CARET: Any way to access other tuning parameters?
On Feb 13, 2013, at 6:58 AM, James Jong wrote:
The documentation for caret::train shows a list of parameters that one can tune for each method classification/regression method. For example, for the method randomForest one can tune mtry in the call to train. But the function call to train random forests in the original package has many other parameters, e.g. sampsize, maxnodes, etc. Is there **any** way to access these parameters using train in caret? (Is the function caret::createGrid limited to the list of parameters specified in the caret documentation, it's not super clear if the list of parameter is for all the caret APIs).
Have you looked at the argument list in ?train: ... arguments passed to the classification or regression routine (such as randomForest). Errors will occur if values for tuning parameters are passed here. Also look at: ? trainControl ? preProccess
David Winsemius Alameda, CA, USA