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Bayesian Networks provide an established approach to classification of objects in various types of activities. These range from technical via medical to economical applications. Heterogeneous sources provide observed declarations, which are evaluated by calculating the probabilities of resulting classes based on an underlying Bayesian Network model. Applying this classification process at different...
Bayesian Networks have various applications including medical and technical diagnosis, financial scoring, and target behavior/pattern recognition. Bayesian Classification Networks fuse evidence from heterogeneous and homogeneous sources and calculate classification results. For many reasons, pieces of evidence from different sources can carry apparently contradicting information and in these cases...
Identification in an air surveillance system is applied to a large number of tracks and can be implemented by means of Bayesian classification. Performed in an automated system, there is a strong need to monitor the identification process and contributing sensors by the operator. This paper describes two sensor failure-tests based on frequencies' evaluation of conflicting evidence by statistical means...
Classification has various applications, e.g., technical monitoring, medical diagnosis, financial scoring, and pattern recognition. In a classification problem, a class out of finitely many has to be chosen on basis of observed feature values. Bayesian Networks and particularly Na??ve Bayes Networks are an established approach to classification, where evidence from different sources is fused into...
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