In this paper, we present a feasibility study in automating the insurance claims processing system related to automotive sector. In automobile insurance claims processing, usually...
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
Recent work has shown the promise in using local-search “probes” as a basis for directing a backtracking-based refinement search. In this approach, the decision about the next...
Alexander Nareyek, Stephen F. Smith, Christian M. ...