Q3. [2 points] In a binary classification problem, assume we have a classifier R that guesses randomly (50/50 positiveegative). For data that has 70% positive and 30% negative instances, show that gets 50% error. Q4. a. [3 points] Change Algorithm 1 (in chapter 1 page 13) in the textbook to take a maximum depth parameter d. b. [1 point] Do we also need to change Algorithm 2 (page 3)? Why