Decision trees are a widely used knowledge representation in machine learning. However, one of their main drawbacks is the inherent replication of isomorphic subtrees, as a result...
Christophe Mues, Bart Baesens, Craig M. Files, Jan...
Decision trees have been successfully used for the task of classification. However, state-of-the-art algorithms do not incorporate the user in the tree construction process. This ...
In multiagent settings where agents have different preferences, preference aggregation can be an important issue. Voting is a general method to aggregate preferences. We consider ...
In this paper we present a study on the Random Forest (RF) family of ensemble methods. From our point of view, a "classical" RF induction process presents two main drawba...
In this paper we provide an automaton-based solution to the decision problem for a large set of monadic second-order theories of deterministic tree structures. We achieve it in two...