Monte Carlo cross-validation for a study with binary outcome and limited sample size
Abstract Cross-validation (CV) is a resampling approach to evaluate machine learning models when sample size is limited. The number of all possible combinations of folds for the training data, known as CV rounds, are often very small in leave-one-out CV. Alternatively, Monte Carlo cross-validation (...
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| Format: | Article |
| Language: | English |
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BMC
2022-10-01
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| Series: | BMC Medical Informatics and Decision Making |
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| Online Access: | https://doi.org/10.1186/s12911-022-02016-z |