Hi,
It *looks* to me like those are just 1 - criterion (from what is
printed). I did not see a nice way to extract them manually. Here is
what I did:
airq <- subset(airquality, !is.na(Ozone))
airct <- ctree(Ozone ~ ., data = airq,
controls = ctree_control(maxsurrogate = 3))
round(1 - airct@t
I have run the ctree function, and my dependent variable is broken into 3
categories: low cost, moderate cost and high cost.
When i plot the results (eg. using plot(test.ct)), the plot shows, at the
very bottom of each node, the probability of falling into each cost
category.
2 matches
Mail list logo
