Mauch MIREX 2010

function CPD = maximize_params(CPD, temp)

% MAXIMIZE_PARAMS Find ML params of an MLP using Scaled Conjugated Gradient (SCG)

% CPD = maximize_params(CPD, temperature)

% temperature parameter is ignored

if ~adjustable_CPD(CPD), return; end

options = foptions;

% options(1) >= 0 means print an annoying message when the max. num. iter. is reached

if CPD.verbose

  options(1) = 1;

else

  options(1) = -1;

end

%options(1) = CPD.verbose;

options(2) = CPD.wthresh;

options(3) = CPD.llthresh;

options(14) = CPD.max_iter;

dpsz=length(CPD.mlp);

for i=1:dpsz

    mask=[];

    mask=find(CPD.eso_weights(:,:,i)>0);    % for adapting the parameters we use only positive weighted example

    if  ~isempty(mask),

        CPD.mlp{i} = netopt_weighted(CPD.mlp{i}, options, CPD.parent_vals(mask',:), CPD.self_vals(mask',:,i), CPD.eso_weights(mask',:,i), 'scg');

        CPD.W1(:,:,i)=CPD.mlp{i}.w1;        % update the parameters matrix

        CPD.b1(i,:)=CPD.mlp{i}.b1;          %

        CPD.W2(:,:,i)=CPD.mlp{i}.w2;        % update the parameters matrix

        CPD.b2(i,:)=CPD.mlp{i}.b2;          %

    end

end