Optimizing things: everything is a proxy for a proxy for a proxy

from blog Home on Erik Bernhardsson, | ↗ original
Say you build a machine learning model, like a movie recommender system. You need to optimize for something. You have 1-5 stars as ratings so let's optimize for mean squared error. Great. Then let's say you build a new model.