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A closer look at cross-validation for assessing the accuracy of gene regulatory networks and models
Cross-validation (CV) is a technique to assess the generalizability of a model to unseen data. This technique relies on assumptions that may not be satisfied when studying genomics datasets. For example, random CV (RCV) assumes that a randomly selected set of samples, the test set, well represents u...
Enregistré dans:
| Publié dans: | Sci Rep |
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| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Publishing Group UK
2018
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5920056/ https://ncbi.nlm.nih.gov/pubmed/29700343 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-018-24937-4 |
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