Development of Supervised Learning Predictive Models for Highly Non-linear Biological, Biomedical, and General Datasets

In highly non-linear datasets, attributes or features do not allow readily finding visual patterns for identifying common underlying behaviors. Therefore, it is not possible to achieve classification or regression using linear or mildly non-linear hyperspace partition functions. Hence, supervised le...

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Detalles Bibliográficos
Autores principales: Medina-Ortiz, David, Contreras, Sebastián, Quiroz, Cristofer, Olivera-Nappa, Álvaro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Molecular Biosciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7031350/
https://www.ncbi.nlm.nih.gov/pubmed/32118039
http://dx.doi.org/10.3389/fmolb.2020.00013

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7031350/
https://www.ncbi.nlm.nih.gov/pubmed/32118039
http://dx.doi.org/10.3389/fmolb.2020.00013

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