Title :
An efficient SFL-based classification rule mining algorithm
Author :
Yin, Hui ; Cheng, Fengjuan ; Zhou, Chunjie
Author_Institution :
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan
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.
Keywords :
data mining; evolutionary computation; pattern classification; SFL-based classification rule mining algorithm; data mining process; robust evolutionary algorithm; shuffled frog leaping algorithm; Classification algorithms; Control engineering education; Data engineering; Data mining; Databases; Educational technology; Evolutionary computation; Genetics; Robustness; Training data;
Conference_Titel :
IT in Medicine and Education, 2008. ITME 2008. IEEE International Symposium on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-3616-3
Electronic_ISBN :
978-1-4244-2511-2
DOI :
10.1109/ITME.2008.4744012
