Are there any good references for kernel-based Naive Bayesian classifier?

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    $\begingroup$ as far as I know, a kernel based NB is just a Naive Bayes which uses kernels to approximate the pdf of continuous variables, meanwhile "default" NB assumes a normal distribution (or make the data discrete beforehand). In this spirit, is the paper linked in this question/answer sufficient ? Use of kernel density estimate in Naive Bayes Classifier? $\endgroup$
    – steffen
    Commented Jul 5, 2012 at 12:17
  • $\begingroup$ or, to be more precise, I have the slight feeling that your question is a duplicate of the linked one. Do you agree on this ? $\endgroup$
    – steffen
    Commented Jul 5, 2012 at 12:20


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