Update app.py

app.py

@@ -23,6 +23,7 @@ def homework01_solution1(K, X1, X2):
   neigh = KNeighborsRegressor(n_neighbors=K)
   neigh.fit(X, y)
   predicted_label = neigh.predict(np.array([[X1, X2]]))[0]
+  predicted_label = np.round(predicted_label, 3)
 
   #(Q) calculate squared error
   pred = neigh.predict(X)
@@ -31,7 +32,7 @@ def homework01_solution1(K, X1, X2):
   #(Q2.3) evaluate mean squared error 
   import sklearn
   y_pred = neigh.predict(X)
-  mse = sklearn.metrics.mean_squared_error(y,y_pred)
+  mse = np.round(sklearn.metrics.mean_squared_error(y,y_pred),3)
 
 
   train_data['Predicted Label ('+str(K)+'-NN)'] = pred