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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| 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 |