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Nonmetric, multidimensional scaling

In order to provide an easy way to visualize how the methods differ from each other the accuracy values (Q3, Ca, Cp and Cc) for each method where subjected to nonmetric multidimensional scaling analysis (Cox and Cox, 1994). The resulting graphs provide a representation in a two-dimensional space of the methods and those are shown in figure 3. As can be observed, the interrelationship between the methods... [Pg.791]

NONMETRIC MULTIDIMENSIONAL SCALING AS A DATA-MINING TOOL NEW ALGORITHM AND NEW TARGETS... [Pg.315]

In this chapter, we would like to demonstrate that one of the very old MVA tools, nonmetric multidimensional scaling (nMDS) [3], can work well as an unsupervised truly data-driven method for data reduction. We first explain an efficient maximally nonmetric algorithm [4] and then demonstrate its superiority to linear MVA methods. We also demonstrate that the subsequent application of linear MVA after data reduction by nMDS can often be a powerful data mining technique. [Pg.317]

The main purpose of this chapter is to advertise an efficient nonmetric multidimensional scaling scheme with possible new applications. In particular,... [Pg.349]


See other pages where Nonmetric, multidimensional scaling is mentioned: [Pg.35]    [Pg.202]   
See also in sourсe #XX -- [ Pg.325 ]




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Data mining, nonmetric multidimensional scaling

Nonmetric, multidimensional scaling NMDS)

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