Pruning. Prevent overfitting to noise in the data “Prune” the decision tree Two strategies: Postpruning take a fully-grown decision tree and discard unreliable parts Prepruning stop growing a branch when information becomes unreliable
f = 5/14 e = 0.46e < 0.51so prune!
(0.47*6 + 0.72 * 2 + 0.47 * 6)/14=0.51
Combined using ratios 6:2:6 gives 0.51