Abstract
Fuzzy rough set theory was introduced as a useful mathematical tool to handle real-valued data. Unluckily, its sensitivity to noise has a great impact on the application in real world. So it is necessary to enhance the robustness of fuzzy rough sets. In this work, based on the minimum enclosing ball problem we introduce a robust model of fuzzy rough sets. In addition, we define a robust fuzzy dependency function and apply it to evaluate features corrupted by noise. Experimental results show that the new model is robust to noise. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
An, S., Hu, Q., & Yu, D. (2010). A robust fuzzy rough set model based on minimum enclosing ball. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6401 LNAI, pp. 102–109). https://doi.org/10.1007/978-3-642-16248-0_19
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