Unintentional Vandalism: Unskilled tree pruning practices in tree management

Risk Management in Game-tree Pruning Risk Management in Game-tree Pruning

Risk Management in Game-Tree Pruning

In the half century since minimax was first suggested as a strategy for adversary game search, various search algorithms have been developed. The standard approach has been to use improvements to the Alpha-Beta (α-β) algorithm. Some of the more powerful improvements examine continuations beyond the nominal search depth if they are of special interest, while others terminate the search early. Th...

Probability-Based Game Tree Pruning

In game-tree search, a point value is customarily used to measure position evaluation. If the uncertainty about the value is to be reflected in the evaluation, which is described with probabilistic distribution or probabilities, the search process must back up distributions from leaf nodes to the root. It is shown that even though the merit value of a node is described by probabilities, α-β bou...

Decision Tree Pruning: Biased or

We evaluate the performance of weakestlink pruning of decision trees using crossvalidation. This technique maps tree pruning into a problem of tree selection: Find the best (i.e. the right-sized) tree, from a set of trees ranging in size from the unpruned tree to a null tree. For samples with at least 200 cases, extensive empirical evidence supports the following conclusions relative to tree se...

MDL-Based Decision Tree Pruning

This paper explores the application of the Min imum Description Length principle for pruning decision trees We present a new algorithm that intuitively captures the primary goal of reduc ing the misclassi cation error An experimental comparison is presented with three other prun ing algorithms The results show that the MDL pruning algorithm achieves good accuracy small trees and fast execution ...