Artigo
Introducing the Discriminative Paraconsistent Machine (DPM)
Registro en:
Information Sciences, n. 221, p. 389-402, 2013.
0020-0255
6542086226808067
0000-0002-0924-8024
Autor
Guido, Rodrigo Capobianco [UNESP]
Barbon Junior, Sylvio
Solgon, Regiane Denise
Paulo, Kátia Cristina Silva
Rodrigues, Luciene Cavalcanti
Silva, Ivan Nunes da
Escola, João Paulo Lemos
Resumen
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. Universidade Estadual Paulista Júlio de Mesquita Filho, Instituto de Biociências Letras e Ciências Exatas de São José do Rio Preto, Sao Jose do Rio Preto, Av. Cristovao Colombo, 2265, Jardim Nazareth, CEP 15054-000, SP, Brasil