Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Empirical evidence shows that naive Bayesian classifiers perform quite well compared to more sophisticated network classifiers, even in view of inaccuracies in their parameters. I...
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...