Timeline for Finding the projection used in multidimensional scaling
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Jun 1, 2014 at 19:09 | answer | added | EngrStudent | timeline score: 1 | |
| Feb 28, 2013 at 13:08 | comment | added | ttnphns | 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. | |
| Feb 28, 2013 at 7:04 | comment | added | Josh | 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? | |
| Feb 28, 2013 at 5:03 | comment | added | ttnphns | 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. | |
| Feb 28, 2013 at 2:50 | history | asked | Josh | CC BY-SA 3.0 |