linkedin / linkedin/FastTreeSHAP
FastTreeSHAP summary_plot plots interaction value instead of impact on model output
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- Dominant language
- Python
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Description
I am using `FastTreeSHAP` to help explained my random forest model prediction having over 40K samples and 24 features.
```
explainer = fasttreeshap.TreeExplainer(model, algorithm='auto' ,n_jobs=-1)
shap_values = explainer(X_test).values
shap_values.shape
(40682, 24, 5)
# plotting
fasttreeshap.summary_plot(shap_values, X_test, plot_type = 'bar')
```
The output figure is (showing top-5 features interaction):
I expected output figure to look similar to below image (FastTreeSHAP docs).
Is there any change in the `summary_plot()` method?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with fasttreeshap.summary_plot() using the reproduced 3-D shap_values shape and the bar plot example in the issue. Compare the generated feature ranking with the documented expected output, then verify that the completed behavior represents impact on model output rather than interaction values.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100