added support for XGBoost Random Forest estimators #157
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StrikerRUS
commented
Jan 25, 2020
| @@ -44,7 +44,7 @@ pip install m2cgen | |||
| | **Linear** | <ul><li>LogisticRegression</li><li>LogisticRegressionCV</li><li>PassiveAggressiveClassifier</li><li>RidgeClassifier</li><li>RidgeClassifierCV</li><li>SGDClassifier</li></ul> | <ul><li>ARDRegression</li><li>BayesianRidge</li><li>ElasticNet</li><li>ElasticNetCV</li><li>HuberRegressor</li><li>Lars</li><li>LarsCV</li><li>Lasso</li><li>LassoCV</li><li>LassoLars</li><li>LassoLarsCV</li><li>LassoLarsIC</li><li>LinearRegression</li><li>OrthogonalMatchingPursuit</li><li>OrthogonalMatchingPursuitCV</li><li>PassiveAggressiveRegressor</li><li>Ridge</li><li>RidgeCV</li><li>SGDRegressor</li><li>TheilSenRegressor</li></ul> | | |||
| | **SVM** | <ul><li>LinearSVC</li><li>NuSVC</li><li>SVC</li></ul> | <ul><li>LinearSVR</li><li>NuSVR</li><li>SVR</li></ul> | | |||
| | **Tree** | <ul><li>DecisionTreeClassifier</li><li>ExtraTreeClassifier</li></ul> | <ul><li>DecisionTreeRegressor</li><li>ExtraTreeRegressor</li></ul> | | |||
| | **Random Forest** | <ul><li>ExtraTreesClassifier</li><li>LGBMClassifier(rf booster only)</li><li>RandomForestClassifier</li></ul> | <ul><li>ExtraTreesRegressor</li><li>LGBMRegressor(rf booster only)</li><li>RandomForestRegressor</li></ul> | | |||
| | **Random Forest** | <ul><li>ExtraTreesClassifier</li><li>LGBMClassifier(rf booster only)</li><li>RandomForestClassifier</li><li>XGBRFClassifier(binary only, multiclass is not supported yet)</li></ul> | <ul><li>ExtraTreesRegressor</li><li>LGBMRegressor(rf booster only)</li><li>RandomForestRegressor</li><li>XGBRFRegressor</li></ul> | | |||
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Unfortunately, I'm not familiar enough with the XGBoost project to dig deeper into a code and find the reason why transpiling of multiclass models fails.
izeigerman
approved these changes
Jan 30, 2020
|
Honestly, me too! 😄 I opened #163 to try to involve more experienced in the XGBoost project people to investigate multiclass support problem. |
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Refer to https://xgboost.readthedocs.io/en/latest/tutorials/rf.html#standalone-random-forest-with-scikit-learn-like-api and dmlc/xgboost#4148.