intial commit (forked from private repo)

extracted_cells/cell20.py

@@ -0,0 +1,25 @@
+def predict_fn(x):
+    # Konvertiere das NumPy-Array zurück in ein DataFrame mit den richtigen Feature-Namen
+    df = pd.DataFrame(x, columns=X_train.columns)
+    return best_rf_model.predict_proba(df)
+
+# Speichere mehrere Erklärungen
+explanations = []
+for i in range(100):
+    exp = lime_explainer.explain_instance(
+        instance, 
+        predict_fn,
+        num_features=20
+    )
+    explanations.append(exp.as_list())
+
+# Berechne die Varianz der Feature-Wichtigkeiten
+feature_variances = {}
+for i in range(len(explanations[0])):
+    feature = explanations[0][i][0]
+    values = [exp[i][1] for exp in explanations if len(exp) > i and exp[i][0] == feature]
+    feature_variances[feature] = np.var(values)
+
+print("Varianz der Feature-Wichtigkeiten:")
+for feature, variance in feature_variances.items():
+    print(f"{feature}: {variance:.6f}")