Introducing the Discriminative Paraconsistent Machine (DPM)
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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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 |