Comments (3)
parrt
commented on May 14, 2024
Hi. SHAP is indeed very interesting but technically is model agnostic and is not really related to decision tree visualization. As far as I can tell there's no overlap.
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zkurtz
commented on May 14, 2024
OK, if you're strictly looking at the visualization of the trees and disinterested in the corresponding effect sizes of the features used for splits, than the overlap may indeed be zero. SHAP does not appear to visualize trees per se. But it does have tree-specific explanations (shap.TreeExplainer) as demoed here. I wonder if there might be a way to overlay SHAP values on your tree visualizations that combines the best of both.
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parrt
commented on May 14, 2024
yep, even their "fast" tree specific one is too slow to be useful from my experience. I'm interested in feature importance, just not in this repo :) thanks...
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Related Issues (20)
- from dtreeviz.trees import * Import necessary libraries HOT 1
- Color keyword argument - Value error HOT 14
- Add support for TensorFlow GradientBoostedTreesModel model
- _regr_leaf_viz calculates the mean for prediction value.
- WARNING:matplotlib.font_manager:findfont: Font family 'Arial' not found. HOT 2
- Decision Tree visualize wrong path HOT 1
- When using dataset that is different from the training for trees models - does not draw HOT 1
- Support for RandomForest HOT 5
- 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
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