A relation between log-likelihood and cross-validation log-scores
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Abstract (arXiv)
It is shown that the log-likelihood of a hypothesis or model given some data is equivalent to an average of all leave-one-out cross-validation log-scores that can be calculated from all subsets of the data. This relation can be generalized to any k-fold cross-validation log-scores.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 23 Aug 2019.
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