An MLE strategy for combining optimally pruned decision trees
Carmela Cappelli, William D. Shannon · COMPSTAT · 2000
This paper provides a maximum likelihood estimation strategy to identify a tree-based model which, being a function of a set of observed optimally pruned trees, represents the final classification model. The strategy is based on a probability distribution and it uses a metric based on structural differences among trees. An example on a real dataset is also presented to show how the procedure works.