SOM-ELM Self-Organized Clustering using ELM

被引:18
作者
Miche, Yoan [1 ,7 ]
Akusok, Anton [2 ,3 ]
Veganzones, David [4 ]
Bjork, Kaj-Mikael [5 ]
Severin, Eric [4 ]
du Jardin, Philippe [6 ]
Termenon, Maite [8 ,9 ]
Lendasse, Amaury [2 ,3 ,5 ]
机构
[1] Aalto Univ, Sch Sci, Dept Informat & Comp Sci, FI-00076 Aalto, Finland
[2] Univ Iowa, Dept Mech & Ind Engn, Iowa City, IA 52242 USA
[3] Univ Iowa, Iowa Informat Initiat, Iowa City, IA 52242 USA
[4] Univ Lille 1, F-59043 Lille, France
[5] Arcada Univ Appl Sci, Helsinki 00550, Finland
[6] EDHEC Business Sch, F-06202 Nice 3, France
[7] Nokia Solut & Networks Grp, Espoo, Finland
[8] INSERM, U836, F-38043 Grenoble, France
[9] Univ Grenoble Alpes, GIN, F-38000 Grenoble, France
关键词
ELM; Self-Organized; SOM; Clustering; MAP; NETWORKS;
D O I
10.1016/j.neucom.2015.03.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents two new clustering techniques based on Extreme Learning Machine (ELM). These clustering techniques can incorporate a priori knowledge (of an expert) to define the optimal structure for the clusters, i.e. the number of points in each cluster. Using ELM, the first proposed clustering problem formulation can be rewritten as a Traveling Salesman Problem and solved by a heuristic optimization method. The second proposed clustering problem formulation includes both a priori knowledge and a self-organization based on a predefined map (or string). The clustering methods are successfully tested on 5 toy examples and 2 real datasets. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:238 / 254
页数:17
相关论文
共 36 条
[1]  
[Anonymous], 2006, Pattern Recognition and Machine Learning. Information Science and Statistics, DOI DOI 10.1007/978-0-387-45528-0
[2]   Solving large-scale retrofit heat exchanger network synthesis problems with mathematical optimization methods [J].
Björk, KM ;
Nordman, R .
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2005, 44 (08) :869-876
[3]   Extreme Learning Machines [J].
Cambria, Erik ;
Huang, Guang-Bin .
IEEE INTELLIGENT SYSTEMS, 2013, 28 (06) :30-31
[4]   The description of personality: Basic traits resolved into clusters [J].
Cattell, RB .
JOURNAL OF ABNORMAL AND SOCIAL PSYCHOLOGY, 1943, 38 (04) :476-506
[5]  
Cottrell M., 1993, New Trends in Neural Computation. International Workshop on Artificial Neural Networks. IWANN '93 Proceedings, P305
[6]   MAXIMUM LIKELIHOOD FROM INCOMPLETE DATA VIA EM ALGORITHM [J].
DEMPSTER, AP ;
LAIRD, NM ;
RUBIN, DB .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1977, 39 (01) :1-38
[7]   Mixture of Gaussians for distance estimation with missing data [J].
Eirola, Emil ;
Lendasse, Amaury ;
Vandewalle, Vincent ;
Biernacki, Christophe .
NEUROCOMPUTING, 2014, 131 :32-42
[8]  
Ester M., 1996, KDD 96 P 2 INT C KNO, P226, DOI DOI 10.5555/3001460.3001507
[9]  
Estivill-Castro Vladimir, 2002, ACM SIGKDD Explorations Newsletter, V4, P65, DOI [DOI 10.1145/568574.568575, 10.1145/568574.568575]
[10]   Self-organizing map and clustering for wastewater treatment monitoring [J].
García, HL ;
González, LM .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2004, 17 (03) :215-225