Add print statement to display the top 10 SE Scores in predict_dupes function for debugging purposes

global_func/predict_dupes.py

@@ -444,6 +444,8 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
     portfolio['Geomean'] = np.power((portfolio[own_columns] * 100).product(axis=1), 1 / len(own_columns))
     portfolio['SE Score'] = ((portfolio['median'] - portfolio['median'].mean()) * (portfolio['Weighted Own'] - portfolio['Weighted Own'].mean()))
     portfolio['SE Score'] = (np.tanh(portfolio['SE Score'] / portfolio['SE Score'].std()) + 1) / 2
+
+    print(portfolio['SE Score'].head(10))
     
     # Calculate similarity score based on actual player selection
     portfolio['Diversity'] = calculate_player_similarity_score_chunked(portfolio, player_columns)