Can someone explain the error? Function with duplicate name dtree cannot be defined

load iris.dat

%discretizeData

discretizedData = zeros(150,5);
for i = 1:size(iris,2)
    currentColumn = iris(:,i);
    bins = length(currentColumn)/4;
    discretizedData(:,i) = round(currentColumn/bins)+1;
    if(i == 5)
       for j = 1: size(iris,1)
          if( iris(j,5) == 2 || iris(j,5) == 3)
              discretizedData(j,5) = -1;
          end
       end
    end
end

%generate test and train data

posIndex = randperm(50,25);
negIndex = randperm(150,50);

trainData = zeros(75,5);
trainData(1:25,:) = discretizedData(posIndex,:);
trainData(26:75,:) = discretizedData(negIndex,:);

list1=[];
list2=[];

%start of the decision tree algorithm
function e = dtree(trainData,list,dominant)
    if size(trainData,1) == 0
        list(length(list)+1) = strcat('=>',num2str(dominant));
        disp(list) %print the rule at the leaf
        e = 1;
    end
    dominant = dominantLabel(trainData);
    nFeatures = size(trainData,2)-1;
    levelEntropy = 999;
    for i = 1:nFeatures
        uniqueValues = unique(trainData(:,i));
        nUnique = length(uniqueValues);
        for u = 1:nUnique
            tposExample = trainData((find(trainData(:,i) == uniqueValues(u) & trainData(:,5) == 1)),:);
            tnegExample = trainData((find(trainData(:,i) == uniqueValues(u) & trainData(:,5) == -1)),:);
            fposExample = trainData((find(trainData(:,i) ~= uniqueValues(u) & trainData(:,5) == 1)),:);
            fnegExample = trainData((find(trainData(:,i) ~= uniqueValues(u) & trainData(:,5) == -1)),:);
            tEntropy = entropy(tposExample,tnegExample);
            fEntropy = entropy(fposExample,fnegExample);
            thisLevelEntropy = (size(tposExample,1)+size(tnegExample,1))*tEntropy + (size(fposExample,1)+size(fnegExample,1))*fEntropy;
            if thisLevelEntropy < levelEntropy
                levelEntropy = thisLevelEntropy;

                  bestFeature1 = strcat('f',num2str(i),'=',num2str(u)+'^');

                  bestFeature2 = strcat('!f',num2str(i),'=',num2str(u)+'^');

              end
          end
      end
      list1(length(list)+1) = bestFeature1;
      list2(length(list)+1) = bestFeature2;
      dtree(vertcat(tposExample,tnegExample),list1,dominant);
      dtree(vertcat(fposExample,fnegExample),list2,dominant);
  end

%dominant label function
function dm = dominantLabel(trainingData)
    posIndices = find(trainingData(:,5)==1);
    negIndices = find(trainingData(:,5)==-1);
    posCount = size(posIndices,1);
    negCount = size(negIndices,1);
    if posCount > negCount
        dm = 1;
    else
        dm = -1;
    end
end

%entropy function
function en = entropy(tExamples,fExamples)
    posCount = size(tExamples,1);
    negCount = size(fExamples,1);
    pPos = posCount/(posCount+negCount);
    pNeg = 1 - pPos;
    en = -1*(pPos*log(pPos) + pNeg*log(pNeg));
end

Answer 1

[Walter Roberson]

If all of those are saved into the same .m file, then the combination of script and functions would only be permitted in R2016b or later.

In R2016b it would be permitted, but you would need to name the script something other than dtree.m : when you use a function in a script in R2016b or later, you cannot name the function the same thing as the script.