TY - GEN
T1 - A characterization of linearly compensated hybrid connectives used in fuzzy classifications
AU - Sańchez, Mónica
AU - Prats, Francesc
AU - Agell, N.
AU - Aguilar-Martin, Joseph
PY - 2004
Y1 - 2004
N2 - The study of linearly compensated hybrid connectives H = C+(1¡) C, where C is a t-norm and C represents the dual connective of C, to define aggregation operators for fuzzy classifications is a key point not only in fuzzy sets theory but also in learning processes. Although these operators are not associative, the fact that they can be decomposed into associative functions easily gives rise to n-Ary aggregation functions by straightforward iteration. Among the most commonly used t-norms are those of Frank's family, which are simultaneously t-norms and copulas. The purpose of this paper is to give a characterization of the hybrid connective H, via the properties of the connective C. Necessary and sufficient conditions of H that define C as a copula are given. The characterized hybrid connectives H are used to compute the global adequacy degree of an object in a class from marginal adequacy degrees in a learning system.
AB - The study of linearly compensated hybrid connectives H = C+(1¡) C, where C is a t-norm and C represents the dual connective of C, to define aggregation operators for fuzzy classifications is a key point not only in fuzzy sets theory but also in learning processes. Although these operators are not associative, the fact that they can be decomposed into associative functions easily gives rise to n-Ary aggregation functions by straightforward iteration. Among the most commonly used t-norms are those of Frank's family, which are simultaneously t-norms and copulas. The purpose of this paper is to give a characterization of the hybrid connective H, via the properties of the connective C. Necessary and sufficient conditions of H that define C as a copula are given. The characterized hybrid connectives H are used to compute the global adequacy degree of an object in a class from marginal adequacy degrees in a learning system.
KW - Classification algorithms
KW - Hybrid connectives
KW - Machine learning
KW - Qualitative reasoning
KW - Reasoning under uncertainty
UR - http://www.scopus.com/inward/record.url?scp=84914176872&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84914176872
T3 - Frontiers in Artificial Intelligence and Applications
SP - 1081
EP - 1082
BT - ECAI 2004 - 16th European Conference on Artificial Intelligence, including Prestigious Applications of Intelligent Systems, PAIS 2004 - Proceedings
A2 - de Mantaras, Ramon Lopez
A2 - Saitta, Lorenza
PB - IOS Press
T2 - 16th European Conference on Artificial Intelligence, ECAI 2004
Y2 - 22 August 2004 through 27 August 2004
ER -