I apologize if you receive multiple copies of this letter. This is the first
time I've written to this mailing list, so please be kind:-)
Hello everyone!
I'm trying to make a programme which grows a classification tree. I use APL
programming language and I use R to compare and test results.
I have a classification tree and I have a sequence of cost-comlexity
parameters(alphas): 0,A1,A2...An. Now I want to choose a right-sized tree or, in
other words, the optimal complexity parameter Ak. I understand that I should use
a V-fold cross validation. The problem is that I don't quite understand how
to prune trees in CV:
1. If I use the initial sequence of alphas:
To test A1 I snip off all rooted nodes with cost-complexity parameters in a
range [0, A1]; to test A2 I prune all nodes with cost-complexity parameters in a
range [A1, A2]; ...etc. Is this correct?
2. If I use a new sequence of complexity parameters 0,B1,B2,...,Bm, where Bi is
the geometric mean of A[i] and A[i+1], Bi=SQRT( A[i] * A[i+1] ):
Suppose, I select Bk as an optimal parameter. Which Ai does this optimal Bk
correspond to?
Which of the two ways should I follow? Are there any other ways of choosing a
right-sized tree? Does anybody have any ideas?
Thank you
Kutinsky Vladimir
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