Performance is not enough: the story told by a Rashomon quartet

arXiv:2302.13356v4 Announce Type: replace-cross
Abstract: The usual goal of supervised learning is to find the best model, the one that optimizes a particular performance measure. However, what if the explanation provided by this model is completely different from another model and different again from another model despite all having similarly good fit statistics? Is it possible that the equally effective models put the spotlight on different relationships in the data? Inspired by Anscombe's quartet, this paper introduces a Rashomon Quartet, …

abstract arxiv cs.lg however performance quartet stat.ap stat.ml story supervised learning type