Last change
on this file since 52 was
18,
checked in by bduin, 14 years ago
|
clevald, parzenddc, parzend_map and kem added
|
File size:
978 bytes
|
Rev | Line | |
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[18] | 1 | %PARZEN_MAP Map a dissimilarity dataset on a Parzen densities based classifier |
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| 2 | % |
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| 3 | % F = PARZEN_MAP(D,W) |
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| 4 | % |
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| 5 | % INPUT |
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| 6 | % D Dissimilarity dataset |
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| 7 | % W Trained Parzen dissimilarity classifier mapping |
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| 8 | % |
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| 9 | % OUTPUT |
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| 10 | % F Mapped dataset |
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| 11 | % |
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| 12 | % DESCRIPTION |
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| 13 | % |
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| 14 | % SEE ALSO |
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| 15 | % MAPPINGS, DATASETS, PARZENDDC |
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| 16 | |
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| 17 | % Copyright: R.P.W. Duin, r.p.w.duin@prtools.org |
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| 18 | % Faculty EWI, Delft University of Technology |
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| 19 | % P.O. Box 5031, 2600 GA Delft, The Netherlands |
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| 20 | |
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| 21 | function f = parzend_map(d,w) |
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| 22 | prtrace(mfilename); |
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| 23 | |
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| 24 | % If no mapping is supplied, train one. |
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| 25 | if (nargin < 2) |
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| 26 | w = parzenddc(d); |
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| 27 | end |
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| 28 | |
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| 29 | pars = getdata(w); |
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| 30 | I = getdata(w,'objects'); |
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| 31 | p = getdata(w,'prior'); |
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| 32 | nlab = getdata(w,'nlab'); |
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| 33 | h = getdata(w,'smoothpar'); |
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| 34 | q = getdata(w,'weights'); |
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| 35 | [k,c] = getsize(w); |
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| 36 | [m,k] = size(d); |
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| 37 | e = +d(:,I); |
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| 38 | |
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| 39 | f = zeros(m,c); |
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| 40 | for j=1:c |
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| 41 | J = find(nlab==j); |
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| 42 | f(:,j) = p(j)*mean(repmat(q(J)',m,1).*exp(-(e(:,J).^2)./repmat((2.*h(J).*h(J))',m,1)),2); |
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| 43 | end |
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| 44 | |
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| 45 | f = setdata(d,f,getlabels(w)); |
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| 46 | |
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| 47 | return |
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