文献类型：会议论文

英文题名：Incremental selection of the neighborhood size for ISOMAP

作者：Shao, Chao[1]

第一作者：邵超

通讯作者：Shao, C[1]

机构：[1]Henan Univ Finance & Econ, Sch Informat, Zhengzhou 450002, Peoples R China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]corresponding author), Henan Univ Finance & Econ, Sch Informat, Zhengzhou 450002, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

会议论文集：7th International Conference on Machine Learning and Cybernetics

会议日期：JUL 12-15, 2008

会议地点：Kunming, PEOPLES R CHINA

语种：英文

外文关键词：data visualization; ISOMAP; neighborhood size; residual variance; order

摘要：The success of ISOMAP depends greatly on selecting a suitable neighborhood size; however, it's an open problem how to do this efficiently. When the neighborhood size becomes unsuitable, shortcut edges can be introduced into the neighborhood graph and destroy the approximation ability of the involved shortest-path distances to the corresponding geodesic distances greatly. It's obvious that shortcut edge links two endpoints lying close in Euclidean space but far away on the manifold, which can be measured approximately by its order presented in this paper. Based on the observation, this paper presented an efficient method to rind a suitable neighborhood size incrementally, which doesn't need to compute shortest-path distances or run the MDS algorithm as those methods based on residual variance do. Finally, the feasibility of this method can be verified by experimental results.