I have a data set with 24 predictor variables, all continuous, but with different scales and potential collinearity. I’m trying to decide whether to use
cforest in party with conditional importance permutation.
I recognize that I should probably use
cforest if I want to overcome variable selection bias, but I find the ability to get partial dependence plots and percent variance explained from the
randomForest package to be quite appealing.
I was wondering if anyone knew if it were possible to get partial dependence plots and percent variance explained from
Also, it appears that
ctree uses a significance test to select variables; is this the same for
cforest? And how might I get these significance values for each variable in cforest?