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Tree post-pruning and m_pruning

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Tree post-pruning and m_pruning

Postby pulsoste » Wed Jul 18, 2012 9:48

I'm building a classification tree with 1 million samples, on a two class problem. I'm wondering if using the m_pruning parameter = 2 as suggested before is a good number to do post pruning of the tree.

Does orange still implement the m estimates described in "Cestnik B. Estimating probabilities: A crucial task in machine learning. Proceedings of the Ninth European Conference on Artificial Intelligence", or has the implementation changed since 2005?


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