A New Rough Set Based Classification Rule Generation Algorithm (RGI)

摘要

In medical fields rule based classifiers have an advantage over black box classifiers, because they are understandable and can be integrated into human's knowledge base to assist clinicians in decision-making. This paper proposes a new classification rule inducing algorithm. In comparison with standard rough sets theory it calculates value core without attribute reduction in advance and does not remove examples covered by the newly generated rule. An experiment on 28 medical data sets is executed in comparison with other 14 algorithms, and experimental results show that the proposed method achieves good classification performance.