文献类型：会议论文

英文题名：Selection of the suitable neighborhood size for the ISOMAP algorithm

作者：Shao, Chao[1];Huang, Houkuan[2];Wan, Chunhong[1]

第一作者：邵超

通讯作者：Shao, C[1]

机构：[1]Henan Univ Finance & Econ, Dept Comp Sci, Zhengzhou 450002, Henan, Peoples R China;[2]Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, 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, Dept Comp Sci, Zhengzhou 450002, Henan, 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：International Joint Conference on Neural Networks

会议日期：AUG 12-17, 2007

会议地点：Orlando, FL

语种：英文

外文关键词：Geodesy

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 is unsuitable, shortcut edges can emerge in the neighborhood graph and shorten the involved shortest path lengths greatly, which makes them not approximate the corresponding geodesic distances anymore, that is, there doesn't exist such an approximately monotonically increasing relationship between them anymore. Based on this observation, in the paper, we use costs over the minimal connected neighborhood graph to approximate the corresponding geodesic distances, and then present an efficient method to judge whether a neighborhood size is suitable beforehand, by which a suitable neighborhood size can be selected more efficiently than the straightforward method with the residual variance. Besides, the correctness of the intrinsic dimensionality, estimated by ISOMAP, of the data can also be judged more easily by our method.