Abstract
The theory of fuzzy rough sets is claimed to be a powerful mathematical tool for dealing with uncertainty in data analysis. Unluckily, the classical model of fuzzy rough sets is sensitive to noisy information. This disadvantage limits the applicability of the model in practice. In this work, we present a robust fuzzy rough set model based on soft minimum enclosing ball, and introduce a new fuzzy dependency function with this model. Some properties of the new model are discussed. Finally, we conduct some experiments to test the effectiveness of the proposed model, and experimental results show that the soft minimum enclosing ball-based fuzzy rough set model is robust to noise.
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