Building a Decision Tree
- Basic Top-down algorithm:
- $A \leftarrow$ the best decision attribute for next
$node$.
- Assign $A$ as decision attribute for $node$.
- For each value of $A$, create new descendant of $node$.
- Sort training examples to leaf nodes.
- If training examples perfectly classified, Then STOP, Else iterate over new leaf nodes.
- This is basically the ID3 algorithm.
- What do we mean by best?
José M. Vidal
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