Saeed,

There is a version in the klaR package. I recently submitted a change to
the predict function that may be related to your problem. 

If:

  1. the posterior probabilities (apart from the prior) are being
approximated by the product of the p(x_i|y_j) and

  2. a lot of predictors are being used

then posterior probabilities may have values of absolute zero. 

When the approximation is used, the approximate posterior probabilities
are normalized by their sum (which is zero in such cases).

The patch in klaR uses the product of the conditional divided by the
marginal of x_i (per the true formula). I haven't seen the problem occur
with this patch.

HTH,

Max

-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Saeed Abu Nimeh
Sent: Monday, June 04, 2007 2:45 PM
To: [email protected]
Subject: [R] naiveBayes other than e1071

Hi List,
Is there a naiveBayes interface other than the one in e1071 package. For
some reason on certain datasets all predicted values are NaN, but it
predicts well on others.
Thanks,
Saeed
---
model <- naiveBayes(x.train, y.train, laplace = 3)
pred <- predict(model,x.test,type="raw")

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