main_QAvsHW.m

clear;

dataset = {'SBU_3DFE','SJAFFE','Yeast_spo5','Yeast_spo','Yeast_heat','Yeast_elu','Yeast_dtt','Yeast_diau','Yeast_cold','Yeast_cdc','Yeast_alpha','Flickr','Twitter','Human_Gene','Natural_Scene'};

for i = 1:length(dataset)
    para{i}.lambda1 = 1e-3;
    para{i}.lambda2 = 0;
    para{i}.method = 0;
    MaxIter{i} = 400;
    Ratio{i} = 0.8;
    LowerBound{i} = 1;
end

para{1}.lambda1 = 1e-4;
para{1}.lambda2 = 0;
MaxIter{1} = 500;
para{2}.lambda1 = 4e-3;
para{2}.lambda2 = 2e-5;
MaxIter{2} = 250;
MaxIter{13}=200;
MaxIter{14}=200;

para_no_qa = para;
for i = 1:length(dataset)
    para_no_qa{i}.method = 1;
end

nFold = 10;
indicatorName = {'Acc','KlDistance','EuclideanDistance','MSE','Chebyshev','Clark','Canberra','Cosine','Intersection','sortLoss','kurtosisKl','laLoss','SignedKurtosisOffset','AbsKurtosisOffset'};
algorithmName = {'bfgs','kqa','kqaQa','kqaHw'};

for datasetNum = 1:length(dataset)
    
    datasetName = dataset{datasetNum};
    load( datasetName+".mat");
    [trainFeatures,trainLabels,testFeatures,testLabels] = crossValidation(features,labels,nFold,false,true);

    algorithmName2 = cell(length(algorithmName),1);
    algorithmName3 = cell(2*length(algorithmName),1);
    for i = 1:length(algorithmName)
        algorithmName2{i} = strcat(upper(algorithmName{i}(1)),algorithmName{i}(2:end)); %#ok<*SAGROW>
        algorithmName3{2*i-1} = strcat(algorithmName{i},'Train');
        algorithmName3{2*i} = strcat(algorithmName{i},'Test');
    end
    for i = 1:length(algorithmName)
            eval([algorithmName{i},'Test = table;']);
            eval([algorithmName{i},'Train = table;']);
    end

    parfor i = 1:nFold
        [bfgsResultTest,bfgsResultTrain] = ldlBfgs(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},MaxIter{datasetNum}); %#ok<*PFBNS>
        [kqaResultTest,kqaResultTrain] = ldlKqa(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},para_no_qa{datasetNum},MaxIter{datasetNum},false,false); 
        [kqaQaResultTest,kqaQaResultTrain] = ldlKqa(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},para{datasetNum},MaxIter{datasetNum},false,false); 
        [kqaHwResultTest,kqaHwResultTrain] = ldlKqa(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},para{datasetNum},MaxIter{datasetNum},false,false,true); 
%         [pskKqaResultTest,pskKqaResultTrain] = ldlKqa(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},para{datasetNum},MaxIter{datasetNum},true,false); 
%         [pskResultTest,pskResultTrain] = ldlPsk(trainFeatures{i},trainLabels{i},testFeatures{i},testLabels{i},false,Ratio{datasetNum},LowerBound{datasetNum},MaxIter{datasetNum});

        bfgsTest = [bfgsTest;bfgsResultTest]; %#ok<*AGROW>
        bfgsTrain = [bfgsTrain;bfgsResultTrain];
        kqaQaTest = [kqaQaTest;kqaQaResultTest];
        kqaQaTrain = [kqaQaTrain;kqaQaResultTrain];
%         pskTest = [pskTest;pskResultTest];
%         pskTrain = [pskTrain;pskResultTrain];
        kqaTest = [kqaTest;kqaResultTest];
        kqaTrain = [kqaTrain;kqaResultTrain];
        kqaHwTest = [kqaHwTest;kqaHwResultTest];
        kqaHwTrain = [kqaHwTrain;kqaHwResultTrain];
    end
    
