A Kernel Fuzzy c-Means Clustering-Based Fuzzy Support Vector Machine Algorithm for Classification Problems With Outliers or Noises

Abstract

The support vector machine (SVM) has provided higher performance than traditional learning machines and has been widely applied in real-world classification problems and nonlinear function estimation problems. Unfortunately, the training process of the SVM is sensitive to the outliers or noises in the training set. In this paper, a common misunderstanding… (More)
DOI: 10.1109/TFUZZ.2010.2087382

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@article{Yang2011AKF, title={A Kernel Fuzzy c-Means Clustering-Based Fuzzy Support Vector Machine Algorithm for Classification Problems With Outliers or Noises}, author={Xiaowei Yang and Guangquan Zhang and Jie Lu and Jun Ma}, journal={IEEE Transactions on Fuzzy Systems}, year={2011}, volume={19}, pages={105-115} }