessioned | 2018-01-21T16:05:26Z | |
dc.date.available | 2018-01-21T16:05:26Z | |
dc.date.issued | 2014 | en |
dc.description.abstract | In this paper we introduce a new conceptualization for the reduction of the number of support vectors (SVs) for an efficient design of support vector machines. The techniques here presented provide a good balance between SVs reduction and generalization capability. Our proposal explores concepts from classification with reject option. These methods output a third class (the rejected instances) for a binary problem when a prediction cannot be given with sufficient confidence. Rejected instances along with misclassified ones are discarded from the original data to give rise to a classification problem that can be linearly solved. Our experimental study on two benchmark datasets show significant gains in terms of SVs reduction with competitive performances. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/7194 | |
dc.language | eng | en |
dc.relation | 3889 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Reject option paradigm for the reduction of support vectors | en |
dc.type | conferenceObject | en |
dc.type | Publication | en |
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