High Speed Training of a Fuzzy Classifier with Polyhedral Regions

In this paper, we discuss a fuzzy classifier with polyhedral regions. First, for each class we generate a hyperbox calculating the minimum and maximum values of the data belonging to the class. Next, we cut the hyperbox using training data belonging to the other classes so that class separability is...

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Bibliographic Details
Published inTransactions of the Institute of Systems, Control and Information Engineers Vol. 15; no. 12; pp. 673 - 680
Main Authors TAKIGAWA, Tomoo, ABE, Shigeo
Format Journal Article
LanguageJapanese
Published THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE) 15.12.2002
Subjects
convex hull
fuzzy classifiers
pattern recognition
polyhedral regions
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Summary:In this paper, we discuss a fuzzy classifier with polyhedral regions. First, for each class we generate a hyperbox calculating the minimum and maximum values of the data belonging to the class. Next, we cut the hyperbox using training data belonging to the other classes so that class separability is maximized. Finally, for each convex polyhedron we define a membership function using the minimum operator. We demonstrate the superiority of our method over our previously developed classifier with polyhedral regions using thyroid, numeral, hiragana, and blood cell data sets.
ISSN:1342-5668
2185-811X
DOI:10.5687/iscie.15.673