Two neural network methods for multidimensional scaling
نویسندگان
چکیده
Multidimensional scaling (MDS) embeds points in a Euclidean space given only dissimilarity data. Only very recently MDS has gotten some attention from neural network researchers. We propose two neural network methods for MDS and evaluate them using both artiicially generated and real data. Training uses two inputs at a time.
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