# Making model predictions

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## Making model predictions

 R User Forum Is there a better way than grabbing individual cell values from a model output to make predictions. For example the output from the following Naïve Bayes model library(e1071) ## Example of using a contingency table: data(Titanic) m <- naiveBayes(Survived ~ ., data = Titanic) m will produce the following results: Call: naiveBayes.formula(formula = Survived ~ ., data = Titanic) A-priori probabilities: Survived       No      Yes 0.676965 0.323035 Conditional probabilities:         Class Survived        1st        2nd        3rd       Crew      No  0.08187919 0.11208054 0.35436242 0.45167785      Yes 0.28551336 0.16596343 0.25035162 0.29817159         Sex Survived       Male     Female      No  0.91543624 0.08456376      Yes 0.51617440 0.48382560         Age Survived      Child      Adult      No  0.03489933 0.96510067      Yes 0.08016878 0.91983122 Say I want to calculate the probability of P(survival = No | Class = 1st, Sex = Male, and Age= Child). While I  can set an object (e.g. myObj <- m\$tables\$Class[1,1])  to the respective cell and perform the calculation, there must be a better way, as I continue to learn R. Jeff ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Making model predictions

 The standard approach for prediction is via a predict() method for the class of the model fit. So, have you checked ?predict.naiveBayes If this does not satisfy your needs, you are on your own. Possibly your best course of action then is to contact the maintainer as the posting guide (linked below) recommends for "non-standard" packages. (?maintainer) Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sat, Feb 27, 2021 at 6:42 AM Jeff Reichman <[hidden email]> wrote: > R User Forum > > Is there a better way than grabbing individual cell values from a model > output to make predictions. For example the output from the following Naïve > Bayes model > > library(e1071) > > ## Example of using a contingency table: > data(Titanic) > m <- naiveBayes(Survived ~ ., data = Titanic) > m > > will produce the following results: > > Call: > naiveBayes.formula(formula = Survived ~ ., data = Titanic) > > A-priori probabilities: > Survived >       No      Yes > 0.676965 0.323035 > > Conditional probabilities: >         Class > Survived        1st        2nd        3rd       Crew >      No  0.08187919 0.11208054 0.35436242 0.45167785 >      Yes 0.28551336 0.16596343 0.25035162 0.29817159 > >         Sex > Survived       Male     Female >      No  0.91543624 0.08456376 >      Yes 0.51617440 0.48382560 > >         Age > Survived      Child      Adult >      No  0.03489933 0.96510067 >      Yes 0.08016878 0.91983122 > > Say I want to calculate the probability of P(survival = No | Class = 1st, > Sex = Male, and Age= Child). > > While I  can set an object (e.g. myObj <- m\$tables\$Class[1,1])  to the > respective cell and perform the calculation, there must be a better way, as > I continue to learn R. > > Jeff > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.