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RF tree size

December 29, 2011 Leave a comment Go to comments

The number of trees in Random Forest is suggested to be high enough in order to ensure that every input sample gets predicted at least a few times. It is suggested that if want auxiliary information like variable importance or proximity , grow a large number of trees is agg choice, since more stable results can be obtained. Well for the current testing data, I have seen that it is not straight proportional to the performance. Features from POS and NEG classes are not containing very good discrimination information, so even a very complex tree can not save the performance.

[Ref] http://oz.berkeley.edu/users/breiman/Using_random_forests_V3.1.pdf

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Categories: Data Mining
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