Autoencoders for sample size estimation for fully connected neural network classifiers

Sample size estimation is a crucial step in experimental design but is understudied in the context of deep learning. Currently, estimating the quantity of labeled data needed to train a classifier to a desired performance, is largely based on prior experience with similar models and problems or on u...

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Detalles Bibliográficos
Autores principales: Gulamali, Faris F., Sawant, Ashwin S., Kovatch, Patricia, Glicksberg, Benjamin, Charney, Alexander, Nadkarni, Girish N., Oermann, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747810/
https://www.ncbi.nlm.nih.gov/pubmed/36513729
http://dx.doi.org/10.1038/s41746-022-00728-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747810/
https://www.ncbi.nlm.nih.gov/pubmed/36513729
http://dx.doi.org/10.1038/s41746-022-00728-0

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