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Is there a way to see what is under the hood of the random forest? Is there a way to get the parameters of a trained model? Or maybe you can get the individual decisions trees as a nested-if-statement?
Thanks alot!
The text was updated successfully, but these errors were encountered:
Hi @DarkoAlexander, currently feature of visualzation is not supported in ThunderGBM, and we are considering to add this feature in the future. Also, we will be glad if you can make a contribution.
You say there is no feature of visualization. Is there also no way to get the parameters of the trained model? I want to get the numerical values for each node in each tree in the forest.
Right, there is no way to get the parameters of the trained model (or numerical values of each node) in Python for now. Maybe you can refer to this and implement your own method.
Is there a way to see what is under the hood of the random forest? Is there a way to get the parameters of a trained model? Or maybe you can get the individual decisions trees as a nested-if-statement?
Thanks alot!
The text was updated successfully, but these errors were encountered: