基于(α,τ)限制相似关系的变精度粗糙集模型

Variable precision rough sets model based on(α,τ) limited similarity relation

针对经典粗糙集模型只能处理完备信息系统,将变精度粗糙集模型引入到不完备信息系统中。给出了(α,τ)限制相似关系的定义及其相关性质,并提出了基于(α,τ)限制相似关系的变精度粗糙集模型,提出了基于属性重要度和近似分类质量的知识约简算法。通过算例分析验证了该模型知识约简算法的有效性。

In view of the classical rough sets model can only dispose the complete information system, a variable precision rough sets model is introduced to dispose the incomplete information system. Firstly, the definition of （α,τ） limited similarity relation and its some interrelated characters are presented, and a variable precision rough sets model based on （α,τ） limited similarity relation is introduced. Secondly, the knowledge reduction algorithm based on attribute significance and the quality of approximate classification is proposed. Finally, an example is given to illustrate the validity of the proposed algorithm.