A similarity-based robust clustering method

This paper presents an alternating optimization clustering procedure called a similarity-based clustering method (SCM). It is an effective and robust approach to clustering on the basis of a total similarity objective function related to the approximate density shape estimation. We show that the dat...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 26; no. 4; pp. 434 - 448
Main Authors:	Yang, Miin-Shen, Wu, Kuo-Lung
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.04.2004 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Artificial Intelligence Cluster Analysis Clustering algorithms Clustering methods Computer Simulation Data mining Fuzzy Logic Image Interpretation, Computer-Assisted - methods Information Storage and Retrieval - methods Mathematical models Noise robustness Noise shaping Numerical Analysis, Computer-Assisted Optimization methods Pattern recognition Pattern Recognition, Automated Prototypes Reproducibility of Results Sensitivity analysis Sensitivity and Specificity Shape Signal Processing, Computer-Assisted Studies Subtraction Technique
ISSN:	0162-8828, 1939-3539
Online Access:	Get full text
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