Title of article :
Fuzzy multi-class classifier based on support vector data description and improved PCM
Author/Authors :
Zhang، نويسنده , , Yong and Chi، نويسنده , , Zhong-Xian and Li، نويسنده , , Ke-Qiu، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
5
From page :
8714
To page :
8718
Abstract :
In this paper, a novel fuzzy classifier for multi-classification problems, based on support vector data description (SVDD) and improved PCM, is proposed. The proposed method is the robust version of SVDD by assigning a weight to each data point, which represents fuzzy membership degree of the cluster computed by the improved PCM method. Accordingly, this paper presents the multi-classification algorithm based on the robust weighted SVDD, and gives the simple classification rule. Experimental results show that the proposed method can reduce the effect of outliers and yield higher classification rate.
Keywords :
Support vector data description , Possibilistic c-means algorithm , classifier , SVM , Minimum enclosing sphere
Journal title :
Expert Systems with Applications
Serial Year :
2009
Journal title :
Expert Systems with Applications
Record number :
2346611
Link To Document :
بازگشت