Abstract
Beaubouef, Petry and Buckles proposed the generalized rough set database analysis (GRSDA) to discuss rough relational databases. Given any rough relational database (U, A) and an attribute a ∈ A, as in rough set theory, a definition of the lower and upper approximations based on φ, a is given. The entropy and conditional entropy of similarity relations in a rough relational database are defined. The examples show that the entropy of a similarity relation does not decrease as the similarity relation is refined. It will be proved that given any two similarity relations φ and ψ, defined by a set C of conditional attributes and a decision attribute d, respectively, if d similarly depends on C in a rough relational database then the conditional entropy of φ with respect to ψ is equal to the entropy of φ.
The project was partially supported by the National NSF of China and the National 973 Project of China under the grant number G1999032701. The first author was partially supported by the National Laboratory of Software Development Environment. The second auther was partially supported by the Yunnan Provincial NSF grant 2000F0049M and 2001F0006Z.
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References
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© 2003 Springer-Verlag Berlin Heidelberg
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Sui, Y., Xia, Y., Wang, J. (2003). The Information Entropy of Rough Relational Databases. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_48
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DOI: https://doi.org/10.1007/3-540-39205-X_48
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