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title:(Leave-One-Out AND Cross-Validation AND for AND Bayesian AND Model AND Comparison AND in AND Large AND Data)

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1 Book chapter

Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data

Recently, new methods for model assessment, based on subsampling and posterior approximations, have been proposed for scaling leave-one-out cross-validation (LOO) to large datasets. Although these methods work well for estimating predictive performance for individual models, they are less powerful

Year: 2020

Language: English

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2 Preprint article

Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data

Recently, new methods for model assessment, based on subsampling and posterior approximations, have been proposed for scaling leave-one-out cross-validation (LOO) to large datasets. Although these methods work well for estimating predictive performance for individual models, they are less powerful

Year: 2020

Language: Undetermined

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