update

app.py

@@ -290,11 +290,19 @@ if uploaded_file:
     #rf_probs = rf.predict_proba(input_df)[:, 1]
  #test
     # Combine results
+    # ✅ Apply Threshold to Convert Probabilities into Binary Predictions
+    THRESHOLD = 0.7  # Adjust to control false positives
+
+
+
     predictions_df = pd.DataFrame({
         "CatBoost": catboost_preds,
         "XGBoost": xgb_preds,
       #  "RandomForest": rf_preds
     })
+
+    catboost_preds = (catboost_probs >= THRESHOLD).astype(int)
+    xgb_preds = (xgb_probs >= THRESHOLD).astype(int)
     # Apply "at least one model predicts 1" rule
     predictions_df["is_click_predicted"] = predictions_df.max(axis=1)