Comments (1)
The link function is there since non-linear transformations of the shap values will break additivity because
Hmm, not sure where it should be applied, usually one hands the link over to the masker. Will need to take another look but wanted to note this here.
Edit: I guess the link function/linearized_link should be applied before checking additivity and nowhere else.
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Related Issues (20)
- Support for KerasClassifier HOT 1
- BUG: Failed in nopython mode pipeline (step: native lowering) float16 HOT 4
- Questions: question about SamplingExplainer HOT 1
- BUG: SHAP values calculated using CPU differ from SHAP values calculated using GPU HOT 5
- BUG: TypeError: ufunc 'isfinite' not supported for the input types HOT 4
- BUG: Additivity check failed HOT 1
- When plotting the shap text it is showing an extra letter(Ġ) before every word. HOT 1
- Demangle pytorch and tensorflow dependencies
- ENH: Python 3.13 Support
- TypeError: In v0.20, force plot now requires the base value as the first parameter! Try shap.plots.force(explainer.expected_value, shap_values) or for multi-output models try shap.plots.force(explainer.expected_value[0], shap_values[0]). HOT 1
- Key not found with shap.TreeExplainer and XGBRegressor HOT 1
- BUG: Unable to Generate SHAP values for a dataframe containing text data trained on lstm model HOT 2
- BUG: Error with SHAP Partial Dependence Plot: ValueError: DataFrame.dtypes for data must be int, float, bool or category
- ENH: integrated gradients
- Support tf 2.16 and keras 3 HOT 4
- BUG: shap.plots.bar(shap_values) TypeError
- BUG: Custom masker offset is not working properly
- BUG: AssertionError, the SHAP explanations do not sum up to the model's output!
- BUG: Background dataset subsampling HOT 4
- BUG: AttributeError: 'tuple' object has no attribute 'as_list' (tensorflow 2.15.0) HOT 2
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