Top-Down Induction of Decision Trees

Main loop:

1.

$A \leftarrow$ the ``best'' decision attribute for next node

2.

Assign A as decision attribute for node

3.

For each value of A, create new descendant of node

4.

Sort training examples to leaf nodes

5.

If training examples perfectly classified, Then STOP, Else iterate over new leaf nodes

Which attribute is best?