A HEURISTIC GENETIC ALGORITHM OF ATTRIBUTE REDUCTION
An attribute reduction method is proposed based on genetic algorithm (GA) with heuristic information. It separates the approximate core attributes from the whole attributes set, then represents the rest of attributes with a group of genetic chromosomes using binary encoding. This improves the local searching ability of GA in the process of global optimizing. Furthermore, the method designs the fitness function that prefers finding shorter approximate reducts to longer real reducts, which increases the classification accuracy on new data. Experiments of reduction and classification with the proposed method are conducted. The results show this method is effective and efficient with regard to classification accuracy, classifier scale and convergence.
Heuristic Attribute reduction Approximate reduct and core Genetic algorithm
HONG SHI JIN-ZONG FU
School of Computer Science and Technology, Tianjin University, Tianjin 300072 China Beijing YUPONT Electric Power Technology Co., Ltd., Beijing
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2263-2267
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）