[R] Naive Bayes Classifier

Murray Jorgensen maj at waikato.ac.nz
Thu May 17 02:38:20 CEST 2001

As I understand Naive Bayes it is essentially a finite mixture model for
multivariate categorical distributions where the variables are independent in
each component of the mixture. That is, I believe it to be a synonym Latent
Class analysis. I believe the Frayley/Raftery package mclust may include this
sort of model, and possibly other packages. Certainly these models may be
expressed in the language of graphical models. Whether or not this would be
useful for estimation purposes I am uncertain.

Murray Jorgensen

At 04:28 PM 16-05-01 +0100, Prof Brian Ripley wrote:
>On Wed, 16 May 2001, Ursula Sondhauss wrote:
>> I am looking for an implementation of the Naive Bayes classifier for a
>> multi-class classification problem. I can not even find the Naive Bayes
>> classifier for two classes, though I can not believe it is not
>> available. Can anyone help me?
>Hard to believe but likely true. However, as I understand this, it applies
>to a (K+1)-way contingency table, with K explanatory factors and and one
>response.  And the `naive Bayes' model is a particular model for that
>table.  If you want a classifier, you only need the conditional
>distribution of the response given the explanatory factors, and that is a
>main-effects-only multiple logistic model.  Now the *estimation*
>procedures may be slightly different (`naive Bayes' is not fully defined),
>but if that does not matter, use multinom() in package nnet to fit this.
>A book on Graphical Modelling (e.g. Whittaker or Edwards) may help
>elucidate the connections.
>Let me stress *as I understand this* here.
>Brian D. Ripley,                  ripley at stats.ox.ac.uk
>Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
>University of Oxford,             Tel:  +44 1865 272861 (self)
>1 South Parks Road,                     +44 1865 272860 (secr)
>Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
>Send "info", "help", or "[un]subscribe"
>(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
Murray Jorgensen,  Department of Statistics,  U of Waikato, Hamilton, NZ
-----[+64-7-838-4773]---------------------------[maj at waikato.ac.nz]-----
"Doubt everything or believe everything:these are two equally convenient
strategies. With either we dispense with the need to think."
http://www.stats.waikato.ac.nz/Staff/maj.html          - Henri Poincare'

r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch

More information about the R-help mailing list