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crossValidation.m
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crossValidation.m
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function crossValidation(Y,Sd,St,classifier,cv_setting,m,n,use_WKNKN,K,eta,use_W_matrix)
% prediction method
pred_fn = str2func(['alg_' classifier]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% cross validation setting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% parameters
fprintf('m = %i\n',m); % #repetitions
fprintf('n = %i\n',n); % #folds
% seeds
rng('shuffle');
seeds = randi(10000,1,m);
% print seeds to be used...
fprintf('seeds = [ ');
for s=1:length(seeds)
fprintf('%i ',seeds(s));
end
fprintf(' ]\n\n');
disp('==========================');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% cross validation (m repetitions of n-fold experiments)
AUCs = zeros(1,m);
AUPRs = zeros(1,m);
for i=1:m
seed = seeds(i);
[AUCs(i), AUPRs(i)] = nfold(Y,Sd,St,pred_fn,n,seed,cv_setting,use_WKNKN,K,eta,use_W_matrix);
diary off; diary on;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% display evaluation results
fprintf('\n FINAL AVERAGED RESULTS\n\n');
fprintf(' AUC (std): %g\t(%g)\n', mean(AUCs), std(AUCs));
fprintf(' AUPR (std): %g\t(%g)\n', mean(AUPRs), std(AUPRs));
diary off; diary on;
end