Timeline for Convert a confusion matrix to a distance/covariance matrix
Current License: CC BY-SA 2.5
4 events
| when toggle format | what | by | license | comment | |
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| Sep 18, 2013 at 4:53 | comment | added | Math101 | related :stats.stackexchange.com/questions/70332/… | |
| Feb 10, 2010 at 11:19 | comment | added | Magnus Lie Hetland | A small update: My answer mainly addresses how to transform a general dissimilarity function into a metric. The original question was more related to an even more basic step: Turning a similarity function into a dissimilarity function. One way, as used in the thesis above, is $d(u,v) = s(u,u) + s(v,v) - 2s(u,v)$, for example. Or, assuming that similarity decays exponentially with distance (common assumption in psychology), you'd have the relationship $s(u,v) = e^{-c\cdot d(u,v)}$, for some constant $c$. This can, of course, be combined with the symmetry fixing mentioned earlier. | |
| Feb 4, 2010 at 13:41 | comment | added | Magnus Lie Hetland | I was only allowed one link in the post, but here's the URL for the thesis I mentioned (it turned out to be a bit hard to find): daim.idi.ntnu.no/masteroppgaver/IME/IDI/2005/1050/… | |
| Feb 4, 2010 at 10:39 | history | answered | Magnus Lie Hetland | CC BY-SA 2.5 |