Robust fuzzy clustering neural network based on ?-insensitive loss function |
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| Affiliation: | 1. Xi’an Research Institute of Hi-Tech, Xi’an, Shaanxi 710025, China;2. The Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi’an 710072, China;1. Centro de Informatica, Universidade Federal de Pernambuco, Av. Jornalista Anibal Fernandes s/n - Cidade Universitaria, CEP, Recife, PE 50740-560, Brazil;2. Departamento de Estatistica, Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraiba, CEP, João Pessoa, PB 58051-900, Brazil |
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| 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. |
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