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Induction of decision trees is one of the most successful approaches to supervised machine learning. Branching programs are a generalization of decision trees and, by the boosting analysis, exponentially more efficiently learnable than decision trees. However, this advantage has not been seen to...
The spatial world consists of regions and relationships between regions. Examples of such relationships are that two regions are disjoint or that one is a proper part of the other. The formal specification of spatial relations is an important part of any formal ontology used in qualitative...
AdaBoost is a method for improving the classification accuracy of a given learning algorithm by combining hypotheses created by the learning alogorithms. One of the drawbacks of AdaBoost is that it worsens its performance when training examples include noisy examples or exceptional examples,...
Knowledge Discovery in Databases (KDD) is an active and important research area with the promise for a high payoff in many business and scientific applications. One of the main tasks in KDD is classification. A particular efficient method for classification is decision tree induction. The...
Symmetry-breaking formulas for a constraint-satisfaction problem are satisfied by exactly one member (e.g., the lexicographic leader) from each set of “symmetrical points” in the search space. Thus, the incorporation of such formulas can accelerate the search for a solution without sacrificing...
In this paper we consider the open problem how to unify version-space representations. We present a first solution to this problem, namely a new version-space representation called adaptable boundary sets (ABSs). We show that a version space can have a space of ABSs representations. We...
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