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fix(model-qa): explain regressors through the prediction fallback

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Signed-off-by: Rudy Celekli <47457359+rudycelekli@users.noreply.github.com>
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Rudy Celekli
2026-10-13 11:43:48 -04:00
parent 4bce55aa8b
commit 683cdbc55f
1 changed files with 4 additions and 6 deletions
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specialized/specialized-model-qa.md
+4 -6
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@@ -239,9 +239,8 @@ def shap_global_analysis(model, X: pd.DataFrame, output_dir: str = ".",
try:
explainer = shap.TreeExplainer(model)
except Exception:
explainer = shap.KernelExplainer(
model.predict_proba, shap.sample(X, 100)
)
predict = model.predict_proba if hasattr(model, "predict_proba") else model.predict
explainer = shap.KernelExplainer(predict, shap.sample(X, 100))
shap_values = explainer.shap_values(X)
@@ -284,9 +283,8 @@ def shap_local_explanation(model, X: pd.DataFrame, idx: int,
try:
explainer = shap.TreeExplainer(model)
except Exception:
explainer = shap.KernelExplainer(
model.predict_proba, shap.sample(X, 100)
)
predict = model.predict_proba if hasattr(model, "predict_proba") else model.predict
explainer = shap.KernelExplainer(predict, shap.sample(X, 100))
explanation = explainer(X.iloc[[idx]])
if explanation.values.ndim == 3: