Jan 8, 2025 · I encountered an AssertionError while using shap.DeepExplainer with a PyTorch LSTM model. The error states: AssertionError: The SHAP explanations do not sum up to the model's output! This is either because of a rounding error or because an operator in your computation graph was not fully supported.

Sep 30, 2024 · I encounter this bug when trying to visualize the plot create by shap.image_plot. In this plot all of the images in shap_values are very small and are unable to view. Minimal Reproducible Example

Jun 23, 2023 · Latest version 0.47.1 triggers "SHAP.ReactDom.render is not a function" regression Regression bugs - worked once, not anymore

Mar 22, 2025 · This release contains many bugs fixes and lots of new functionality, specifically for transformer based NLP models. Some highlights include: New plots, bug fixes, docs, and features for NLP model explanations (see docs for details). important permutation explainer performance fix by @sander-sn

Aug 12, 2024 · 该bug原因可以在此issue中了解： BUG: Unexpected Interaction Plot Instead of Summary Plot in Multiclass SHAP Summary with XGBoost，错误是由于0.45.0版本中的更改，他们将输出从list更改为 numpy 数组导致 异常。 解决办法有两种： 1. 注释explainers/_tree.py第515-516行. 2. 切换到shap==0.44.1. 修改bar颜色. 需要传入一个 函数 作为color的参数： colors = ["#1F77B4", "#6da2d2", "#8cb8e1"] 文章浏览阅读1.1k次，点赞21次，收藏17次。

Jul 5, 2021 · So here's my code using shap : Since I just plot three times the same shape values, I'd expect the three plots to be the same. However, it keeps on changing. After some research, it seems that a new value appear at the top at each call, but why ? Is it a bug in shap ?

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As you can see below, the Tree SHAP algorithm is used to estimate the Shapley values. Tree SHAP is a method specifically designed for tree models and tree ensembles that estimates Shapley...

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Apr 27, 2024 · When attempting to use SHAP with an XGBoost multiclass classification model to generate summary plots, the output unexpectedly appears as an interaction plot rather than the anticipated summary plot. This issue occurs when trying to visualize the SHAP values for all classes simultaneously.