RT Book, Section
T1 A methodology for building fuzzy rules from data
A1 Rodríguez González, Juan Tinguaro
A1 López, Victoria
A1 Montero De Juan, Francisco Javier
A1 Vitoriano Villanueva, Begoña
A2 Burillo, P.
A2 Bustince, H.
A2 De Baets, B.
A2 Fodor, J.
AB Extraction of rules for classification and decision tasks from databases is an issue of growing importance as automated processes based on data are being required in these fields. Interpretability of rules is improved by defining classes for independent variables. Moreover, though more complex, a more realistic and flexible framework is attained when fuzzy classes are considered. In this paper, an inductive approach is taken in order to develop a general methodology for building fuzzy rules from databases. Three types of rules are built in order to be able of dealing with both categorical and numerical data.
PB Public University of Navarre
SN 978-84-9769-242-7
YR 2009
FD 2009
LK https://hdl.handle.net/20.500.14352/53453
UL https://hdl.handle.net/20.500.14352/53453
LA eng
NO EuroFuse Workshop, September 16-18, 2009, Pamplona
DS Docta Complutense
RD 10 abr 2025