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Abstract: This report deals with Bayesian networks through a data mining project. Our goal has been to evaluate algorithms for learning a Bayesian classi- er for mastitis detection. We have studied the fundamental theory of causal and Bayesian networks, along with probability calculus and discritization of datasets. The datasets have been selected from a real-life database. This dataset is then discretized and fed to the batch learning algorithms, in order to compare the induced network... (Update)
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