# MLE for Naive Bayes in R

I am using the naivebayes function of the e1071 library. Some example commands are:

model = naiveBayes(Species ~ ., data = iris)
pred = predict(model, iris[,])


My question is: how can I obtain the maximum likelihood estimate for the conditional probability distribution of this model?

• Crossposting between here and StackOverflow is discouraged. – Dirk Eddelbuettel Oct 27 '10 at 15:47
• I would suggest that this would be the more appropriate place for this question. – csgillespie Oct 27 '10 at 15:48
• sorry for crossposting.i didn't know here when i posted the question to stackoverflow.somebody suggested here and i posted here then. thanks. – Yuan Oct 27 '10 at 15:50
• At the very least, you should provide the link to the other posting. – Jeromy Anglim Oct 28 '10 at 3:20

This seems a bit ambiguous... What's wrong with model$table? • unfortunately, i have no background in statistics so i don't know what to expect from a "MLE" output. sorry for that. so, when i print model$table, i get something like below. is this MLE? Sepal.Length Y [,1] [,2] setosa 5.006 0.3524897 versicolor 5.936 0.5161711 virginica 6.588 0.6358796 – Yuan Oct 27 '10 at 17:18