Pruning algorithm

In statistical genetics, Felsenstein's tree-pruning algorithm attributed to Joseph Felsenstein, is an algorithm for computing the likelihood of an evolutionary tree . Video created by University of Washington for the course Machine Learning: Classification. Out of all machine learning techniques, decision. This thesis presents pruning algorithms for decision trees and lists that are based on significance tests. A novel feature of our algorithm is its locality the decision to prune a. Our main result is a new and rather efficient pruning algorithm, and the . Pruning decision trees is a useful technique for improving the generalization performance in decision tree induction, and for trading accuracy for simplicity in . Alpha-beta pruning is an optimisation of the minimax algorithm.

It limits the search space by culling search paths that cannot contribute to the final result. K The algorithm template for the construction of decision trees, DT-construct, prefers larger. We have developed a pruning algorithm for likelihood estimation of a tree of populations.

This algorithm enables us to compute the likelihood for large trees.