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
来源：
SWARM AND EVOLUTIONARY COMPUTATION | 2017年 / 32卷
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
[21]  
[Anonymous], P WORKSH WEB MIN SIA
[22]  
[Anonymous], P 33 HAW INT C SYST
[23]  
[Anonymous], Pattern Recognition with Fuzzy Objective Function Algorithms, DOI 10.1007/978-1-4757-0450-1_3
[24]  
[Anonymous], INT J INF TECHNOL
[25]  
[Anonymous], 2000, Data Mining: Practical Machine Learning Tools with Java Implementations
[26]  
Bache K., 2013, UCI Machine Learning Repository
[27]  
Ball GH., 1965, ISODATA NOVEL METHOD
[28]   Genetic clustering for automatic evolution of clusters and application to image classification [J].
Bandyopadhyay, S ;
Maulik, U .
PATTERN RECOGNITION, 2002, 35 (06) :1197-1208
[29]   Nonparametric genetic clustering: Comparison of validity indices [J].
Bandyopadhyay, S ;
Maulik, U .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2001, 31 (01) :120-125
[30]   A point symmetry-based clustering technique for automatic evolution of clusters [J].
Bandyopadhyay, Sanghamitra ;
Saha, Sriparna .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2008, 20 (11) :1441-1457
12345678910