Matlab_LibLinearWrapper/binary/do_binary_cross_validation.m

function f_accuracy = do_binary_cross_validation(y, x, param, nr_fold)
    len        = length(y);
    rand_ind   = randperm(len);
    dec_values = [];
    labels     = [];
    
    % Cross training : folding
    for i = 1:nr_fold 
      test_ind = rand_ind([floor((i-1)*len/nr_fold)+1:floor(i*len/nr_fold)]');
      train_ind = [1:len]';
      train_ind(test_ind) = [];
      model = train(y(train_ind),x(train_ind,:),param);
      [pred, acc, dec] = predict(y(test_ind),x(test_ind,:),model,'-q');
      
      if model.Label(1) < 0;
        dec = dec * -1;
      end
      
      dec_values = vertcat(dec_values, dec);
      labels     = vertcat(labels, y(test_ind));
    end
    
    % final evaluation
    f_accuracy = validation_function(dec_values, labels);
    disp(sprintf('Cross Validation: %f', f_accuracy));

end