Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44062
Title: Reducing Features Using Discriminative Common Vectors
Authors: Travieso, Carlos M. 
del Pozo, Marcos
Ferrer, Miguel A. 
Alonso, Jesús B. 
UNESCO Clasification: 3307 Tecnología electrónica
Issue Date: 2010
Publisher: 1866-9956
Journal: Cognitive Computation 
Abstract: A feature reduction system based on Discriminative Common Vector is presented and evaluated in this paper. The validation of this system was made with three databases, first one is DNA markers and the other two are The ORL Database of Face and The Yale Face Database. Moreover, a supervised classification system has been implemented with three different classifiers, achieving the best success rates with Support Vector Machines using Radial Basis Function kernel and a one-versus-all multi-class approach. The study shows clearly how our approach reduces the number of features and load times, keeping or improving the level of discrimination.
URI: http://hdl.handle.net/10553/44062
ISSN: 1866-9956
DOI: 10.1007/s12559-010-9059-y
Source: Cognitive Computation[ISSN 1866-9956],v. 2, p. 160-164
Appears in Collections:Artículos
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