Comments (2)
Hey, that is a great idea! I like the way it connects the feature values to their SHAP values while still only using a single dimension.
A PR would be much appreciated. If you have any questions just let me know.
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Awesome - I will submit one hopefully over the weekend.
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Related Issues (20)
- BUG: LightGBM with multiclass interaction TreeShap produces explainer error HOT 12
- ENH: Integrate Fasttreeshap speedup into SHAP HOT 2
- BUG: `base_score` attribute of the `XGBTreeModelLoader` is broken for all exponential losses (e.g. tweedie, poisson) HOT 4
- BUG: ERROR USING LLAMA-2 HOT 15
- BUG: 0.45.0 update breaks pytorch example on docs HOT 1
- x
- BUG: Error using Falcon for text-generation HOT 4
- BUG: Error when using DeepExplainer on LSTM Model HOT 1
- ENH: Partition Explainer for Video Models
- Does Feature/Column Order of dataset matter while calculating SHAP values? HOT 3
- When will the paddlepaddle framework be supported HOT 1
- BUG: LookupError: gradient registry has no entry for: shap_TensorListStack HOT 1
- BUG: shap summary plot for 3 group classification HOT 1
- ENH: Include directionality of feature association in beeswarm plot
- ENH: Support SeLU and activation function in Pytorch Deep Explainer
- BUG: tensorflow DeepExplainer SHAP explanations do not sum up to the model's output HOT 1
- Question: Using SHAP with GPT-4 via API HOT 1
- BUG: Warning: unrecognized nn.Module: Chomp1d HOT 2
- CI broken: mistralai Mistral-7B-v0.1 Tokenizer no longer accessible
- BUG: summary_plot ignores plot_type for TreeExplainer
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