NDLI: A Constructing Method of Fuzzy Classifier Using Kernel K-Means Clustering Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Aimin Yang Qing Li Xinguang Li
Copyright Year	2009
Abstract	A constructing method of fuzzy classifier using kernel k-means clustering algorithm is introduced in this paper. This constructing method are divided into three phases, namely clustering phase, fuzzy rule created phanse and parameters modified phase. firstly, the original sample space is mapped into a high dimensional feature space by selecting appropriate kernel function. In the feature space, training samples are grouped into some clusters by kernel k means clustering algorithm. Then for each created cluster, a fuzzy rule is defined with the appropriate membership function. Finally, Some parameters of fuzzy classifier are chosen by GAs. The experiment results show the proposed fuzzy classifier has very high classification accuracy by the comparison results with the similar approach, and has the better applied values.
Starting Page	73
Ending Page	76
File Size	457916
Page Count	4
File Format	PDF
ISBN	9780769538884
DOI	10.1109/KAM.2009.5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	triangle membership function Particle separators Knowledge acquisition Clustering methods Partitioning algorithms Electronic mail genetic algorithms kernel k-means clustering Neural networks Clustering algorithms fuzzy rule fuzzy classifier Genetics Kernel Informatics
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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