Abstract
Multi-sphere Support Vector Data Description (MS-SVDD) has been proposed in our previous work. MS-SVDD aims to build a set of spherically shaped boundaries that provide a better data description to the normal dataset and an iterative learning algorithm that determines the set of spherically shaped boundaries. MS-SVDD could improve classification rate for one-class classification problems comparing with SVDD. However MS-SVDD requires a small abnormal data set to build the spherically shaped boundaries for the normal data set. In this paper, we propose a new fuzzy MS-SVDD that can be used when only the normal data set is available. Experimental results on 14 well-known datasets and a comparison between fuzzy MS-SVDD and SVDD are also presented
Original language | English |
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Title of host publication | 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) |
Editors | Hussein Abbass |
Place of Publication | New York |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1956-1960 |
Number of pages | 5 |
ISBN (Print) | 9781467315050 |
DOIs | |
Publication status | Published - 2012 |
Event | WCCI 2012 IEEE World Congress on Computational Intelligence - Brisbane, Brisbane, Australia Duration: 10 Jun 2012 → 15 Jun 2012 |
Conference
Conference | WCCI 2012 IEEE World Congress on Computational Intelligence |
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Country/Territory | Australia |
City | Brisbane |
Period | 10/06/12 → 15/06/12 |