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- W2616062453 abstract "We propose a method to assist the user in the interpretation of the best Bayesian network model induced from data. The method consists in extracting relevant features from the model (e.g. edges, directed paths and Markov blankets) and, then, assessing the confidence in them by studying multiple locally optimal models of the data. We prove that our approach to confidence estimation is asymptotically optimal under the faithfulness assumption. Experiments with synthetic and real data show that the method is accurate and informative." @default.
- W2616062453 created "2017-05-26" @default.
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- W2616062453 date "2004-01-01" @default.
- W2616062453 modified "2023-09-27" @default.
- W2616062453 title "Featuring Multiple Local Optima to Assist the User in the Interpretation of Induced Bayesian Network Models." @default.
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