Bayesian classi cation addresses the classi cation problem by learning the distribution of instances given di erentclassvalues. We review the basic notion of Bayesian classi cation, describe in some d...
Most of today's terminological representation systems implement hybrid reasoning architectures wherein a concept classi er is employed to reason about concept de nitions, and a separate recognizer is ...
The issue of deletion schemes for classi er systems has received little attention. In a standard genetic algorithm achromosome can be evaluated (assigned a reasonable tness) immediately. In classi er ...
In order to facilitate the user's access to a movie lm the scene structure should be constructed. A general framework for constructing scenes consists in clustering the shots into groups and then merg...
The representation languages found in many expert system shells are hybrids composed ofaframe language and a rule language. Unfortunately, the frame and rule components in these systems are not well i...
We present a framework for characterizing Bayesian classi cation methods. This framework can be thought of as a spectrum of allowable dependence in a given probabilistic model with the Naive Bayes alg...
We consider the problem of classifying objects using their two dimensional silhouettes in environments generating large aberrant observations (outliers). These may be generated by failures in edge ext...