Discriminative Learning Approach Based on Flexible Mixture Model for Medical Data Categorization and Recognition

In this paper, we propose a novel hybrid discriminative learning approach based on shifted-scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address some challenging problems of medical data categorization and recognition. The main goal is to capture accurately the intrins...

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Detalles Bibliográficos
Autores principales: Alharithi, Fahd, Almulihi, Ahmed, Bourouis, Sami, Alroobaea, Roobaea, Bouguila, Nizar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036303/
https://www.ncbi.nlm.nih.gov/pubmed/33918120
http://dx.doi.org/10.3390/s21072450

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036303/
https://www.ncbi.nlm.nih.gov/pubmed/33918120
http://dx.doi.org/10.3390/s21072450

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