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Author: AmirhosseinHonardoust

app.py

@@ -182,7 +182,7 @@ def main():
 """)
 
     st.warning(
-        "This dashboard uses a synthetic, highly separable demo dataset. "
+        "This dashboard uses a synthetic demo dataset with overlapping classes and label noise. "
         "It demonstrates fraud-risk workflow design, not real-world fraud benchmark performance."
     )
 

src/dashboard_utils.py

@@ -83,8 +83,8 @@ def build_model_metadata(
         "threshold_recall": best_threshold.get("recall"),
         "threshold_precision": best_threshold.get("precision"),
         "data_note": (
-            "Synthetic, highly separable demo data. Metrics validate the workflow and should not "
-            "be treated as real-world fraud benchmark performance."
+            "Synthetic demo data with overlapping classes and label noise. Metrics validate "
+            "the workflow and should not be treated as real-world fraud benchmark performance."
         ),
     }
 

src/train_model.py

@@ -69,8 +69,9 @@ def train_and_evaluate() -> dict:
         "positive_rate_train": float(y_train.mean()),
         "positive_rate_test": float(y_test.mean()),
         "note": (
-            "This synthetic demo dataset is highly separable. Probability metrics should be "
-            "interpreted as workflow checks, not real-world fraud benchmark performance."
+            "This synthetic demo dataset has overlapping classes and injected label noise. "
+            "Probability metrics should be interpreted as workflow checks, not real-world "
+            "fraud benchmark performance."
         ),
     }