Decision Trees – Are They Almost Always Binary Trees?

cartdata miningmachine learning

Nearly every decision tree example I've come across happens to be a binary tree. Is this pretty much universal? Do most of the standard algorithms (C4.5, CART, etc.) only support binary trees? From what I gather, CHAID is not limited to binary trees, but that seems to be an exception.

A two-way split followed by another two-way split on one of the children is not the same thing as a single three-way split. This might be an academic point, but I'm trying to make sure I understand the most common use-cases.

Best Answer

This is mainly a technical issue: if you don't restrict to binary choices, there are simply too many possibilities for the next split in the tree. So you are definitely right in all the points made in your question.

Be aware that most tree-type algorithms work stepwise and are even as such not guaranteed to give the best possible result. This is just one extra caveat.

For most practical purposes, though not during the building/pruning of the tree, the two kinds of splits are equivalent, though, given that they appear immediately after each other.