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Tree is Too Large or Too Complex


CART determines that the optimal tree has a very large number of nodes and therefore is too complex for practical use or easy intelligibility.


SOLUTION 1: Pick a Smaller Tree

CART is designed to identify a set of candidate predictive trees complete with honest estimates of costs and standard errors. There is no reason not to decide to accept a higher error rate in exchange for a simpler tree, so long as you remain aware of the costs of the simplification.


SOLUTION 2: Parametric Model

Consider fitting a parametric model using CART to select variables and possible interactions. We have often used CART regression trees to partition a sample into subsets on which separate linear models are fit. CART can assist in specifying a switching regression.


Steinberg, Dan and Phillip Colla. CART--Classification and Regression Trees. San Diego, CA: Salford Systems, 1997.