%0 Journal Article
%T Robust ISOMAP insensitive to singular value<br>一种对奇异值不敏感的ISOMAP
%A WEI Lai
%A WANG Shou-jue
%A XU Fei-fei
%A <br>魏莱
%A 王守觉
%A 徐菲菲
%J 计算机应用
%D 2007
%I 
%X ISOAMP is a classical nonlinear dimensionality reduction algorithm. It is effective to discover the low-dimensional manifold in a high-dimensional data space. But the algorithm is very sensitive to the noises and singular value. Principal Component Analysis with robustness (Robust PCA) was used to detect singular points, and the singularity was also appropriately treated to reduce the ISOMAP's sensitivity to it. The proposed algorithm is intuitive and easy to understand, the results of the experiment prove that it is robust, and can maintain the overall structure of data with more singular points.
%K 流形学习
%K 主成分分析
%K 等度规映射
%K 奇异值
%K 敏感
%K ISOMAP
%K singular
%K value
%K 整体结构
%K 数据集
%K 情况
%K 结果
%K 实验
%K 易于理解
%K 程度
%K 处理
%K 奇异点
%K 探测
%K Robust
%K 主成分分析
%K 鲁棒性
%K 利用
%K 噪声
%K 算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512792EAEF023330473&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=AC45B356D9DF3BDB&eid=DDA12465F03AF56A&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=8