A supervised classifier scheme based on clustering algorithms

A. Hernandez-Matamoros, E. Escamilla-Hernandez, K. Perez-Daniel, M. Nakano-Miyatake, H. Perez-Meana

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

This paper proposes a new classifier scheme based on classical clustering algorithms, such as the Batchelor & Wilkins y K-means algorithms which are trained in a similar form that the artificial neural network (ANN) or support vector machines (SVM). Proposed scheme has the advantage that if a new class is added, it is not necessary to train he classifier completely, but only add a new class. Experimental results show that the proposed scheme provides classification rates quite similar to those provided by the SVM with much less computational complexity.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2014 IEEE Central America and Panama Convention, CONCAPAN 2014
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781479975846
DOI
EstadoPublicada - 30 dic. 2014
Evento2014 34th IEEE Central America and Panama Convention, CONCAPAN 2014 - Panama City, Panamá
Duración: 12 nov. 201414 nov. 2014

Serie de la publicación

NombreProceedings of the 2014 IEEE Central America and Panama Convention, CONCAPAN 2014

Conferencia

Conferencia2014 34th IEEE Central America and Panama Convention, CONCAPAN 2014
País/TerritorioPanamá
CiudadPanama City
Período12/11/1414/11/14

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