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Evidence and scenario sensitivities in naive Bayesian classifiers
2008
International Journal of Approximate Reasoning
Empirical evidence shows that naive Bayesian classifiers perform quite well compared to more sophisticated network classifiers, even in view of inaccuracies in their parameters. In this paper, we study the effects of such parameter inaccuracies by investigating the sensitivity functions of a naive Bayesian classifier. We demonstrate that, as a consequence of the classifier's independence properties, these sensitivity functions are highly constrained. We investigate whether the various patterns
doi:10.1016/j.ijar.2008.02.008
fatcat:pd5vamaocfe6zdtcwbvtmrxyvy