Why the decision tree structure is only binary tree for sklearn DecisionTreeClassifier?
<p>As we can see from the sklearn document <a href="http://scikit-learn.org/stable/modules/tree.html#classification" rel="nofollow">here</a>, or from my experiment, all the tree structure of DecisionTreeClassifier is binary tree. Either the criterion is gini or entropy, each DecisionTreeClassifier node can only has 0 or 1 or 2 child node.</p>

<p>But from the decision tree introduction <a href="http://www.cs.princeton.edu/courses/archive/spr07/cos424/papers/mitchell-dectrees.pdf" rel="nofollow">slide</a>(page 3), each node of theoretic decision tree can has more than 2 child node.</p>

<p>So my question is why the decision tree structure is only binary tree (each DecisionTreeClassifier node can only has 1 or 2 child node.) for sklearn DecisionTreeClassifier? Can we get the tree structure with more than 2 child node for DecisionTreeClassifier? </p>