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any update about the XGBoost and LightGBM implementations?

yoremeyoreme Member Posts: 2 Learner I
I am new to RM. I have been looking for XGBoost in RM but apparently it is not implemented. I find it very strange that it is not implemented since it is a very popular and useful algorithm, or is there some other way to implement it in RM?
Thanks,
Aaron ST

Best Answer

  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,053  RM Data Scientist
    Solution Accepted
    Hi @yoreme ,
    we have it on our radar and if I am not mistaken XGBoost is the example for our python operator framework. So you can simply create your own python based operator to run XGBoost. You can check the help of Python Learner for some more infos: https://docs.rapidminer.com/latest/studio/operators/modeling/python_learner.html

    So far its a big hurdle to integrate LightGBM and XGBoost, since they are C(++) based. We are a Java platform, so this is not that straight forward. We carefully monitor this of course. If there is enough traction for alternative, 'native' XGBoost/Catboost/lightGBM implementations we will of course check what we can do.

    Best,
    Martin


    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
    lionelderkrikor

Answers

  • MichaelMichael Administrator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 25  RM Data Scientist
    Please not that the first tutorial process for the Python Learner operator already wraps LightGBM. If you have Python and LightGBM installed, it should work out of the box (you might have to configure your Python environment in RapidMiner first).
    lionelderkrikor
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