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On the Existence of Simpler Machine Learning Models. (arXiv:1908.01755v4 [cs.LG] UPDATED)
May 16, 2022, 1:11 a.m. | Lesia Semenova, Cynthia Rudin, Ronald Parr
cs.LG updates on arXiv.org arxiv.org
It is almost always easier to find an accurate-but-complex model than an
accurate-yet-simple model. Finding optimal, sparse, accurate models of various
forms (linear models with integer coefficients, decision sets, rule lists,
decision trees) is generally NP-hard. We often do not know whether the search
for a simpler model will be worthwhile, and thus we do not go to the trouble of
searching for one. In this work, we ask an important practical question: can
accurate-yet-simple models be proven to exist, …
arxiv learning machine machine learning machine learning models
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