OneNNClassifierMinkowski.m

function acc = OneNNClassifierMinkowski(DS,param1, NormalizationIndex)
    
    acc = 0;
    
    for id = 1 : DS.TestInstancesCount
        disp(id);
        classify_this = DS.Test(id,:);
        
            if NormalizationIndex==2
                classify_this = MinMaxNorm(classify_this,0.001,1);
            elseif NormalizationIndex==3
                classify_this = UnitLengthNorm(classify_this);
            elseif NormalizationIndex==4
                classify_this = MeanNorm(classify_this);
            elseif NormalizationIndex==5
                classify_this = MedianNorm(classify_this);
            elseif NormalizationIndex==6
            elseif NormalizationIndex==7  
                classify_this = SigmoidNorm(classify_this);
            elseif NormalizationIndex==8
                classify_this = TanhNorm(classify_this);
            end
            
        best_so_far = inf;

        for i = 1 : DS.TrainInstancesCount
            
            compare_to_this = DS.Train(i,:);
            
            if NormalizationIndex==2
                compare_to_this = MinMaxNorm(compare_to_this,0.001,1);
            elseif NormalizationIndex==3
                compare_to_this = UnitLengthNorm(compare_to_this);
            elseif NormalizationIndex==4
                compare_to_this = MeanNorm(compare_to_this);
            elseif NormalizationIndex==5
                compare_to_this = MedianNorm(compare_to_this);
            elseif NormalizationIndex==6
                [classify_this,compare_to_this] = AdaptiveScaling(classify_this,compare_to_this);
            elseif NormalizationIndex==7  
                compare_to_this = SigmoidNorm(compare_to_this);
            elseif NormalizationIndex==8
                compare_to_this = TanhNorm(compare_to_this);
            end

            distance = minkowski(compare_to_this,classify_this, param1);

            if distance < best_so_far
                class = DS.TrainClassLabels(i);
                best_so_far = distance;
            end
        end
        
        if (DS.TestClassLabels(id) == class)
            acc = acc + 1;
        end
    end
    
    acc = acc / DS.TestInstancesCount;
end