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 <ph...@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. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Max ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
