Update app.py

app.py

@@ -242,8 +242,8 @@ def bootstrap_stats(predicted_target, num_samples=1000):
         bootstrapped_means.append(np.mean(bootstrap_sample))
 
     # Calculate lower and higher bounds
-    lower_bound = np.percentile(bootstrapped_means, 2.5)
-    higher_bound = np.percentile(bootstrapped_means, 97.5)
+    lower_bound = np.percentile(bootstrapped_means, 15.)
+    higher_bound = np.percentile(bootstrapped_means, 85.)
 
     # Calculate the mean value
     mean_value = np.mean(bootstrapped_means)