[R] Making model predictions

[Jeff Reichman]

Rui

Actually yes.  I was able to work this into my shiny app this afternoon. 

Thank you

Jeff

-----Original Message-----
From: Rui Barradas <ruipbarradas using sapo.pt> 
Sent: Sunday, February 28, 2021 5:26 AM
To: reichmanj using sbcglobal.net; R-help using r-project.org
Subject: Re: [R] Making model predictions

Hello,

Are you looking for this?


newd <- data.frame(
   Class = '1st',
   Sex = 'Male',
   Age = 'Child'
)
predict(m, newdata = newd, type = 'raw')
#            No       Yes
#[1,] 0.3169345 0.6830655


With the default type = 'class' the result is

predict(m, newdata = newd)
#[1] Yes
#Levels: No Yes


Hope this helps,

Rui Barradas

Às 14:42 de 27/02/21, Jeff Reichman escreveu:
> 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
> 
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