Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
Decisionand optimizationproblemsinvolvinggraphsarise in manyareas of artificial intelligence, including probabilistic networks, robot navigation, and network design. Manysuch prob...
In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several ha...
The current evaluation functions for heuristic planning are expensive to compute. In numerous domains these functions give good guidance on the solution, so it worths the computat...
Decision trees are widely disseminated as an effective solution for classification tasks. Decision tree induction algorithms have some limitations though, due to the typical strat...