Update my_pages/multiverse.py

my_pages/multiverse.py

@@ -301,11 +301,17 @@ def render():
     all_preds_numpy = np.load("all_predictions.npy")
 
     prop_ones = np.mean(all_preds_numpy == 1, axis=0)
-    condition = (y_pred == 0) & (prop_ones > 0.5)
-    uniq_perc = 100 * np.sum(condition) / len(y_pred)
+    condition_rej = (y_pred == 0) & (prop_ones > 0.5)
+    # uniq_perc = 100 * np.sum(condition) / len(y_pred)
+    uniq_count_rej = np.sum(condition_rej)
+
+    
+    condition_acc = (y_pred == 1) & (prop_ones < 0.5)
+    uniq_count_acc = np.sum(condition_acc)
     
     add_red_text(f"""
-        <b>Multiplicity of your predictions:</b> Your chosen model rejected {uniq_perc}% loans that would have been accepted by more than 80% of the other models.<br><br>
+        <b>Multiplicity of your predictions:</b> Your chosen model rejected {uniq_count_rej} loans that would have been accepted by the majority of the other models.
+        Similariy, your chosen model accepted {uniq_count_acc} loans that would have been rejected by the majority of the other models.<br><br>
         You might want higher multiplicity, to avoid competiting for the same loan applicants with others and to give a chance to unique applicants.<br><br>
         On the other hand, you might instead want lower multiplicity, to take lower risks and to avoid facing a justification crisis, i.e., 
         not able to explain why you rejected certain applicants when they were accepted by everyone else.<br><br>