Abstract: Attribute reduction is an important concept in rough set data analysis. An algorithm for dissimilar reductions finding was presented. Method of bottomup agglomerative hierarchical clustering was used to get k partitions of conditional attributes set, and then these k attribute sets were dealt with by postprocessing and get k dissimilar attribute reductions. Result of experiments show that our method is effective.

Key words: attribute reduction, dissimilar, hierarchical clustering

摘要： 属性约简是粗糙集用于数据分析的一个重要概念，提出了一个计算差异化属性约简的算法。利用自底向上的聚合层次聚类方法对决策表的条件属性集进行聚类,得到条件属性集的k个划分，然后对这k个属性子集进行后处理操作而得到k个有较大差异的约简属性集。实验结果表明了算法的有效性。

关键词: 属性约简, 差异, 层次聚类