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...d we use geterrMessage() to retrieve the error. When we execute the following command, cnr_model<-rpart(as.factor(Species)~Sepal Length+Sepal Width+Petal Length, method="class", parms=list(split="gini",prior=c()), control=rpart.control(minsplit=2, na.action=na.pass,cp=0.001,usesurrogate=1,maxsurrogate=2,surrogatestyle=0,maxdepth=20,xval=10)) we get an error message* "Error: unexpected symbol in "a<-cnr_model<-rpart(as.factor(Species)~Sepal Length""* The REXP returned in not null and the geterrMessage() call doesnt return an error message. But for ot...

Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below. What do I need to do to for rpart to build a tree with the variable experience? My guess is that this would happen if rpart used the loss matrix while creating