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XGBoost into python code


Package pyxgboost converts a tree from xgboost into a Python code. Python still needs to be used if the models has to be deployed but it should be faster for small models.


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I would not say this module is actively maintained. It was more fun to have the idea, to test it on some simple model than to extend its coverage to all available models in scikit-learn. Some altenatives exists but it is still ongoing work. sklearn-porter proposed to produce code into many languages, C++, Javascipt, PHP, Java, Ruby, Go. It only includes learners and not transforms. onnx proposes to convert any models into a unified format. This module implements the format, onnxmltools, winmltools do the conversion of many models from scikit-learn, xgboost, lightgbm. The produced file can be used to run prediction on GPU and Windows with a dedicated runtime.


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