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[10] | 1 | %DISMATSEL Forward selection and combination of dissimilarity datasets
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| 2 | %
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| 3 | % [D,L,E] = DISMATSEL(C)
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| 4 | %
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| 5 | % C is a cell array of labeled datasets being square dissimilarity
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| 6 | % matrices. In a forward selection the best of them according to the
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| 7 | % leave-one-out nearest neighbor error (NNE) are selected and summed.
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| 8 | % L contains the ranked set of indices of selected matrices. E stores the
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| 9 | % error and D is the sum of the best subset.
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| 10 | %
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| 11 | % SEE ALSO
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| 12 | % DATASETS, NNE
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| 13 |
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| 14 | % Copyright: R.P.W. Duin, r.p.w.duin@prtools.org
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| 15 | % Faculty EWI, Delft University of Technology
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| 16 | % P.O. Box 5031, 2600 GA Delft, The Netherlands
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| 17 |
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| 18 | function [d_final,L,E] = dismatsel(c,nmax)
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| 19 |
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| 20 | if ~iscell(c) | ~isdataset(c{1})
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| 21 | error('Cell array of dissimilarity matrices expected')
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| 22 | end
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| 23 |
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| 24 | n = length(c);
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| 25 | if nargin < 2, nmax = n; end
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| 26 | for j=1:n
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| 27 | c{j} = abs(c{j});
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| 28 | c{j} = setfeatlab(c{j},getlabels(c{j}));
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| 29 | c{j} = c{j}*disnorm(c{j});
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| 30 | end
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| 31 | L = zeros(1,nmax);
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| 32 | J = [1:n];
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| 33 | E = zeros(1,nmax);
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| 34 | d = zeros(size(c{1}));
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| 35 | emin_total = 1;
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| 36 | for j=1:nmax
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| 37 | emin = 1;
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| 38 | for i=J
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| 39 | e = nne(c{i}+d);
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| 40 | if e < emin
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| 41 | L(j) = i;
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| 42 | emin = e;
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| 43 | end
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| 44 | end
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| 45 | d = c{L(j)}+d;
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| 46 | if nargin < 2 % do not allow multiple choices
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| 47 | J(J==L(j)) = [];
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| 48 | end
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| 49 | E(j) = emin;
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| 50 | if emin < emin_total
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| 51 | emin_total = emin;
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| 52 | d_final = d;
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| 53 | end
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| 54 | end
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| 55 |
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| 56 |
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| 57 |
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