Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. A number of multi-class subgroup disc...
Probability trees (or Probability Estimation Trees, PET’s) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probabilit...
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
In this paper, we propose a new fast semi-supervised image segmentation method based on augmented tree partitioning. Unlike many existing methods that use a graph structure to mod...
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...