A Multidimensional Scaling (MDS) method for interval-valued dissimilarity data. The objects are represented as hyperspheres in a p-dimensional space. The minimum and maximum distances between hyperspheres approximate the lower and upper dissimilarities in the least squares sense. The method is described in:

T. Denoeux and M.-H. Masson. Multidimensional scaling of interval-valued dissimilarity data. Pattern Recognition Letters, 21:83-92, 2000. pdf

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