Last change
on this file since 160 was
20,
checked in by bduin, 13 years ago
|
updates for handling soft labels
|
File size:
901 bytes
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Rev | Line | |
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[10] | 1 | %NNE Leave-one-out Nearest Neighbor Error on a Dissimilarity Matrix |
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| 2 | % |
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| 3 | % [E,LAB] = NNE(D) |
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| 4 | % |
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| 5 | % INPUT |
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| 6 | % D NxN symmetric dissimilarity dataset |
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| 7 | % |
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| 8 | % OUTPUT |
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| 9 | % E Leave-one-out error |
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| 10 | % LAB Nearest neighbor labels |
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| 11 | % |
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| 12 | % DESCRIPTION |
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| 13 | % Estimates the leave-one-out error of the 1-nearest neighbor rule |
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| 14 | % on the givven symmetric dissimilairy data. |
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| 15 | % |
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| 16 | |
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| 17 | % Copyright: Robert P.W. Duin, r.p.w.duin@prtools.org and |
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| 18 | % Elzbieta Pekalska, ela.pekalska@googlemail.com |
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| 19 | % Faculty EWI, Delft University of Technology and |
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| 20 | % School of Computer Science, University of Manchester |
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| 21 | |
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| 22 | |
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| 23 | function [e,NNlab] = nne(D) |
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| 24 | |
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| 25 | [m,n] = size(D); |
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| 26 | if m ~= n, |
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| 27 | error('Distance matrix should be square.'); |
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| 28 | end |
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| 29 | |
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| 30 | lab = getlab(D); |
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| 31 | [nlab,lablist] = renumlab(lab); |
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| 32 | D(1:m+1:end) = inf; |
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| 33 | [d,M] = min(D'); |
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| 34 | e = mean(nlab(M) ~= nlab); |
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[20] | 35 | if islabtype(D,'crisp') |
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| 36 | NNlab = lablist(nlab(M),:); |
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| 37 | else |
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| 38 | labs = gettargets(D); |
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| 39 | NNlab = labs(M,:); |
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| 40 | end |
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[10] | 41 | return; |
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