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Content Provider | IEEE Xplore Digital Library |
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Author | Yosung Shim Jiwon Chung In-Chan Choi |
Copyright Year | 2006 |
Description | Author affiliation: Dept. of Ind. Syst. & Inf. Eng., Korea Univ., Seoul (Yosung Shim; Jiwon Chung; In-Chan Choi) |
Abstract | Cluster analysis is widely used in the initial stages of data analysis and data reduction. The K-means algorithm, a nonhierarchical clustering algorithm, has regained popularity among researchers in data mining and knowledge discovery, partly because of its low time complexity. The algorithm requires the number of clusters as an input parameter. When the parameter value is not known a priori, a researcher often has to use a cluster validity index to search for a suitable parameter value. In this study, we use computational experiments to examine the performance of cluster validity indices with the K-means algorithm. Our analysis parallels the study performed by Milligan and Cooper on cluster validity indices; we use hierarchical clustering algorithms and present observations and conclusions resulting from the simulation study |
Sponsorship | IEEE Comput Intelligence Soc. Eur. Soc. for Fuzzy Logic and Technol. Eur. Neural Networks Soc. Int. Assoc. for Fuzzy Set in Manage. and Economy Japan Soc. for Fuzzy Theor. and Soc. for Fuzzy Theor. and Intelligent Informatics Taiwan Fuzzy Syst. Assoc. World Wide Web Bus. Intelligence Hungarian Fuzzy Assoc. Univ. of Canberra |
Starting Page | 199 |
Ending Page | 204 |
File Size | 176758 |
Page Count | 6 |
File Format | |
ISBN | 0769525040 |
DOI | 10.1109/CIMCA.2005.1631265 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-11-28 |
Publisher Place | Austria |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Algorithm design and analysis Data analysis Computational modeling Clustering algorithms Data engineering Systems engineering and theory Educational institutions Partitioning algorithms Data mining Information analysis |
Content Type | Text |
Resource Type | Article |
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