Algorithm Skill vs Complexity Frontier
A thought bouncing around in the back of my head related to machine learning algorithm selection is skill vs complexity. Typically we want the most simplest skillful model, i.e. Occam’s Razor. A way of thinking about this is to assign a complexity score to a suite of algorithms and then evaluate each in turn. From this table of data, we can imagine a frontier (or Pareto front) of skill vs complexity. Come to think of it, I probably got the idea from this AutoGluon slide: ...