A comprehensive survey of traditional, merge-split and evolutionary approaches proposed for determination of cluster number

被引:83
作者
Hancer, Emrah [1 ]
Karaboga, Dervis [2 ]
机构
[1] Mehmet Akif Ersoy Univ, Dept Comp Technol & Informat Syst, TR-15039 Burdur, Turkey
[2] Erciyes Univ, Dept Comp Engn, TR-38039 Kayseri, Turkey
关键词
Clustering; Validity indexes; Automatic cluster evolution; Knee point; Evolutionary algorithms; MULTIOBJECTIVE DIFFERENTIAL EVOLUTION; PARTICLE SWARM OPTIMIZATION; BEE COLONY ALGORITHM; GENETIC ALGORITHM; AUTOMATIC EVOLUTION; PIXEL CLASSIFICATION; PATTERN-RECOGNITION; VALIDITY MEASURE; JUMPING-GENES; VALIDATION;
D O I
10.1016/j.swevo.2016.06.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Today's data mostly does not include the knowledge of cluster number. Therefore, it is not possible to use conventional clustering approaches to partition today's data, i.e., it is necessary to use the approaches that automatically determine the cluster number or cluster structure. Although there has been a considerable attempt to analyze and categorize clustering algorithms, it is difficult to find a survey paper in the literature that has thoroughly focused on the determination of cluster number. This significant issue motivates us to introduce concepts and review methods related to automatic cluster evolution from a theoretical perspective in this study. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:49 / 67
页数:19
相关论文
共 215 条
[11]  
[Anonymous], 2000, Icml
[12]  
[Anonymous], 1985, P 7 ANN C COGN SCI S
[13]  
[Anonymous], DATA MINING ANAL FUN
[14]  
[Anonymous], INT S MOD IMPL COMPL
[15]  
[Anonymous], CORR
[16]  
[Anonymous], 2007, Scholarpedia, DOI [10.4249/scholarpedia.1568, DOI 10.4249/SCHOLARPEDIA.1568]
[17]  
[Anonymous], 2004, REV MACH LEARN TECH
[18]  
[Anonymous], NAACL DEMONSTRATIONS
[19]  
[Anonymous], 2006, NEURIPS
[20]  
[Anonymous], 2001, P 6 INT C PAR PROBL