[Objective] Solve the problem of rigid division of the traditional classification and some classification methods only dealing with discrete data. [Methods] The fuzzy comprehensive evaluation method is put forward to realize the fuzzy classification for continuous attributes samples, obtaining the soft classification of samples to categories. In the process, the method of continuous attributes discretization is used to divide attribute interval, and the particle swarm optimization algorithm is used to obtain the optimal weight distribution. The final results are the membership degrees of samples to each category. [Results] This method can effectively achieve the soft division of samples. [Limitations] This method is difficult to divide the attribute whose values is too concentrated. [Conclusions] This fuzzy classification method based on particle swarm optimization and fuzzy comprehensive evaluation is effective and feasible.
殷希红, 乔晓东, 张运良, 李国双. 利用粒子群和模糊综合评判的模糊分类方法[J]. 现代图书情报技术, 2015, 31(9): 46-51.
Yin Xihong, Qiao Xiaodong, Zhang Yunliang, Li Guoshuang. Fuzzy Classification Method Based on Particle Swarm Optimization and Fuzzy Comprehensive Evaluation. New Technology of Library and Information Service, 2015, 31(9): 46-51.
[1] 张小峰, 赵永升, 刘智云, 等. 分类问题中连续属性的离散化方法[J]. 兰州理工大学学报, 2007, 33(1):104-106. (Zhang Xiaofeng, Zhao Yongsheng, Liu Zhiyun, et al. Discretization of Continuous Attributes in Classification Problems [J]. Journal of Lanzhou University of Technology, 2007, 33(1): 104-106.)
[2] Kennedy J, Eberhart R.Particle Swarm Optimization [C]. In: Proceedings of IEEE International Conference on Neural Networks.1995: 1942-1948.
[3] 陈秉正, 韩春鹏. 归纳式学习中连续型数据的区间划分问题[J]. 系统工程理论与实践, 2001, 21(4): 1-7, 18. (Chen Bingzheng, Han Chunpeng. Discretization for Inductive Learning from Continuous Sample Data [J]. Systems Engineering-Theory & Practice, 2001, 21(4): 1-7, 18.)
[4] 陈果. 基于遗传算法的决策表连续属性离散化方法[J]. 仪器仪表学报, 2007, 28(9): 1700-1705. (Chen Guo. Discretization Method of Continuous Attributes in Decision Table Based on Genetic Algorithm [J]. Chinese Journal of Scientific Instrument, 2007, 28(9): 1700-1705.)
[5] Baraldi A, Blonda P. A Survey of Fuzzy Clustering Algorithms for Pattern Recognition [J]. IEEE Transactions on System, Man and Cybernetics, 1999, 29(6): 778-785.
[6] 王熙照, 孙娟, 杨宏伟, 等. 模糊决策树算法与清晰决策树算法的比较研究[J].计算机工程与应用, 2003(21): 72-75, 99. (Wang Xizhao, Sun Juan, Yang Hongwei, et al. A Comparison Between Fuzzy and Crisp Decision Trees [J]. Computer Engineering and Applications, 2003(21): 72-75, 99.)
[7] 孙娟, 王熙照.自适应模糊决策树算法[J]. 计算机工程与设计, 2013, 34(2): 649-653. (Sun Juan, Wang Xizhao.Adaptive Fuzzy Decision Tree Algorithms [J]. Computer Engineering and Design, 2013, 34(2): 649-653.)
[8] 邹晓峰, 陆建江, 宋自林.基于模糊分类关联规则的分类系统[J]. 计算机研究与发展, 2003, 40(5): 651-656. (Zou Xiaofeng, Lu Jianjiang, Song Zilin. A Classification System Based on Fuzzy Class Association Rules [J]. Journal of Computer Research and Development, 2003, 40(5): 651-656.)
[9] 崔建, 李强, 刘勇. 基于模糊分类关联规则的支持向量机分类器生成方法[J]. 计算机应用, 2011, 31(5): 1348-1350, 1366. (Cui Jian, Li Qiang, Liu Yong. Method of SVM Classifier Generation Based on Fuzzy Classification Association Rule [J]. Journal of Computer Applications, 2011, 31(5): 1348-1350, 1366.)
[10] Takagi H. Fusion Technology of Fuzzy Theory and Neural Networks Survey and Future Directions [C]. In: Proceedings of International Conference on Fuzzy Logic and Neural Networks, Japan.1990: 13-26.
[11] 张凯, 钱锋, 刘漫丹. 模糊神经网络技术综述[J]. 信息与控制, 2003, 32(5): 431-435. (Zhang Kai, Qian Feng, Liu Mandan.A Survey on Fuzzy Neural Network Technology [J]. Information and Control, 2003, 32(5): 431-435.)
[12] 杨纶标, 高英仪, 凌卫新. 模糊数学原理及应用[M]. 5版. 广州: 华南理工大学出版社, 2011. (Yang Lunbiao, Gao Yingyi, Ling Weixin. Fuzzy Mathematics Theory and Application [M]. The 5th Edition. Guangzhou: South China University of Technology Press, 2011.)
[13] 谢季坚, 刘承平. 模糊数学方法及其应用[M]. 武汉: 华中科技大学出版社, 2005: 31-36. (Xie Lijian, Liu Chengping. Fuzzy Mathematics Method and Application [M]. Wuhan: Huazhong University of Science & Technology Press, 2005.)
[14] 刘玲, 肖嵘. 连续属性离散化算法SHD及其改进[J]. 计算机工程与应用, 2001, 37(9): 97-99. (Liu Ling, Xiao Rong. The Discretization of Continuous Feature Algorithm SHD and Its Improvement [J]. Computer Engineering and Applications, 2001, 37(9): 97-99.)
[15] Wong A K C, Chiu D K Y. Synthesizing Statistical Knowledge from Incomplete Mixed-mode Data [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, 9(6): 796-805.
[16] Stashuk D W, Naphan R K. Probabilistic Inference Base Classification Applied to Myoelectric Signal Decomposition [J]. IEEE Transactions on Biomedical Engineering, 1992, 39(4): 346-355.