R help - Feb 2011 - J48 - contrasts can be applied only to factors with 2 or more levels

Hi everybody,

I recently sent out a first message using this tool and was astonished about the
quick and helpful replys. So, thank you in advance for your help, I really
appreciate that!

As already recently mentioned I am new to using R as I have to implement some
decision trees with R respectively RWeka for my master thesis. I have tried so
built some J48 trees and could accomplish first, very basic results. But when I
increased the number of independent variables the tree in fact is getting
created, but when I try to plot it, R displays ???Error in
`contrasts<-`(`*tmp*`, value = "contr.treatment") :  contrasts can
be applied only to factors with 2 or more levels??.

I found out that this was apparently due to IVs with only one value and so
excluded all these variables from the dataset and double-checked it by using the
summary function. Anyway the same error occurs. Anyone any idea? Is there a
specific function to test my dataset in this way instead of doing it manually or
with the summary function? FYI, the dataset contains 54 attributes, all kind of
scales and about 5,000 rows.


-- 
Schon geh?rt? GMX hat einen genialen Phishing-Filter in die

On 24.02.2011 15:29, Patrick Skorupka wrote:
> Hi everybody,
>
> I recently sent out a first message using this tool and was astonished
about the quick and helpful replys. So, thank you in advance for your help, I
really appreciate that!
>
> As already recently mentioned I am new to using R as I have to implement
some decision trees with R respectively RWeka for my master thesis. I have tried
so built some J48 trees and could accomplish first, very basic results. But when
I increased the number of independent variables the tree in fact is getting
created, but when I try to plot it, R displays ???Error in
`contrasts<-`(`*tmp*`, value = "contr.treatment") :  contrasts can
be applied only to factors with 2 or more levels??.
>
> I found out that this was apparently due to IVs with only one value and so
excluded all these variables from the dataset and double-checked it by using the
summary function. Anyway the same error occurs. Anyone any idea? Is there a
specific function to test my dataset in this way instead of doing it manually or
with the summary function? FYI, the dataset contains 54 attributes, all kind of
scales and about 5,000 rows.
>
>
You may want to supply a reproducible example of that behaviour as the 
posting guide asks you to do.

Best,
Uwe Ligges