基于粗糙集理论的属性约简算法研究

The Study on Attribute Reduction Algorithm Based on the Rough Set Theory

数据挖掘是近年来数据库领域中出现的一个新兴研究热点,它是从大量数据中获取知识。进行数据挖掘的方法很多,粗糙集方法便是其中的主要方法之一。属性约简算法是基于粗糙集理论的数据挖掘模型中的关键步骤,同时也是粗糙集理论研究中的一个研究重点。通过对粗糙集理论的属性约简算法的深入研究,本文提出了一种改进的属性约简启发式算法。该算法建立在可辨识矩阵计算基础上。改进算法基于Hu的算法与Jelonek算法,在计算可辨识矩阵的基础上,保证最终能够找到决策信息系统的一个约简,同时较Jelonek算法相比,运算时间明显减少。

Data mining(DM)is a new hot research pointin database area.Data mining gets knowledge from large quantity of data.There are some methods for data mining, and Rough Sets methodology is one of important methods.Attribute reduction algorithm is the key for the model and the focus of the Rough Sets. On the basis of the research on Rough Sets theory and known reduction algorithms, an improved attribute reduction algorithm is presented in this paper. This heuristic, improved attribute reduction algorithm, based on the Hu's algorithm and Jelonek's algorithm, can guarantee a reduction compared with the Hu's algorithm, and on the other hand has better effi ciency as far as time is concerned compared with the Jelonek's algorithm.