Title of article :
A Model of Immune Gene Expression Programming for Rule Mining
Author/Authors :
Zeng, Tao Sichuan University - School of Computer, China , Tang, Changjie Sichuan University - School of Computer, China , Xiang, Yong Chengdu Electromechanical College, China , Chen, Peng Sichuan University - School of Computer, China , Liu, Yintian Sichuan University - School of Computer, China
Abstract :
Abstract: Rule mining is an important issue in data mining. To address it, a novel Immune Gene Expression Programming (IGEP) model was proposed. Concepts of rule, gene, immune cell, and antibody were formalized. The dynamic evolution models and the corresponding recursive equations of immune cell, self, immune-tolerance were built. The novel key techniques of IGEP were presented. Experiment results showed that the new method has good stability, scalability and flexibility. It can discover traditional association rule, non-traditional rule including connective “OR” or “NOT”, and meta-rule of strong rule. Furthermore, it can perform well in constrained pattern mining.
Keywords :
Data mining , Rule , Meta , rule , Evolutionary algorithm , Gene expression programming , Artifical immune system
Journal title :
Journal of J.UCS (Journal of Universal Computer Science)
Journal title :
Journal of J.UCS (Journal of Universal Computer Science)
