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...

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Detalles Bibliográficos
Autores principales: Tabe-Bordbar, Shayan, Emad, Amin, Zhao, Sihai Dave, Sinha, Saurabh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920056/
https://www.ncbi.nlm.nih.gov/pubmed/29700343
http://dx.doi.org/10.1038/s41598-018-24937-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920056/
https://www.ncbi.nlm.nih.gov/pubmed/29700343
http://dx.doi.org/10.1038/s41598-018-24937-4

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