Difference in performance of the Naive bayes and AODE algorithms

@pravin wrote:

Hi,

I read that like naive Bayes, AODE does not perform model selection and does not use tuneable parameters. As a result, it has low variance. It predicts class probabilities rather than simply predicting a single class, and can also handle the missing data.
Which of the two algorithms performs good? Is there a difference in situations where we should apply them or that one would outperform the other every time?

Thanks

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