A Subgroup Discovery Algorithm Based on Genetic Fuzzy Systems
Subgroup discovery algorithm is a new data mining technique,which plays an important role in the induction of large data areas.First,the basic concepts of subgroup discovery algorithm and fuzzy system are introduced.Then subgroup discovery iterative genetic algorithm(SDIGA)is studied.Genetic fuzzy system is used in traditional subgroup discovery algorithm,the way that a weighted sum of multiple objective functions is taken in fitness function.After continuous crossover genetic,the best description of the rules is obtained.Finally,the proposed method is applied to the dataset of compressive strength of concrete in UCI database,and the experiment results show the effectiveness of SDIGA subgroup discovery algorithm.
Subgroup discovery algorithm Genetic fuzzy systems Rules
Shuo Dai Yong Zhang Limin Jia Yong Qin
School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,Beijing 100044,C
国际会议
The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)
福州
英文
171-177
2015-05-08（万方平台首次上网日期，不代表论文的发表时间）