Association Rule Mining Using Firefly Algorithm
Poonam Sehrawat, Harish Rohil, Chaudhary Devi · 2013
Data mining is the process of extracting previously unknown patterns from large amount of data. Association rule mining is one of very important data mining models. Swarm intelligence is a new subfield of artificial intelligence which studies the collective behavior of groups of simple agents. In this paper, a new efficient approach is proposed for exploring high-quality association rules. The proposed approach is based on firefly algorithm, which is an optimization algorithm used in swarm optimization. The proposed approach mines interesting and understandable association rules in single run without using the minimum support and the minimum confidence thresholds. The proposed approach was implemented using Microsoft Visual Studio 4.0 to prove its efficiency in terms of computation time.