Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices

作者：Ma Zhiliang; Cardinal Stakenas Adam; Park Youngser; Trosset Michael W; Priebe Carey E^*

来源：Journal of Classification, 2010, 27(3): 307-321.

DOI：10.1007/s00357-010-9059-3

• Dissimilarity representation
• Multidimensional scaling
• Dimensionality reduction
• Principal components analysis
• Linear discriminant analysis

We consider the problem of combining multiple dissimilarity representations via the Cartesian product of their embeddings. For concreteness, we choose the inferential task at hand to be classification. The high dimensionality of this Cartesian product space implies the necessity of dimensionality reduction before training a classifier. We propose a supervised dimensionality reduction method, which utilizes the class label information, to help achieve a favorable combination. The simulation and real data results show that our approach can improve classification accuracy compared to the alternatives of principal components analysis and no dimensionality reduction at all.

• 出版日期2010-11