摘要： 增量式属性约简算法是动态数据挖掘技术的重要研究内容。为降低区分矩阵的存储空间,结合二进制区分矩阵便于计算以及形象直观的优点,给出一种压缩二进制区分矩阵的方法。将二进制区分矩阵的存储空间从|C|+1列简化成3列。通过动态更新二进制区分矩阵实现增量式求核,并以核为出发点,提出一种的增量式属性约简算法。通过实例计算及仿真实验验证了该算法的有效性。

关键词: 粗糙集, 增量式属性约简, 二进制区分矩阵, 核属性, 属性频率

Abstract: Incremental attribute reduction algorithm is one of the important research contents in the area of dyanmic data mining.To reduce the storage space of binary discernibility matrix,and by combining the advantages of the binary discernibility matrix that it facilitates the calculation and is visual,this paper proposes a method to compress binary matrix.It simplifies the binary discernibility matrix storage space from |C|+1 column to three columns.Through dynamically updating the binary discernibility matrix to incrementally get core.According to the core,the paper proposes an incremental attribute reduction algorithm based on binary discernibility matrix.Example calculation and experimental simulation prove the effectiveness of the algorithm.

Key words: rough sets, incremental attribute reduction, binary discernibility matrix, core attribute, attribute frequency

中图分类号: 

• TP391