Decision Trees
Contents
Decision Trees#
Decision Tree from known features#
The idea of the decision tree is that you select a feature, split your data according to their label on this feature then recursively do that.
Ways to split#
Select feature based on its independent classification accuracy (at this point in
the tree, so conditioned on the data it is given)
Select feature based on lowest entropy
How many possible trees are there with n features
Pruning#
Remove leaves and assign label as majority of parent.
Prepruning#
Stop growing at some point (more popular)
Postpruning#
Prune after tree made