New perspectives in cross-validation
Appealing due to its universality, cross-validation is an ubiquitous tool for model tuning and selection. At its core, cross-validation proposes to split the data (potentially several times), and alternatively use some of the data for fitting a model and the rest for testing the model. This produces...
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| Language: | English |
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2020
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| Online Access: | https://doi.org/10.7916/d8-3z39-7v31 |