Constructing Accurate Fuzzy Rule-Based Classification Systems Using Apriori Principles and Rule-Weighting [chapter]

S. M. Fakhrahmad, A. Zare, M. Zolghadri Jahromi
Intelligent Data Engineering and Automated Learning - IDEAL 2007  
A fuzzy rule-based classification system (FRBCS) is one of the most popular approaches used in pattern classification problems. One advantage of a fuzzy rule-based system is its interpretability. However, we're faced with some challenges when generating the rule-base. In high dimensional problems, we can not generate every possible rule with respect to all antecedent combinations. In this paper, by making the use of some data mining concepts, we propose a method for rule generation, which can
more » ... sult in a rule-base containing rules of different lengths. As the next phase, we use rule-weight as a simple mechanism to tune the classifier and propose a new method of ruleweight specification for this purpose. Through computer simulations on some data sets from UCI repository, we show that the proposed scheme achieves better prediction accuracy compared with other fuzzy and non-fuzzy rule-based classification systems proposed in the past.
doi:10.1007/978-3-540-77226-2_56 dblp:conf/ideal/FakhrahmadZJ07 fatcat:4owdfevxdvbjrodozeaexlfpdy