pred_cpann.m

来自「this file is leverage algorithm written 」· M 代码 · 共 48 行

function pred = pred_cpann(X,model)

% prediction of unknown samples with counterpropagation artificial neural networks (CPANNs)
% pred_cpann predicts classes of unknown samples by using a previuos model
% built by means of CPANNs (model_cpann)
% 
% pred = pred_cpann(X,model);
%
% input:
%   X           data [n x p], n samples, p variables
%   model       model structure built with model_cpann
% 
% output:
%   pred is a structure, with the following fields
%   pred.class              predicted class [n x 1]
%   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 = cpann_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));
    class_pred(i) = model.net.neuron_ass(pos(i,1),pos(i,2));
end

% saves results
pred.type = 'cpann';
pred.class = class_pred;
pred.top_map = pos;