[R] NAIVE BAYES with 10-fold cross validation

["Julia Kröpfl"]

thx for your help,

i checked the caret package out and the tuning works. but i can't find a way to make a contingency table in order to see the classification result.

e.g. like:

table(outcome NaiveBayes, mydata$code)

Is there something like that?

Julia

-------- Original-Nachricht --------
> Datum: Tue, 30 Oct 2007 17:03:49 -0400
> Von: "Kuhn, Max" <Max.Kuhn at pfizer.com>
> An: "Julia Kröpfl" <jkroepfl at gmx.net>, r-help at r-project.org
> Betreff: RE: [R] NAIVE BAYES with 10-fold cross validation

> > am trying to implement the code of the e1071 package for naive bayes, 
> > but it doens't really work, any ideas??
> > am very glad about any help!!
> > need a naive bayes with 10-fold cross validation:
> 
> The caret package will do this. Use
> 
>  fit <- train(
>    x, y, method = "nb", 
>    trControl = trainControl(method = "cv", number = 10))
> 
> (there is no formula interface yet).
> 
> It will use the naïve Bayes implementation in klaR. Unless you specify
> otherwise, it will train naïve Bayes models with and without using kernel
> density estimation (but you can change that). 
> 
> The object fit$finalModel will contain the model fit that is "cv optimal".
> 
> For example:
> 
>  > fit <- train(
>  +    iris[,-5], iris$Species, "nb", 
>  +    trControl = trainControl(method = "cv", number = 10))
>  Iter 1  Values: TRUE 
>  Loading required package: MASS
>  Loading required package: class
>  Iter 2  Values: FALSE 
>  > 
>  > fit
>  
>  Call:
>  train.default(x = iris[, -5], y = iris$Species, method = "nb", 
>      trControl = trainControl(method = "cv", number = 10))
>  
>  150 samples
>  4 predictors
>  
>  summary of cross-validation (10 fold) sample sizes:
>      135, 135, 135, 135, 135, 135, ... 
>  
>  cv resampled training results across tuning parameters:
>  
>    usekernel  Accuracy  Kappa  Accuracy SD  Kappa SD  Optimal
>    FALSE      0.953     0.93   0.0706       0.106            
>    TRUE       0.96      0.94   0.0562       0.0843    *      
>  
>  Accuracy was used to select the optimal model
>  
> 
> Max
> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On Behalf Of "Julia Kröpfl"
> Sent: Tuesday, October 30, 2007 4:46 PM
> To: r-help at r-project.org
> Subject: [R] NAIVE BAYES with 10-fold cross validation
> 
> hi there!!
> 
> i am trying to implement the code of the e1071 package for naive bayes,
> but it doens't really work, any ideas??
> i am very glad about any help!!
> i need a naive bayes with 10-fold cross validation:
> 
> code:
> library(e1071)
> 
> model <- naiveBayes(code ~ ., mydata)
> 
> tune.control <- tune.control(random = FALSE, nrepeat = 1, repeat.aggregate
> = min,
> sampling = c("cross"), sampling.aggregate = mean,
> cross = 10, best.model = TRUE, performances = TRUE)
> 
> pred <- predict(model, mydata[,-12], type="class")
> tune(naiveBayes, code~., mydata, predict.fun=pred, tune.control)
> 
> 
> thx for your help!
> cheers, julia
> --
> 
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