    meanTest=[];
    meanTrain=[];
    meanAll=[];
    stdTest=[];
    stdTrain=[];
    stdAll=[];
    for i = 1:length(algorithmName)
        eval(['mean',algorithmName2{i},'Test = mean(',algorithmName{i},'Test{:,:},1);']);
        eval(['mean',algorithmName2{i},'Train = mean(',algorithmName{i},'Train{:,:},1);']);
        eval(['std',algorithmName2{i},'Test = std(',algorithmName{i},'Test{:,:},1);']);
        eval(['std',algorithmName2{i},'Train = std(',algorithmName{i},'Train{:,:},1);']);
        eval(['meanTest =[meanTest;mean',algorithmName2{i},'Test];']);
        eval(['meanTrain = [meanTrain;mean',algorithmName2{i},'Train];']);
        eval(['meanAll = [meanAll;mean',algorithmName2{i},'Train;mean',algorithmName2{i},'Test];']);
        eval(['stdTest =[stdTest;std',algorithmName2{i},'Test];']);
        eval(['stdTrain = [stdTrain;std',algorithmName2{i},'Train];']);
        eval(['stdAll = [stdAll;std',algorithmName2{i},'Train;std',algorithmName2{i},'Test];']);        
    end

    compareMeanTest = array2table(meanTest,'RowNames',algorithmName,'VariableNames',indicatorName);
    compareStdTest = array2table(stdTest,'RowNames',algorithmName,'VariableNames',indicatorName);
    compareMeanTrain = array2table(meanTrain,'RowNames',algorithmName,'VariableNames',indicatorName);
    compareStdTrain = array2table(stdTrain,'RowNames',algorithmName,'VariableNames',indicatorName);
    compareMeanAll = array2table(meanAll,'RowNames',algorithmName3,'VariableNames',indicatorName);
    compareStdAll = array2table(stdAll,'RowNames',algorithmName3,'VariableNames',indicatorName);

    % compareMeanTest = array2table([meanBfgsTest;meanKqaTest],'RowNames',{'bfgs','kqa'},'VariableNames',{'meanKlDistance','meanEuclideanDistance','meanMSE','bfgsMeanKurtosisDif','meanChebyshev','meanClark','meanCanberra','meanCosine','meanIntersection','meanNDCG','meanSortLoss','meanKurtosisKL'});
    % compareStdTest = array2table([stdBfgsTest;stdKqaTest],'RowNames',{'bfgs','kqa'},'VariableNames',{'stdKlDistance','stdEuclideanDistance','stdMSE','stdKurtosisDif','stdChebyshev','stdClark','stdCanberra','stdCosine','stdIntersection','stdNDCG','stdSortLoss','stdKurtosisKL'});
    % compareMeanAll = array2table([meanBfgsTrain;meanBfgsTest;meanKqaTrain;meanKqaTest],'RowNames',{'bfgsTrain','bfgsTest','kqaTrain','kqaTest'},'VariableNames',{'meanKlDistance','meanEuclideanDistance','meanMSE','meanKurtosisDif','meanChebyshev','meanClark','meanCanberra','meanCosine','meanIntersection','meanNDCG','meanSortLoss','meanKurtosisKL'});
    % compareStdAll = array2table([stdBfgsTrain;stdBfgsTest;stdKqaTrain;stdKqaTest],'RowNames',{'bfgsTrain','bfgsTest','kqaTrain','kqaTest'},'VariableNames',{'stdKlDistance','stdEuclideanDistance','stdMSE','stdKurtosisDif','stdChebyshev','stdClark','stdCanberra','stdCosine','stdIntersection','stdNDCG','stdSortLoss','stdKurtosisKL'});

    % ±£´æ½á¹û
    cd('DataResult_QAvsHW');
    eval(['save ',datasetName,'_2_24_1.mat datasetName compareMeanAll compareMeanTest compareMeanTrain compareStdAll compareStdTest compareStdTrain']);
    cd('..');

    clear stdKnnTest stdKnnTrain stdBf
    gsTest stdBfgsTrain stdLcTest stdLcTrain stdAdaboostBfgsTest stdAdaboostLcTest  S'%'1;
end