A Quantitative Comparison between Shannon and Tsallis–Havrda–Charvat Entropies Applied to Cancer Outcome Prediction

In this paper, we propose to quantitatively compare loss functions based on parameterized Tsallis–Havrda–Charvat entropy and classical Shannon entropy for the training of a deep network in the case of small datasets which are usually encountered in medical applications. Shannon cross-entropy is wide...

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Detalles Bibliográficos
Autores principales: Brochet, Thibaud, Lapuyade-Lahorgue, Jérôme, Huat, Alexandre, Thureau, Sébastien, Pasquier, David, Gardin, Isabelle, Modzelewski, Romain, Gibon, David, Thariat, Juliette, Grégoire, Vincent, Vera, Pierre, Ruan, Su
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9031340/
https://www.ncbi.nlm.nih.gov/pubmed/35455101
http://dx.doi.org/10.3390/e24040436

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9031340/
https://www.ncbi.nlm.nih.gov/pubmed/35455101
http://dx.doi.org/10.3390/e24040436

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