期刊名称：International Journal of Computer Science and Network Solutions
印刷版ISSN：2345-3397
出版年度：2014
卷号：2
期号：3
页码：128-136
出版社：International Journal of Computer Science and Network Solutions
摘要：Data mining usually means the approaches and appliances for the valid new knowledge discovery from databases. A response model can be built as a decision model for prediction or classification of a domain problem potential like expert systems. This paper addresses the famous classification task of data mining, where the objective is to predict the class which an example belongs to. Discovered knowledge is expressed in the form of high-level, easy-to-interpret classification rules. In order to discover classification rules, we propose a hybrid meta-heuristic/fuzzy system. In this paper we have used Genetic Algorithm as meta-heuristic algorithm which extracts optimized fuzzy if-then rules for classification patterns. Fuzzy rules are desirable because of their interpretability by human experts. Genetic Algorithm is employed as evolutionary algorithm to optimize the obtained set of fuzzy rules. Results on breast cancer data set from UCI machine learning repository show that the proposed approach would be incapable of classifying cancer patterns with high accuracy rate in order to adequate interpretability of extracted rules
关键词：Classification; Meta-Heuristic; Genetic Algorithm; Fuzzy system; Breast Cancer; If then Rules.
