Most machine learning classes and textbooks mention that there is no universal supervised learning algorithm that can do reasonably well on all learning problems. Indeed, a series of “no free lunch theorems” state that even in a simple input space, for any learning algorithm, there always exists a bad conditional distribution of outputs given inputs…