Progress of Studies on Pattern Recognition Clustering Algorithm

被引:0
作者
Wu, XingHui [1 ]
Long, HaiXia [1 ]
Shi, ZaiFeng [2 ]
机构
[1] Hainan Normal Univ, Coll Informat Sci, Haikou 571158, Peoples R China
[2] Hainan Normal Univ, Coll Chem & Chem Engn, Haikou 571158, Peoples R China
来源
2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING APPLICATIONS (CSEA 2015) | 2015年
关键词
Pattern recognition; clustering algorithm; progress;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper, clustering algorithms in pattern recognition are reviewed. The sequential algorithm, hierarchical algorithms and clustering algorithm based on cost function optimization are mainly discussed.
引用
收藏
页码:1 / 4
页数:4
相关论文
共 25 条
[1]   A new clustering algorithm based on near neighbor influence [J].
Chen, Xinquan .
EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (21) :7746-7758
[2]  
Francisco A.T.C., 2015, NEUROCOMPUTING, V163, P115
[3]  
Gerhard X.R., 2015, PATTERN RECOGN, V48, P918
[4]   NCM: Neutrosophic c-means clustering algorithm [J].
Guo, Yanhui ;
Sengur, Abdulkadir .
PATTERN RECOGNITION, 2015, 48 (08) :2710-2724
[5]  
Helton H.C.J., 2013, COMPUTER METHODS PRO, V110, P447
[6]  
Ioannis P., 2015, ENG APPL ARTIF INTEL, V38, P1
[7]   Interval-valued possibilistic fuzzy C-means clustering algorithm [J].
Ji, Zexuan ;
Xia, Yong ;
Sun, Quansen ;
Cao, Guo .
FUZZY SETS AND SYSTEMS, 2014, 253 :138-156
[8]   A new credibilistic clustering [J].
Kalhori, M. Rostam Niakan ;
Zarandi, M. H. Fazel ;
Turksen, I. B. .
INFORMATION SCIENCES, 2014, 279 :105-122
[9]  
Krisztian B., 2014, EXPERT SYSTEMS APPL, V41, P4148
[10]  
Laszlo S., 2014, NEUROCOMPUTING, V139, P298