Classic regression's potential for intelligibility relies on the modeler choosing terms which are based on observed relations and improve performance. For examp

Classic regression's potential for intelligibility relies on the modeler choosing terms which are based on observed relations and improve performance. For example, population forecasts can be modeled as the current population plus forecasted changes through immigration, emigration, birth, and death. Yes, somebody can produce "magical" regression models with terms divorced from reality. But unsupervised learning is never guaranteed to produce a reality-grounded model, no matter the user's skill. It goes through steps, tries different transformations, and chooses the algorithm which led to the best result. Logic and understanding played no part. That sounds like alchemy. It definitely works, but alchemy also stumbled onto theories later explained by chemistry. And, yes, anyone who doesn't consider the implications of the linear model behind ANOVA would also be a "magician."