Title :
Classification rule mining research based on hybrid genetic algorithm
Author :
Wang Xiangrui ; Wang Shuai
Author_Institution :
Sch. of Comput. Sci. & Eng., Jilin Inst. of Archit. & Civil Eng., Changchun, China
Abstract :
Traditional classification rule mining based on genetic algorithm usually exists the problem of low quality of the mined rules, too many redundant rules in the population after optimization, and inaccuracy in classification. The paper analyzes the principles of classification rules mining, and proposes that classification rules mining methods based on hybrid genetic algorithm can effectively overcome the above disadvantages and improve the accuracy of classification rule mining.
Keywords :
data mining; genetic algorithms; pattern classification; classification rule mining research; hybrid genetic algorithm; mined rules; optimization; redundant rules; traditional classification rule mining; Accuracy; Biological cells; Classification algorithms; Data mining; Genetic algorithms; Genetics; Training; Classification Rules; Data Mining; Genetic Algorithm; Hybrid Genetic Algorithms; Local Search;
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
DOI :
10.1109/TMEE.2011.6199200