Suppressed fuzzy C-means clustering algorithm

被引：141
|
作者：
Fan, JL
Zhen, WZ
Xie, WX
机构：
[1] Xian Inst Post & Telecommun, Dept Informat & Control, Xian 710061, Shaanxi, Peoples R China
[2] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
[3] Shenzhen Univ, Sch Informat Engn, Shenzhen 518060, Peoples R China
来源：
PATTERN RECOGNITION LETTERS | 2003年 / 24卷 / 9-10期
关键词：
fuzzy partition; HCM algorithm; FCM algorithm;
D O I：
10.1016/S0167-8655(02)00401-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Based on the defect of rival checked fuzzy c-means clustering algorithm, a new algorithm: suppressed fuzzy c-means clustering algorithm is proposed. The new algorithm overcomes the shortcomings of the original algorithm, establishes more natural and more reasonable relationships between hard c-means clustering algorithm and fuzzy c-means clustering algorithm. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：1607 / 1612
页数：6
相关论文
共 50 条
  • [1] Generalization rules for the suppressed fuzzy c-means clustering algorithm
    Szilagyi, Laszlo
    Szilagyi, Sandor M.
    NEUROCOMPUTING, 2014, 139 : 298 - 309
  • [2] Modified suppressed relative entropy fuzzy c-means clustering algorithm
    Li, Jing
    Hu, Yifan
    Fan, Jiulun
    Yu, Haiyan
    Jia, Bin
    Liu, Rui
    Zhao, Feng
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (03) : 6995 - 7019
  • [3] Suppressed possibilistic c-means clustering algorithm
    Yu, Haiyan
    Fan, Jiulun
    Lan, Rong
    APPLIED SOFT COMPUTING, 2019, 80 : 845 - 872
  • [4] Analytical and numerical evaluation of the suppressed fuzzy c-means algorithm: a study on the competition in c-means clustering models
    Szilagyi, Laszlo
    Szilagyi, Sandor M.
    Benyo, Zoltan
    SOFT COMPUTING, 2010, 14 (05) : 495 - 505
  • [5] Analytical and numerical evaluation of the suppressed fuzzy c-means algorithm: a study on the competition in c-means clustering models
    László Szilágyi
    Sándor M. Szilágyi
    Zoltán Benyó
    Soft Computing, 2010, 14 : 495 - 505
  • [6] Parameter selection of suppressed relative entropy fuzzy c-means clustering algorithm
    Li, Jing
    Jia, Bin
    Fan, Jiulun
    Yu, Haiyan
    Hu, Yifan
    Zhao, Feng
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (01) : 1213 - 1228
  • [7] A review on suppressed fuzzy c-means clustering models
    Szilagyi, Laszlo
    Lefkovits, Laszlo
    Iclanzan, David
    ACTA UNIVERSITATIS SAPIENTIAE INFORMATICA, 2020, 12 (02) : 302 - 324
  • [8] Parameter selection for suppressed fuzzy c-means clustering algorithm based on fuzzy partition entropy
    Li, Jing
    Fan, Jiulun
    2014 11TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD), 2014, : 82 - 87
  • [9] A Generalized Approach to the Suppressed Fuzzy c-Means Algorithm
    Szilagyi, Laszlo
    Szilagyi, Sandor M.
    Kiss, Csilla
    MODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE (MDAI), 2010, 6408 : 140 - 151
  • [10] A Thorough Analysis of the Suppressed Fuzzy C-Means Algorithm
    Szilagyi, Laszlo
    Szilagyi, Sandor M.
    Benyo, Zoltan
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS, 2008, 5197 : 203 - 210
12345