Mercurial > repos > goeckslab > tabular_learner
comparison feature_importance.py @ 7:0afd970bd8ae draft default tip
planemo upload for repository https://github.com/goeckslab/gleam commit 55deacbbc78a00f27d789e11d563ba49dfb9cf9e
| author | goeckslab |
|---|---|
| date | Fri, 22 Aug 2025 21:13:44 +0000 |
| parents | 11fdac5affb3 |
| children |
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| 6:4bd75b45a7a1 | 7:0afd970bd8ae |
|---|---|
| 134 max_bg = min(len(X_data), 100) | 134 max_bg = min(len(X_data), 100) |
| 135 bg = X_data.sample(max_bg, random_state=42) | 135 bg = X_data.sample(max_bg, random_state=42) |
| 136 | 136 |
| 137 predict_fn = model.predict_proba if hasattr(model, "predict_proba") else model.predict | 137 predict_fn = model.predict_proba if hasattr(model, "predict_proba") else model.predict |
| 138 | 138 |
| 139 explainer = shap.Explainer(predict_fn, bg) | 139 try: |
| 140 self.shap_model_name = explainer.__class__.__name__ | 140 explainer = shap.Explainer(predict_fn, bg) |
| 141 | 141 self.shap_model_name = explainer.__class__.__name__ |
| 142 shap_values = explainer(X_data) | 142 |
| 143 shap_values = explainer(X_data) | |
| 144 except Exception as e: | |
| 145 LOG.error(f"SHAP computation failed: {e}") | |
| 146 self.shap_model_name = None | |
| 147 return | |
| 143 | 148 |
| 144 output_names = getattr(shap_values, "output_names", None) | 149 output_names = getattr(shap_values, "output_names", None) |
| 145 if output_names is None and hasattr(model, "classes_"): | 150 if output_names is None and hasattr(model, "classes_"): |
| 146 output_names = list(model.classes_) | 151 output_names = list(model.classes_) |
| 147 if output_names is None: | 152 if output_names is None: |