Comments (1)
Heh, looks pretty cool! I think it is useful. Let's add
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Related Issues (20)
- Visualize custom decision tree HOT 1
- how to use dtreeviz in streamlit HOT 2
- VisualisationNotYetSupportedError: get_min_samples_leaf() is not implemented yet for XGBoost. HOT 4
- TypeError: list indices must be integers or slices, not numpy.float64 HOT 5
- Crash when leaf nodes have no samples HOT 1
- Out of memory when calling viz.view() HOT 2
- Integrate AI explanation
- CatBoost need to be supported. HOT 1
- AttributeError: module 'dtreeviz' has no attribute 'model' on Windows platform, works fine on Google colab
- tfdf.keras.CartModel support? HOT 1
- TypeError: 'int' object is not subscriptable HOT 3
- Development requirement in `setup.py` HOT 1
- Adjust Bounding Box of saved svg file
- DTreeViz crashes, if descision tree was built with objects, that are interpretable as numbers.
- How to use chinese? HOT 1
- get_score() is not implemented yet for XGBoost. HOT 1
- cannot import name 'dtreeviz' from 'dtreeviz.trees HOT 1
- VisualisationNotYetSupportedError: get_node_criterion() is not implemented yet for LightGBM
- VisualisationNotYetSupportedError: get_feature_path_importance() is not implemented yet for LightGBM
- Any way to filter features before plotting with instance_feature_importance(x,figsize=(10,12))? HOT 2
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