A Heuristic Algorithm of Knowledge Reduction
一种启发式知识约简算法

In rough sets theory, reduction of attributes is an important issue. It has been proved that computing all re- ductions or the minimal reduction of decision table is a NP-hard problem. Now, many algorithms for reduction of at- tributes are still heuristic algorithms. In this paper, new heuristic information is proposed. We consider boundary re- gion (complement of positive region) can affect reducing attributes in inconsistent decision table, so we use not only positive region but also boundary region to calculate this heuristic information. Based on this new heuristic information. We develop heuristic algorithm for reduction of attributes in inconsistent decision table. In order to test efficiency of the algorithm, an example is analyzed and some experiments are made. The analysis and experimental results show that the algorithm is efficient and capable of finding the minimal or suboptimal reduction in most of cases.