Cross validation for Naive Bayes and Bayes Networks

An embedded and charset-unspecified text was scrubbed...
Name: not available
URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20130414/3b4f8f7a/attachment.pl>

Hi Guilherme,

On Sun, Apr 14, 2013 at 11:48 PM, Guilherme Ferraz de Arruda

Hi,
I need to classify, using Naive Bayes and Bayes Networks,  and estimate
their performance using cross validation.
How can I do this?
I tried the bnlearn package for Bayes Networks, althought I need to get
more indexes, not only the error rate (precision, sensitivity, ...).

You can do that using the object returned by bn.cv(), because it
contains the predicted values and the indexes of the corresponding
observations in the original data, for each fold. It's just a matter
to reassemble observed and predicted class labels and compute your
metrics.

I also tried the *e1071* package, but I could not find a way to do
cross-validation.

You might be able to trick the tune() function to do it, but I am not sure.

Marco

Marco Scutari, Ph.D.
Research Associate, Genetics Institute (UGI)
University College London (UCL), United Kingdom