The automatic induction of classification rules from examples in the form of a decision tree is an important technique used in data mining. One of the problems encountered is the o...
Abstract. Branch predictors are associated with critical design issues for nowadays instruction greedy processors. We study two important domains where the optimization of decision...
Patrick Carribault, Christophe Lemuet, Jean-Thomas...
Most decision tree induction methods used for extracting knowledge in classification problems are unable to deal with uncertainties embedded within the data, associated with human...
1 Decision Tree Induction is a powerful classification tool that is much used in practice and works well for static data with dozens of attributes. We adapt the decision tree conce...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...