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Hi, I am using fasttreeshap v0.1.6 package to calculate the shap values of my random forest model. It really accelerate the shap value calculation substantially. However, when I tried to produce the s…
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### Search before asking
- [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and fou…
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For debugging black box models, it would be nice to get shapley feature importance values as they relate to the loss of the model rather than the prediction. I've seen this implemeted by the original …
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Hello,
I am trying predict_parts_shap_aggregated () to predict the important variable features of a random forest model.
However, I am getting this error -
**Error in `.rowNamesDF
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I want to output the Shap values, and the code as follow:
` double[] shap_values = model.predictForMat(featArray, 1, featArray.length, true,
PredictionType.C_API_PREDICT_CON…
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There are large differences between SHAP values calculated using CPU and GPU for XGBoost models with `feature_perturbation='interventional'` and `model_output='log_loss'`. The detailed description of …
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[SHAP Explainability](https://shap.readthedocs.io/en/latest/example_notebooks/overviews/An%20introduction%20to%20explainable%20AI%20with%20Shapley%20values.html) provides an explanation for the output…
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When retrieving `full_shap` values, debugger returns a matrix in the shape of `number of training samples, number of features` e.g.
```
for index,i in enumerate(trial.tensor_names(regex='full_shap')…
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## Description
The `InteractionValues` dataclass is the core data object containing the results and of approximators and explainers. For representing Shapley values (SVs) visually, the _shap_ package…
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**Addition Description**
SHAP is one of the state-of-the-art methods for computing feature importance using concepts from game theory.
Briefly, for each prediction, SHAP will estimate how much each …