基于连续型决策表属性均值聚类约简算法

Continuous attributes reduction algorithm of decision table based on hard C-means clustering

针对粗糙集对于连续域属性决策表的处理能力差以及不容易获得模糊集之间关系等问题,提出一种基于连续型属性的硬C均值(HCM)聚类约简算法。该算法首先引入三角隶属度函数将连续属性值转化为模糊值,并使用HCM聚类方法获得数据集之间关系。实例验证表明:采用该算法,用户可以根据实际决策需要和领域知识更改阈值,从而获得满意的属性结果。

To solve the problems of low adaptability for continuous domain reduction and the disadvantage of failing to obtain eventual relationship among the fuzzy sets,a new attribute reduction algorithm of decision table was proposed based on Hard C-Means （HCM） clustering.First,continuous attribute values were transformed into fuzzy values with triangular membership function,and then the algorithm of HCM clustering was provided to obtain relationship among the fuzzy sets.In the end,the simulation results show the effectiveness of the proposed method.