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 at tree$criterion$maxcriterion, 3)
round(1 - airct at tree$left$criterion$maxcriterion, 3)
round(1 - airct at tree$left$right$criterion$maxcriterion, 3)
round(1 - airct at tree$right$criterion$maxcriterion, 3)
I am not too familiar with the package so take what I said with a
grain or block of salt.
Cheers,
Josh
On Sun, Jul 31, 2011 at 6:40 AM, <seanstclair at verizon.net>
wrote:>
> ? 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.
>
>
>
> ? When i print the actual results (eg. using print(test.ct)), i get all of
the
> ? backup information, but i do not get the probability of falling into each
> ? cost category.
>
>
>
> ? Is ?there a way i can get these probabilities to show up on the actual
> ? summary of results using print function?
>
>
>
> ? THANKS.
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--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, ATS Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/