A Novel Algorithm for Filling Incomplete Data Based on Attribute Reduction

摘要：

　　Traditional data filling algorithms take the unified method to fill the incomplete data,leading to the low efficiency for filling a large number of incomplete data.This paper proposes a novel algorithm for filling incomplete data based on attribute reduction.The presented algorithm first uses the attribute reduction to distinguish the important attribute from unimportant attribute,and then fills the two kinds of data attributes using different filling technologies.Experiments show that this algorithm can effectively and quickly fill the large-scale incomplete data.

关键词： attribute reduction incomplete data data filling

作者: Yang Yang Shan Xiong Chen Feng Liu Xiao Wen

作者单位: School of Computer & Information Science,Southwest University Chongqing,China;Chongqing Engineering School of Computer & Information Science,Southwest University Chongqing,China Chongqing Engineering Research Center for Instrument and Control Equipment Chongqing,China School of Software Technology,Dalian University of Technology Dalian,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 497-499

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）