R help - Mar 2010 - kknn and logistic regression: how to cross-validate binary prediction

I am comparing kknn and logistic regression for binary outcome prediction -

For kknn, I can do -

kknn_<-kknn(out_come ~ age + gender , learn_, valid_)
fit<-fitted(kknn_)
table(valid_$out_come, fit)

to get validation results in cross-tabulation.

---------

For logistic, how can I do the equivalent cross-validation?

logit_<-glm(out_come ~ age + gender, data=learn_, family=binomial)
...
... 
then how could I fit the logistic regression on validation data (ie. valid_)
to get predicted outcome?

Thanks!
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Take a look at the caret package

http://cran.r-project.org/web/packages/caret/index.html

and the package vignettes, especially the one labeled as "model  
builing".

Max



On Mar 15, 2010, at 6:11 PM, noclue_ <tim.liu at netzero.net> wrote:
>
> I am comparing kknn and logistic regression for binary outcome  
> prediction -
>
> For kknn, I can do -
>
> kknn_<-kknn(out_come ~ age + gender , learn_, valid_)
> fit<-fitted(kknn_)
> table(valid_$out_come, fit)
>
> to get validation results in cross-tabulation.
>
> ---------
>
> For logistic, how can I do the equivalent cross-validation?
>
> logit_<-glm(out_come ~ age + gender, data=learn_, family=binomial)
> ...
> ...
> then how could I fit the logistic regression on validation data (ie.  
> valid_)
> to get predicted outcome?
>
> Thanks!
> -- 
> View this message in context:
http://n4.nabble.com/kknn-and-logistic-regression-how-to-cross-validate-binary-prediction-tp1594107p1594107.html
> Sent from the R help mailing list archive at Nabble.com.
>
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