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Least squares multidimensional scaling (MDS) is a classical method for representing a n×n dissimilarity matrix D. One seeks a set of configuration points z1,…,zn∈RS such that D is well approximated by the Euclidean distances between the configuration points: Dij≈‖zi−zj‖2. Suppose that in addition to D, a vector of associated binary class labels y∈{1,2}n corresponding to the n observations is available...
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