Andy,

Does it mean that the error rate does increase as long as the aggregating
number of out-of-bag cases reaches the number of all cases?  or, in other
words, because the number of points being predicted (right or wrong) gets
larger at the first steps of the process?

If it so then it's all clear now.

A few more questions.
1. What is the format of using the "classwt" parameter? Should it be
something like c(0.3,0.6,0.1)?

2. Where can I find any information about rf$forest element of the result?
namely about its elements like $treemap, $nodeclass etc?

Thanks,
Vladimir

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