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|Title:||A rough-set based incremental approach for updating attribute reduction under dynamic incomplete decision systems|
|Citation:||Proceedings of the 2013 IEEE International Conference on Fuzzy Systems, FUZZ: pp.1-7|
|Conference Name:||IEEE International Conference on Fuzzy Systems (2013 : Hyderabad, India)|
|Wenhao Shu and Hong Shen|
|Abstract:||Efficient attribute reduction in large-scale incomplete decision systems is a challenging problem. The computation of tolerance classes induced by the condition attributes in the incomplete decision system is a key part among all existing attribute reduction algorithms. Moreover, updating attribute reduction for dynamically-increasing decision systems has attracted much attention, in view of that incremental attribute reduction algorithms in a dynamic incomplete decision system have not yet been sufficiently discussed so far. In this paper, we first introduce a simpler way of computing tolerance classes than the classical method. Then we present an incremental attribute reduction algorithm to compute an attribute reduct for a dynamically-increasing incomplete decision system. Compared with the non-incremental algorithms, our incremental attribute reduction algorithm can compute a new attribute reduct in much shorter time. Experiments on four data sets downloaded from UCI show that the feasibility and effectiveness of the proposed incremental algorithm.|
Incomplete decision systems
Rough set theory
|Rights:||Copyright status unknown|
|Appears in Collections:||Aurora harvest|
Computer Science publications
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