Introducing the Discriminative Paraconsistent Machine (DPM)


Autoria(s): Guido, Rodrigo Capobianco; Barbon Junior, Sylvio; Solgon, Regiane Denise; Paulo, Kátia Cristina Silva; Rodrigues, Luciene Cavalcanti; Silva, Ivan Nunes da; Escola, João Paulo Lemos
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/04/2015

27/04/2015

2013

Resumo

This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency.

Formato

389-402

Identificador

http://dx.doi.org/10.1016/j.ins.2012.09.028

Information Sciences, n. 221, p. 389-402, 2013.

0020-0255

http://hdl.handle.net/11449/122786

6542086226808067

Idioma(s)

eng

Relação

Information Sciences

Direitos

closedAccess

Palavras-Chave #Paraconsistency #Pattern recognition #Discriminative model training
Tipo

info:eu-repo/semantics/article