Can I atleast get help with what pacakge to use for logistic
regression with all possible models and do prediction. I know i can
use regsubsets but i am not sure if it has any prediction functions to
go with it.
Thanks
On Oct 25, 6:54 pm, RAJ <dheerajathr...@gmail.com> wrote:
> Hello,
>
> I am pretty new to R, I have always used SAS and SAS products. My
> target variable is binary ('Y' and 'N') and i have about 14 predictor
> variables. My goal is to compare different variable selection methods
> like Forward, Backward, All possible subsests. I am using
> misclassification rate to pick the winner method.
>
> This is what i have as of now,
>
> Reg <- glm (Graduation ~., DFtrain,family=binomial(link="logit"))
> step <- extractAIC(Reg, direction="forward")
> pred <- predict(Reg, DFtest,type="response")
> mis <- mean({pred > 0.5} != {DFtest[,"Graduation"] == "Y"})
> This program actually works but I needed to check to make sure am
> doing this right. Also, I am getting the same misclassification rates
> for all different methods.
>
> I also tried to use
>
> Reg <- leaps(Graduation ~., DFtrain)
> pred <- predict(Reg, DFtest,type="response")
> mis <- mean({pred > 0.5} != {DFtest[,"Graduation"] == "Y"})
> #print(summary(mis))
> which doesnt work
>
> and
>
> Reg <- regsubsets(Graduation ~., DFtrain)
> pred <- predict(Reg, DFtest,type="response")
> mis <- mean({pred > 0.5} != {DFtest[,"Graduation"] == "Y"})
> #print(summary(mis))
>
> The Regsubsets will work but the 'predict' function does not work with
> it. Is there any other way to do predictions when using regsubsets
>
> Any help is appreciated.
>
> Thanks,
>
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