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The aim of multidimensional scaling is to represent dissimilarities among
objects in high dimensional space as distances in low (usually 2- or 3-) dimensional
space. Usually the input to multidimensional scaling procedure is a square, symmetric
matrix indicating relationships (similarities or dissimilarities) among a set of items.
There are many techniques of classical multidimensional scaling...
Visualizing data in the form of illustrative diagrams and searching, in these diagrams, for structures, clusters, trends, dependencies etc. is one of the main aims of multivariate statistical analysis. In the case of symbolic data (e.g. data in form of: single quantitative value, categorical values, intervals, multi-valued variables, multi-valued variables with weights), some well-known methods are...
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