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

[pdb]

Thanks again Max - a great time saver this is.

Now just for my sanity, if I use glm.fit to build a model where I have the
matrices, how do I then use the predict function without getting an error
message?

> LOGISTIC_model1 <- glm.fit(mdrrDescr,mdrrClass,
> family=binomial(link="logit")) 
Warning messages:
1: glm.fit: algorithm did not converge 
2: glm.fit: fitted probabilities numerically 0 or 1 occurred 
> predict(LOGISTIC_model1) 
Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class
"c('double', 'numeric')"

Secondly, caret acts as a nice wrapper to protect me from all this, and it
does the resampling to give me an idea of the expected model fit. If I was
doing a parameter search, would it do all this resampling for each
combination of parameters? Now if I just want to build a model and not worry
about all the resampling (in my case I just want a set of baseline
predictions to compare various variable selections methods against) it would
be nice if there was a simple option to turn off the resampling.

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