Cargando…
A3SOM, abstained explainable semi-supervised neural network based on self-organizing map
In the sea of data generated daily, unlabeled samples greatly outnumber labeled ones. This is due to the fact that, in many application areas, labels are scarce or hard to obtain. In addition, unlabeled samples might belong to new classes that are not available in the label set associated with data....
Autores principales: | Creux, Constance, Zehraoui, Farida, Hanczar, Blaise, Tahi, Fariza |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212082/ https://www.ncbi.nlm.nih.gov/pubmed/37228138 http://dx.doi.org/10.1371/journal.pone.0286137 |
Ejemplares similares
-
IRSOM, a reliable identifier of ncRNAs based on supervised self-organizing maps with rejection
por: Platon, Ludovic, et al.
Publicado: (2018) -
Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data
por: Bourgeais, Victoria, et al.
Publicado: (2021) -
Biological interpretation of deep neural network for phenotype prediction based on gene expression
por: Hanczar, Blaise, et al.
Publicado: (2020) -
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data
por: Hanczar, Blaise, et al.
Publicado: (2022) -
IRSOM2: a web server for predicting bifunctional RNAs
por: Postic, Guillaume, et al.
Publicado: (2023)