1 Classification and Regression Tree Intro 2 1.1 Classification and Regression Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Decision Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Building Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.4 Recursive Binary Partition (CART) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.5 Growing a Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.6 Splitting Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.7 Stopping and Pruning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.8 Special Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.9 Tree Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.10 Tree Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.11 Trees in R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
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