摘要
根据向量矩阵与向量之间的映射关系,研究了基于二元向量矩阵算法的粗糙近似、属性约简以及最优属性约简集的获取。提出基于二元向量矩阵的属性相对约简、最优属性集获取算法,解决原有矩阵算法属性核不一致性和属性约简集选择的盲目性。并提出了二元向量压缩矩阵算法,降低了原有矩阵算法的复杂度。通过实例分析,证明所提出的相关算法的有效性,为研究粗糙集数据挖掘提供了一种可行有效的计算方法。
From the mapping relationship between information vector matrix and relative vectors, rough approximation, attribute relative reductions and selecting optimal attribute reductions set algorithms based on binary vector matrix were proposed. Inconsistency of acquiring attribute kernel and blindness of selecting attribute reductions are overcome. On the foundation of studying binary vector matrix algorithms, binary vector compression matrix algorithm was also put forward, and the algorithm complexity was decreased faster than the original matrix algorithm. By the example analysis, the validity of the proposed algorithms was verified, the feasible computing way is presented for studying rough set further.
出处
《石油化工高等学校学报》
EI
CAS
2007年第3期1-4,共4页
Journal of Petrochemical Universities
基金
北京化工大学青年基金(No.QN0626)
北京教育委员会项目(No.XK100100435)
关键词
粗糙集
二元向量矩阵
属性约简
信息压缩
Rough set
Binary vector matrix
Attribute reductions
Information compression
