Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily depen...

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Detalles Bibliográficos
Autores principales: Adeli, Ehsan, Wu, Guorong, Saghafi, Behrouz, An, Le, Shi, Feng, Shen, Dinggang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264393/
https://www.ncbi.nlm.nih.gov/pubmed/28120883
http://dx.doi.org/10.1038/srep41069

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264393/
https://www.ncbi.nlm.nih.gov/pubmed/28120883
http://dx.doi.org/10.1038/srep41069

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