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Author Kuo-Lung Wu
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Algorithm design and analysis ♦ Partitioning algorithms ♦ Clustering algorithms ♦ Robustness ♦ Iterative algorithms ♦ Shape ♦ Euclidean distance ♦ Quantization ♦ Unsupervised learning ♦ Clustering methods
Abstract In the traditional fuzzy c-means clustering algorithm, nearly no data points have a membership value one. Özdemir and Akarum proposed a partition index maximization (PIM) algorithm which allows the data points can whole belonging to one cluster. This modification can form a core for each cluster and data points inside the core will have membership value {0,1}. In this paper, we will discuss the parameter selection problems and robust properties of the PIM algorithm.
Description Author affiliation: Department of Information Management, Kun Shan University, Yunk-Kang, Tainan 71023, Taiwan (Kuo-Lung Wu)
ISBN 9781424435968
ISSN 10987584
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2009-08-20
Publisher Place South Korea
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 359.02 kB
Page Count 6
Starting Page 1785
Ending Page 1790

Source: IEEE Xplore Digital Library