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A methodology for building fuzzy rules from data

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Rodríguez, Juan Tinguaro and Lopez, Victoria and Montero, Javier and Vitoriano, Begoña (2009) A methodology for building fuzzy rules from data. In Preference modelling and decision analysis. Public University of Navarre, Pamplona, pp. 33-38. ISBN 978-84-9769-242-7

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Abstract

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.


Item Type:Book Section
Additional Information:

EuroFuse Workshop, September 16-18, 2009, Pamplona

Uncontrolled Keywords:Rules induction; Fuzzy classification; Data Mining; Decision Support Systems
Subjects:Sciences > Mathematics > Logic, Symbolic and mathematical
ID Code:30844
Deposited On:12 Jun 2015 07:41
Last Modified:25 May 2016 14:53

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