Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
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Is library supporting scikit-learn API such as XGBoost or LightGBM compatible to HSTreeClassifier/Regressor? #171
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HyukdongKim closed 1 year ago
First, thank you for creating such an awesome library.
I tried to apply HSTreeClassifier(&Regressor) to the XGBoost library and it does not change anything to prediction.
Of course, I saw in the support-for-different-tasks in readme.md that it says 'Wraps any sklearn tree-based model'.
Is that means only compatible to scikit-learn's model or other possibilities?
Test env followings:
From sklearns example, I just changed
to
And I noticed HSTreeClassifier works to DecisionTreeClassifier, RandomForestClassifier and AdaBoostClassifier. But not to XGBClassifier.
Base template![image](https://user-images.githubusercontent.com/64831904/233602179-33486411-fa3c-408c-845d-8f4267918116.png)
with HSTreeClassifier![image](https://user-images.githubusercontent.com/64831904/233602289-3a972397-8aaf-4618-a97b-cc0b25a1e245.png)