switch algo.optimizer
    case 'R'
        preds=fevalR('RFtest', 'forest', forest, 'xtest', X_te);　　　　
        % warning, may have inverted the 2 classes.
        % case of 2 classes only %% 这里只处理了两类分类
        %% preds.resu 是一个numIns * numClass的矩阵，对应分类为不同类别的概率，根据这个矩阵可以求解多类的Y_resu
        outval=preds.resu(:,2)-preds.resu(:,1);
        Y_conf=abs(outval);
        Y_resu=sign(outval);
        zero_val=find(Y_resu==0); % remove ties
        Y_resu(zero_val)=algo.algorithm.default_output;
        
    case 'Weka'
        % ...
            case 'Merk'
        param = forest.param;
        warning off
        out = RFClass(param, X_te, Y_te, forest);
        warning on

        Y_resu=targets(out.ypredts);
        zero_val=find(Y_resu==0); % remove ties
        Y_resu(zero_val)=algo.algorithm.default_output;

        Y_conf=abs(log(out.countts(:,2)+1)-log(out.countts(:,1)+1));
        zero_val=find(Y_conf==0); % remove ties
        Y_conf(zero_val)=eps;

        %Y_resu=out.countts(:,2)-out.countts(:,1);
        % we use the counts as class likelihoods
        % the discriminant value is log(p1/p2)
end

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