It provides deep learning tools of deep belief networks (DBNs).
CalcErrorRate( dbn, IN, OUT )
% CalcErrorRate: calculate error rate
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% ErrorRate = CalcErrorRate( dbn, IN, OUT )
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%Output parameters:
% ErrorRate: error rate
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%Input parameters:
% dbn: network
% IN: input data, where # of row is # of data and # of col is # of input features
% OUT: output data, where # of row is # of data and # of col is # of output labels
%
%
%Version: 20131213
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% Deep Neural Network: %
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% Copyright (C) 2013 Masayuki Tanaka. All rights reserved. %
% mtanaka@ctrl.titech.ac.jp %
% %
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function ErrorRate = CalcErrorRate( dbn, IN, OUT )
out = v2h( dbn, IN );
[m ind] = max(out,[],2);
out = zeros(size(out));
for i=1:size(out,1)
out(i,ind(i))=1;
end
ErrorRate = abs(OUT-out);
ErrorRate = mean(sum(ErrorRate,2)/2);
end