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  • $\begingroup$ so that I can apply it to new data points? How do you see it? MDS input is one or several matrices of a dissimilarity within a fixed set of objects. $\endgroup$ Commented Feb 28, 2013 at 5:03
  • $\begingroup$ So I am unable to obtain a projection since the point location information is lost by the distance (dissimilarity) matrix? What about comparing the projections of multiple dimensionality reduction techniques? Can I evaluate their relative effectiveness by comparing the size of the differences in distance between neighbouring points with respect to both spaces? Does this make sense, or is there a better way of doing or looking at this? $\endgroup$ Commented Feb 28, 2013 at 7:04
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    $\begingroup$ It's not because something is "lost" but because MDS is not a "forcasting" method to be able to find coordinates for new points on an old map. Consider using PCA or Correspondense analysis which can do it. $\endgroup$ Commented Feb 28, 2013 at 13:08