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Nested cross-validation (nCV) is a common approach that chooses the classification model and features to represent a given outer fold based on features that give the maximum inner-fold accuracy.
May 1, 2020 · We develop consensus nested cross-validation (cnCV) that combines the idea of feature stability from differential privacy with nCV.
We develop consensus nested CV (cnCV) that combines the idea of feature stability from differential privacy with nested CV.
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What is nested cross-validation?
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Can you use cross-validation for feature selection?
Jan 2, 2020 · Nested cross-validation (nCV) is a common approach that chooses the classification model and features to represent a given outer fold based on ...
Abstract<jats:sec>SummaryFeature selection can improve the accuracy of machine-learning models, but appropriate steps must be taken to avoid overfitting.
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Feb 27, 2022 · Nested cross validation can indeed include feature selection. It is similar to preprocessing as you have mentioned.
Modified consensus nested cross-validation (cnCV) implemented for feature selection and hyperparameter tuning. Features are selected in the inner loops, ...
Consensus nested cross validation for feature selection and parameter tuning · Description · Usage · Arguments · Value · See Also. Other nestedCV: ...
Aug 3, 2020 · Consensus features (found in all folds) are used as the best features in the corresponding outer fold. For example, features 'EFG' are shared ...
Jan 2, 2020 · bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution.