Computer Science ›› 2016, Vol. 43 ›› Issue (5): 230-233.doi: 10.11896/j.issn.1002-137X.2016.05.042

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Fuzzy Support Vector Data Description with Centers of Classes Distance

WANG Min-guang and WANG Zhe   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Support vector data description(SVDD) ignores the importance of sample distribution.This paper proposed a new method called fuzzy SVDD with centers of classes distance,and it had been applied on the UCI data sets.The algorithm uses ratio of the distance of sample to the centers of two classes to give each sample a weight.The important samples’ weights should be increased and the others should be not,which can highlight the difference of samples.The results show that our algorithm has better performance than SVDD.

Key words: Pattern recognition,Support vector data description,Weight

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