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Decision Trees Help
Hello people! I have a problem, for a school projekt I have to learn how decision trees are working. So I used a demo data set from the book to build a decionion tree, I did everything just like it was in the book but my tree is very different from the tree in the book. Can some one help me to solve this problem?Thank you in advance
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Answers
Thanks for sharing your screenshots and findings. If you used the default set up of the derision tree, the "pruning" and "pre-pruning" will be automatically enabled to simply the tree and avoid overfitting.
There are some other parameters that can change the tree structure, max_depth, min_leaf_size, etc. The tree from the text book obviously have not been pruned that comes with more branches.
Cheers,
YY