If you fit a classification tree to the famous Fisher iris data, you get this:
>> load fisheriris
>> f = fitctree(meas,species);
>> view(f)
Decision tree for classification
1 if x3<2.45 then node 2 elseif x3>=2.45 then node 3 else setosa
2 class = setosa
3 if x4<1.75 then node 4 elseif x4>=1.75 then node 5 else versicolor
4 if x3<4.95 then node 6 elseif x3>=4.95 then node 7 else versicolor
5 class = virginica
6 if x4<1.65 then node 8 elseif x4>=1.65 then node 9 else versicolor
7 class = virginica
8 class = versicolor
9 class = virginica
So you can see:
- The tree has more than two branches
- It can predict more than two classes (three in this case)
- However, at each branch it makes a binary decision, X<s or X>=s
If X happens to be a categorical predictor, then it still makes a binary decision of the form "X is among this group of categories" or "X is among this other group."
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