An incremental attribute reduction algorithm in decision table

Attribute reduction is one of the key problems in Rough Set theory, and many algorithms have been proposed for static data. Very little work has been done in incremental attribute reduction algorithm. In this paper, an incremental attribute reduction algorithm is present. In order to reduce the computational complexity, a fast counting sort algorithm is introduced for dealing with redundant and inconsistent data in decision tables. When the objects in decision table increase dynamically, a new reduct can be updated by the old reduct effectively. Experiments show that our algorithm outperforms other incremental attribute reduction algorithms.