In the AdaBoost Algorithm 9.10, assume we have learned a base model fmx at step m that performs worse than random guessing (i.e., its error

In the AdaBoost Algorithm 9.10, assume we have learned a base model fm¹xº at step m that performs worse than random guessing (i.e., its error m > 1 2 ). If we simply flip it to ¯ fm¹xº = ???? fm¹xº, compute the error for ¯ fm¹xº and its optimal ensemble weight. Show that it is equivalent to use either fm¹xº or ¯ fm¹xº in AdaBoost.