Comments (2)
For others who land here @ricoms mentioned that there may also be some issues with some versions of XGBoost 0.7. If you run into these try updated XGBoost to 0.8 :)
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The SHAP value implementation in XGBoost is very recent, so the 0.6 release does not have them. You will need 0.7, or even better the latest master of XGBoost.
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Related Issues (20)
- ENH: support for elementwise multiplication for pytorchdeep HOT 2
- [Meta-issue] Improve plotting API for consistency
- [Meta issue] Release 0.44.0 HOT 3
- BUG: Trouble with TreeExplainer, xgboost version, shap version 0.43.0, xgboost version 2.0.2 HOT 3
- BUG: Pytorch LSTM Not recognizednn.Model:LSTM HOT 1
- BUG: compute interaction values for catboost HOT 2
- ENH: Explaining squared loss in Regression Tree HOT 1
- MAINT: implement "no-response" bot to close issues where the author hasn't responded to a request for more information
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- ENH: Run Notebooks in CI pipeline HOT 2
- BUG: Force plot JS Not Initialized HOT 4
- BUG: Inconsistencies between different tree-based ensembles with the TreeExplainer HOT 1
- BUG: Categorical features in HistGradientBoostingRegressor
- Add GPU Support for explainability. HOT 2
- Add Support for More nn.Modules Layers. HOT 1
- BUG: shap does not work with Embeddings and tf.version >= 2.4
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