期刊
FUZZY SETS AND SYSTEMS
卷 183, 期 1, 页码 26-43出版社
ELSEVIER
DOI: 10.1016/j.fss.2011.01.016
关键词
Approximate reasoning; Decision analysis; Fuzzy statistics and data analysis; Fuzzy rough sets; Robustness
资金
- National Natural Science Foundation of China [60703013, 10978011]
- Hong Kong Polytechnic University [G-YX3B]
- National Science Fund for Distinguished Young Scholars [50925625]
Fuzzy rough sets, generalized from Pawlak's rough sets, were introduced for dealing with continuous or fuzzy data. This model has been widely discussed and applied these years. It is shown that the model of fuzzy rough sets is sensitive to noisy samples, especially sensitive to mislabeled samples. As data are usually contaminated with noise in practice, a robust model is desirable. We introduce a new model of fuzzy rough set model, called soft fuzzy rough sets, and design a robust classification algorithm based on the model. Experimental results show the effectiveness of the proposed algorithm. (C) 2011 Elsevier B.V. All rights reserved.
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