A method of uncertainty measure based on rough set

Rough set is a new mathematical theory for dealing with uncertain and imprecise information. In view of it widely applied to data analysis, how to measure effectively the uncertainty is a meaningful issue. First, several main methods of uncertainty measure are introduced and their advantages and disadvantages are analyzed and compared; Second, combined with rough entropy, precision, inclusion degree, a new method of uncertainty measure, which is used to measure the uncertainty of rough set, is proposed. Finally, the proposed method is tested and compared with other methods of uncertainty measure. Experimental results show that it is effective and make the uncertainty measure more precise and complete.

[1]  Guo-Sheng Liu,et al.  An improved adi-fdtd method with lower splitting error , 2008, 2008 12th International Conference on Mathematical Methods in Electromagnetic Theory.

[2]  M. J. Wierman,et al.  MEASURING UNCERTAINTY IN ROUGH SET THEORY , 1999 .

[3]  Qinghua Hu,et al.  Uncertainty measures for fuzzy relations and their applications , 2007, Appl. Soft Comput..

[4]  Theresa Beaubouef,et al.  Information-Theoretic Measures of Uncertainty for Rough Sets and Rough Relational Databases , 1998, Inf. Sci..

[5]  Zdzislaw Pawlak,et al.  Rough sets and intelligent data analysis , 2002, Inf. Sci..

[6]  Jiye Liang,et al.  The Information Entropy, Rough Entropy And Knowledge Granulation In Rough Set Theory , 2004, Int. J. Uncertain. Fuzziness Knowl. Based Syst..