摘要
δ-邻域计算是邻域粗糙集模型中操作最为频繁和复杂的步骤。针对当前邻域算法的研究现状,根据样本空间的分布,提出了块集的概念,证明了每个样本的邻域只存在于其相邻的块集中。在此基础上,提出了基于块集的邻域粗糙集快速约简算法,降低了计算邻域的时间复杂性,并利用多个UCI标准数据集对该算法进行了验证。结果表明,该算法是有效的、可行的。
Calculating each record＇sδ-neighborhood elements is the most frequent and complex step in neighborhood rough set model.In this paper,we proposed the concept of the block sets according to the distribution of records in the space,then proved that each record＇sδ-neighborhood elements can only be contained in its own block set and its adjacent block sets.Based on the block-set-neighborhood theory,we presented a quick attribute reduct algorithm on neighborhood rough set,which can reduce the complexity of calculating each record＇sδ-neighborhood elements.Moreover,the algorithm＇s validity was verified by several data sets from UCI.Expermental results show that our algorithm is effective and feasible.
出处
《计算机科学》
CSCD
北大核心
2014年第B11期337-339,363,共4页
Computer Science
关键词
粗糙集
邻域
属性约简
块集
快速算法
Rough set
Neighborhood
Attribute reduct
Block set
Efficient algorithm
