Abstract. An object recognition process in general is designed as a domain specific, highly specialized task. As the complexity of such a process tends to be rather inestimable, m...
This paper extends previous work on skewing, an approach to problematic functions in decision tree induction. The previous algorithms were applicable only to functions of binary v...
In this paper, we present DeFer--a fast, high-quality, scalable, and nonstochastic fixed-outline floorplanning algorithm. DeFer generates a nonslicing floorplan by compacting a sli...
This paper investigates how the splitting criteria and pruning methods of decision tree learning algorithms are influenced by misclassification costs or changes to the class distr...
Conventional algorithms for decision tree induction use an attribute-value representation scheme for instances. This paper explores the empirical consequences of using set-valued ...