On Wed, 7 Apr 2010, Steven J. Clark wrote:
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.
See
help("BinaryTree-class")
especially the examples section. With where(fit) you can query the node
number and with treeresponse(fit) you get a list with the frequency
distribution. There are also some worked examples how you can compute
other quantities of interest.
hth,
Z
Any help on how to extract this information would be greatly appreciated
-- thanks!
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