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Robust fuzzy clustering neural network based on ɛ-insensitive loss function

Authors :
Deng Zhaohong
Korris Fu-Lai Chung
Hu Dewen
Shitong Wang
Source :
Applied Soft Computing. 7:577-584
Publication Year :
2007
Publisher :
Elsevier BV, 2007.

Abstract

In the paper, as an improvement of fuzzy clustering neural network FCNN proposed by Zhang et al., a novel robust fuzzy clustering neural network RFCNN is presented to cope with the sensitive issue of clustering when outliers exist. This new algorithm is based on Vapnik's @?-insensitive loss function and quadratic programming optimization. Our experimental results demonstrate that RFCNN has much better robustness for outliers than FCNN.

Details

ISSN :
15684946
Volume :
7
Database :
OpenAIRE
Journal :
Applied Soft Computing
Accession number :
edsair.doi...........c8c8c91ce277962f3861e6e8a18f5a41