Abstract
On fundamental aspect of variable precision rough approximate reduction is an important mechanism for knowledge discovery. This paper mainly deals with attribute reductions of an inconsistent decision information system based on a dependence space. Through the concept of inclusion degree, a generalized decision distribution function is first constructed. A decision distribution relation is then defined. On the basis of this decision distribution relation, a dependence analogy relation representation of VPRS data space is proposed, and an equivalence congruence based on the attribute sets is also obtained. Applying the congruence on a dependence space, new approaches to find a distribution consistent set are formulated. The theorems for judging distribution consistent sets are also established by using these congruences and the decision distribution relation.
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Liu, B., Guo, H. (2011). Theory and Algorithm Based on the General Similar Relationship between the Approximate Reduction. In: Liu, B., Chai, C. (eds) Information Computing and Applications. ICICA 2011. Lecture Notes in Computer Science, vol 7030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25255-6_17
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DOI: https://doi.org/10.1007/978-3-642-25255-6_17
Publisher Name: Springer, Berlin, Heidelberg
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