Abstract Nonmetric pairwise data with violations of symmetry, reflexivity, or triangle inequality appear in fields such as image matching, web mining, or cognitive psychology. When data are inherently nonmetric, we should not enforce metricity as real information could be lost. The multidimensional scaling problem is addressed from a new perspective. I propose a method based on the h-plot, which naturally handles asymmetric proximity data. Pairwise proximities between the objects are defined, t.
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