Article ID: | iaor200924649 |
Country: | United States |
Volume: | 18 |
Issue: | 4 |
Start Page Number: | 494 |
End Page Number: | 505 |
Publication Date: | Oct 2006 |
Journal: | INFORMS Journal On Computing |
Authors: | Huo Xiaoming, Kim Seoung Bum, Tsui KwokLeung, Wang Shuchun |
Keywords: | networks: path |
A frontier–based tree–pruning algorithm (FBP) is proposed. The new method has an order of computational complexity comparable to cost–complexity pruning (CCP). Regarding tree pruning, it provides a full spectrum of information: namely, (1) given the value of the penalization parameter λ, it gives the decision tree specified by the complexity–penalization approach; (2) given the size of a decision tree, it provides the range of the penalization parameter λ, within which the complexity–penalization approach renders this tree size; (3) it finds the tree sizes that are inadmissible—no matter what the value of the penalty parameter is, the resulting tree based on a complexity–penalization framework will never have these sizes. Simulations on real data sets reveal a ‘surprise’: in the complexity–penalization approach, most of the tree sizes are inadmissible. FBP facilitates a more faithful implementation of cross validation (CV), which is favored by simulations. Using FBP, a stability analysis of CV is proposed.