# [R] MSE Cross-validation with factor interactions terms MARS regression

Bert Gunter bgunter@4567 @end|ng |rom gm@||@com
Mon Oct 29 22:07:11 CET 2018

```I did no analysis of your code or thought process, but noticed that you had
the following two successive lines in your code:

y=Testing\$wage

y=Wage[-sam,]\$wage

This obviously makes no sense, so maybe you should fix this first and then
proceed.

-- Bert

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 Mon, Oct 29, 2018 at 1:46 PM varin sacha via R-help <r-help using r-project.org>
wrote:

>
> Dear R-experts,
> I am having trouble while doing crossvalidation with a MARS regression
> including an interaction term between a factor variable (education) and 1
> continuous variable (age). How could I solve my problem ?
>
> Here below my reproducible example.
>
> #######
>
> install.packages("ISLR")
>
> library(ISLR)
>
> install.packages("earth")
>
> library(earth)
>
> a<-as.factor(Wage\$education)
>
> # Create a list to store the results
>
> lst<-list()
>
> # This statement does the repetitions (looping)
>
> for(i in 1 :200) {
>
> n=dim(Wage)[1]
>
> p=0.667
>
> sam=sample(1 :n,floor(p*n),replace=FALSE)
>
> Training =Wage [sam,]
>
> Testing = Wage [-sam,]
>
> mars5<-earth(wage~age+education+year+age*a, data=Wage)
>
> ypred=predict(mars5,newdata=Testing)
>
> y=Testing\$wage
>
> y=Wage[-sam,]\$wage
>
> MSE = mean(y-ypred)^2
>
> MSE
>
> lst[i]<-MSE
>
> }
>
> mean(unlist(lst))
>
> summary(mars5)
>
> #######
>
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