[R] caret - prevent resampling when no parameters to find

[Max Kuhn]

Not all modeling functions have both the formula and "matrix"
interface. For example, glm() and rpart() only have formula method,
enet() has only the matrix interface and ksvm() and others have both.
This was one reason I created the package (so we don't have to
remember all this).

train() lets you specify the model either way. When the actual model
is fit, it favors the matrix interface whenever possible (since it is
more efficient) and works out the details behind the scenes.

For your example, you can fit the model you want using train():

   train(mdrrDescr,mdrrClass,method='glm')

If y is a factor, it automatically adds the 'family = binomial' option
when the model is fit (so you don't have to).

Max


On Sun, May 1, 2011 at 7:18 PM, pdb <philb at philbrierley.com> wrote:
> glm.fit - answered my own question by reading the manual!--
> View this message in context: http://r.789695.n4.nabble.com/caret-prevent-resampling-when-no-parameters-to-find-tp3488761p3488923.html
> Sent from the R help mailing list archive at Nabble.com.
>
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-- 

Max