—We propose an exhaustive search algorithm that calculates the VC-dimension of univariate decision trees with binary features. The VC-dimension of the univariate decision tree wi...
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
This paper addresses the issue of supporting the end-user of a classifier, when it is used as a decision support system, to classify new cases. We consider several kinds of classif...
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....
We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...