📄 pred_kohonen.m
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function pred = pred_kohonen(X,model)
% prediction of unknown samples with Kohonen maps
% pred_kohonen projects new samples by using a previuos model
% built by means of Kohonen maps (model_kohonen)
%
% pred = pred_kohonen(X,model);
%
% input:
% X data [n x p], n samples, p variables
% model model structure built with model_kohonen
%
% output:
% pred is a structure, with the following fields
% pred.top_map sample position in the kohonen map [n x 2]
%
% see the HTML HELP files (help.htm) for details and examples
%
% version 1.0 - may 2007
% Davide Ballabio
% Milano Chemometrics and QSAR Research Group
% www.disat.unimib.it/chm
% checks
errortype = kohonen_check(X,[],model,'pred');
if ~strcmp(errortype,'none')
disp(errortype)
return
end
% data scaling
[Xsca,scal] = som_scaling(X,[],model);
% projects the samples on the topmap and assigns samples to classes
nsize = size(model.net.W,1);
W_reshape = reshape(permute(model.net.W,[2 1 3]),[nsize*nsize size(X,2)]);
for i = 1:size(X,1)
x_in = Xsca(i,:);
winner = som_winner(x_in,W_reshape);
[pos(i,1),pos(i,2)] = som_which_neuron(winner,size(W_reshape,1));
end
% saves results
pred.type = 'kohonen';
pred.top_map = pos;
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