Rough set Based Clustering of the Self Organizing Map

被引：3

作者：

Mohebi, E. ^{[1
]}

Sap, M. N. N. ^{[1
]}

机构：

[1] Univ Technol Malaysia, Fac Comp Sci & Informat Syst, Johor Baharu 81310, Malaysia

来源：

2009 FIRST ASIAN CONFERENCE ON INTELLIGENT INFORMATION AND DATABASE SYSTEMS | 2009年

关键词：

clustering; overlapped data; SOM; uncertainty; Rough set;

D O I：

10.1109/ACIIDS.2009.79

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Kohonen Self Organizing Map (SOM) is an excellent tool in exploratory phase of data mining. The SOM is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. When the number of SOM units is large, to facilitate quantitative analysis of the map and the data, similar units needs to be grouped i.e., clustered In this paper a two-level clustering based on SOM is proposed, which employs rough set theory to capture the inherent uncertainty involved in cluster analysis. The two-stage procedure (first using SOM to produce the prototypes that are then clustered in the second stage) is found to perform well when compared with crisp clustering of the data and increase the accuracy.

引用

页码：82 / 85

页数：4

共 50 条

[21] A rough set based map granule
Sonamthiang, Sumalee
Cercone, Nick
Naruedomkul, Kanlaya
ROUGH SETS AND INTELLIGENT SYSTEMS PARADIGMS, PROCEEDINGS, 2007, 4585 : 290 - +
[22] An clustering algorithm based on rough set
Xu, E.
Gao Xuedong
Sen, Wu
Bin, Yu
2006 3RD INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2006, : 466 - 469
[23] Correction to: An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis
Sobhan Sarkar
Numan Ejaz
J. Maiti
Anima Pramanik
Neural Computing and Applications, 2022, 34 : 21413 - 21413
[24] A self-organizing map for clustering probabilistic models
Hollmén, J
Tresp, V
Simula, O
NINTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS (ICANN99), VOLS 1 AND 2, 1999, (470): : 946 - 951
[25] REFINING OF IMAGE USING SELF -ORGANIZING MAP WITH CLUSTERING
Dahiya, Neeraj
Dalal, Surjeet
Tanwar, Gundeep
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS (ICCS-2015), 2016, 1715
[26] Reliable hierarchical clustering with the self-organizing map
Samsonova, EV
Bäck, T
Kok, JN
IJzerman, AP
ADVANCES IN INTELLIGENT DATA ANALYSIS VI, PROCEEDINGS, 2005, 3646 : 385 - 396
[27] Clustering method using self-organizing map
Endo, Masahiro
Ueno, Masahiro
Tanabe, Takaya
Yamamoto, Manabu
Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, 2000, 1 : 261 - 270
[28] Clustering method using self-organizing map
Endo, M
Ueno, M
Tanabe, T
Yamamoto, M
NEURAL NETWORKS FOR SIGNAL PROCESSING X, VOLS 1 AND 2, PROCEEDINGS, 2000, : 261 - 270
[29] Clustering writing styles with a Self-Organizing Map
Vuori, V
EIGHTH INTERNATIONAL WORKSHOP ON FRONTIERS IN HANDWRITING RECOGNITION: PROCEEDINGS, 2002, : 345 - 350
[30] Fast Growing Self Organizing Map for Text Clustering
Matharage, Sumith
Alahakoon, Damminda
Rajapakse, Jayantha
Huang, Pin
NEURAL INFORMATION PROCESSING, PT II, 2011, 7063 : 406 - +

← 1 2 3 4 5 →