A new algorithm for non-linear mapping with applications to dimension and cluster analyses

摘要

In this paper, a new non-linear mapping method suitable for dimension and cluster analysis is proposed. In order to obtain a flexible and powerful method, the non-metric multidimensional scaling of Kruskal type is extended by introducing the concept of k-nearest neighbor. Some simulation results supporting the efficiency of our new method are given along with a detailed discussion.