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A new algorithm for non-linear mapping with applications to dimension and cluster analyses
Authors:Osamu Kakusho  Riichiro Mizoguchi
Affiliation:The Institute of Scientific and Industrial Research, Osaka University, Suita, Osaka, 565 Japan
Abstract: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.
Keywords:Cluster analysis  Multi-dimensional scaling  Minimum dimension  Non-linear mapping
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