An efficient SFL-based classification rule mining algorithm

Abstract

Classification rule mining is an important data mining process that aims to discover a small set of rules from the training data set with predetermined targets. The shuffled frog leaping(SFL) algorithm, is a new robust evolutionary algorithm based on the local search and the shuffling processes. In this paper, an efficient SFL-based classification rule mining algorithm is proposed. The experimental results show that the proposed algorithm performs much better than other related algorithms.