Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Aki Vehtari, Andrew Gelman, Jonah Gabry
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Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC presents a bayesian probability approach for cross-validation.
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Evidence disclosure
Evidence graph: 2 refs, 1 links.
Utility signals: depth 65/100, grounding 58/100, status medium.
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Research context
5,327
Citations
49
References
Tasks
Cross-validation, Computer science, Data mining, Econometrics, Statistics and Probability, Physical Sciences
Methods
Bayesian probability, Model validation, Variable-order Bayesian network, Bayesian inference
Domains
Artificial intelligence, Machine learning, Mathematics
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