Hi, I am new to R and am using the ctree() function to do customer segmentation. I am using the following code to generate the tree: treedata$Response<-factor(treedata$Conversion) fit<-ctree(Response ~ .,controls=ctree_control(mincriterion=0.99,maxdepth=4),data=treedata) plot(fit) print(fit) The variable "Response" above equals 1 if the customer responded to an offering and 0 otherwise. Everything works great, however I am struggling to extract the information I need from the output. When I look at the output from print(fit) I see things similar to: 4) age <=42; criterion 1, statistic = 73.055 5)* weights = 5843 What this is telling me is that 5,843 customers ended up being classified into the group labeled 5. What I would really like to know, however, is what proportion of this 5,843 had Response=1 and what proportion had Response=0 so that I could make some inference about the P(Response) for customers that match the demographic characteristics of each terminal node. Any help on how to extract this information would be greatly appreciated -- thanks!
[[alternative HTML version deleted]] ______________________________________________ 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.