A Constructing Method of Fuzzy Classifier Using Kernel K-means Clustering Algorithm

被引:0
|
作者
Yang, Aimin [1 ]
Li, Qing [2 ]
Li, Xinguang [1 ]
机构
[1] Guangdong Univ Foreign Studies, Sch Informat, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Univ Foreign Studies, Sch Business, Guangzhou, Guangdong, Peoples R China
关键词
fuzzy classifier; kernel k-means clustering; triangle membership function; genetic algorithms; fuzzy rule; FEATURE SPACE;
D O I
10.1109/KAM.2009.5
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
A constructing method of fuzzy classifier using kernel k-means clustering algorithm is instroduced in this paper. This constructing method are divided into three phases,namely clustering phase,fuzzy rule created phanse and parameters modified phase. firstly, the original sample space is mapped into a high dimensional feature space by selecting appropriate kernel function. In the feature space, training samples are grouped into some clusters by kernel k-means clustering algorithm. Then for each created cluster, a fuzzy rule is defined whith the appropriate membership function. Finally, Some parameters of fuzzy classifier are chosen by GAs. The experiment results show the proposed fuzzy classifer has very high classification accuracy by the the comparision results with the similar approach,and has the better applied values.
引用
收藏
页码:73 / +
页数:2
相关论文
共 50 条
  • [1] Soil data clustering by using K-means and fuzzy K-means algorithm
    Hot, Elma
    Popovic-Bugarin, Vesna
    2015 23RD TELECOMMUNICATIONS FORUM TELFOR (TELFOR), 2015, : 890 - 893
  • [2] The Global Kernel k-Means Clustering Algorithm
    Tzortzis, Grigorios
    Likas, Aristidis
    2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 1977 - 1984
  • [3] An Improved Kernel K-means Clustering Algorithm
    Liu, Yang
    Yin, Hong Peng
    Chai, Yi
    PROCEEDINGS OF 2016 CHINESE INTELLIGENT SYSTEMS CONFERENCE, VOL I, 2016, 404 : 275 - 280
  • [4] The Hybrid of Kernel K-Means and Fuzzy Kernel C-Means Clustering Algorithm in Diagnosing Thalassemia
    Rustam, Zuherman
    Hartini, Sri
    Saragih, Glori S.
    Darmawan, Nurlia A.
    Aurelia, Jane E.
    ADVANCED INTELLIGENT SYSTEMS FOR SUSTAINABLE DEVELOPMENT (AI2SD'2020), VOL 1, 2022, 1417 : 494 - 505
  • [5] A Fuzzy Clustering Algorithm Based on K-means
    Yan, Zhen
    Pi, Dechang
    ECBI: 2009 INTERNATIONAL CONFERENCE ON ELECTRONIC COMMERCE AND BUSINESS INTELLIGENCE, PROCEEDINGS, 2009, : 523 - 528
  • [6] K-means clustering algorithm in kernel function space
    Liang, JZ
    Wang, JY
    Xu, XB
    PROGRESS IN INTELLIGENCE COMPUTATION & APPLICATIONS, 2005, : 642 - 646
  • [7] A heuristic K-means clustering algorithm by kernel PCA
    Xu, MT
    Fränti, P
    ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5, 2004, : 3503 - 3506
  • [8] Clustering of Image Data Using K-Means and Fuzzy K-Means
    Rahmani, Md. Khalid Imam
    Pal, Naina
    Arora, Kamiya
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2014, 5 (07) : 160 - 163
  • [9] A Kernel K-means Clustering Algorithm Based on an Adaptive Mahalanobis Kernel
    Ferreira, Marcelo R. P.
    de Carvalho, Francisco de A. T.
    PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2014, : 1885 - 1892
  • [10] Automated Detection of Glaucoma Using Fuzzy K-Means Algorithm and Fuzzy Sugeno Classifier
    Yun, Wong Li
    Koh, Joel E. W.
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2013, 3 (04) : 592 - 597