Model Selection Principles

Occam’s Razor: when two models explain the data equally well, prefer the simpler one. Simplicity helps avoid overfitting and makes results easier to interpret.

“All models are wrong, but some are useful” (George Box): every model is a simplification of reality, so perfection is impossible; the goal is to pick a model that is useful for the task at hand.