Hi,

Perhaps this is not the proper place to ask this

question but I am out of options, therefore I

apologize in advance.

I want to know how the (upper bound?) generalization

error of the random forest is determined using the

out-of-bag estimate. I read in Breiman's paper that s

and p determine the generalization error:

p(1-s^2)/s^2.

Does s stands for the strength of the individual tree

or of the entire ensemble? p stands for the

correlation between the trees.

If I have, let's say, built 3 trees in my forest and I

know for each tree the instances that were left out

during training, how do I calculate s and p, so I can

calculate the error?

Thanks in advance,

Martin

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