Semi‐supervised empirical Bayes group‐regularized factor regression

The features in a high‐dimensional biomedical prediction problem are often well described by low‐dimensional latent variables (or factors). We use this to include unlabeled features and additional information on the features when building a prediction model. Such additional feature information is of...

Descripción completa

Detalles Bibliográficos
Autores principales: Münch, Magnus M., van de Wiel, Mark A., van der Vaart, Aad W., Peeters, Carel F. W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Statistical Modeling
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9796498/
https://www.ncbi.nlm.nih.gov/pubmed/35730912
http://dx.doi.org/10.1002/bimj.202100105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9796498/
https://www.ncbi.nlm.nih.gov/pubmed/35730912
http://dx.doi.org/10.1002/bimj.202100105

Ejemplares similares