%0 Journal Article
%T Research of Detection of Outliers Based on Locally Linear Weighted Value<br>基于局部线性加权的离群点检测方法
%A XU Xue-song SONG Dong-ming ZHANG Xu ZHANG Hong LIU Feng-yu
%A <br>徐雪松
%A 宋东明
%A 张谞
%A 张宏
%A 刘凤玉
%J 计算机科学
%D 2008
%I 
%X The data dimension reduction is the main method that can enhance the outliers mining efficiency based on higher-dimension data set.The research of detection of outliers based on locally linear weighted value is proposed after analyzing the advantages and disadvantages of the classical outlier mining algorithm in the paper.With the idea of Lo- cal Linear Embedding,the algorithm tries to find distribution of internal embedding of the samples,and determines value-weighted by combining distance formula with dis...
%K Loeally linear embedding
%K High dimensional data
%K Nonlinear dimensionality reduction
%K Outliers<br>局部线性嵌入
%K 高维数据
%K 非线性降维
%K 离群数据
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=8B4C5400AA69D12F44C40C713D9874FB&yid=67289AFF6305E306&vid=6209D9E8050195F5&iid=94C357A881DFC066&sid=E2546871E5B846EF&eid=0B4F496D54044D86&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=10