PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Probabilistic Tri-class Support Vector Machine
Luis Gonzalez-Abril, Cecilio Angulo, Francisco Velasco and Juan Antonio Ortega
Journal of Pattern Recognition Research Volume 5, Number 1, pp. 1-9, 2010. ISSN 1558-884X

Abstract

A probabilistic interpretation for the output obtained from a tri-class Support Vector Machine into a multi-classification problem is presented in this paper. Probabilistic outputs are defined when solving a multi-class problem by using an ensemble architecture with tri-class learning machines working in parallel. This architecture enables the definition of an ‘interpretation’ mapping which works on signed and probabilistic outputs providing more control to the user on the classification problem.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:7203
Deposited By:Cecilio Angulo
Deposited On:09 March 2011