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Author Topic: Decision Tree + Validation: different validation methods yield different trees.  (Read 38 times)
maverik
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« on: July 07, 2014, 03:35:27 PM »

Hello! I have a dataset with about 500 examples and 50 attributes. I try to use the Decision Tree operator nested in either 5 or 10 fold X-validation or 5 fold bootstrapping validation operator. I let the tree grow for 10 steps without pre-pruning. This results in 2 trees similar on the top levels but quite different from level 4 onwards. Could someone please explain how the validation methods affect tree structure? And what is the criteria to decide which tree to pick? Many thanks!
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