Support Vector Machine Implementations for Classification & Clustering

BACKGROUND: We describe Support Vector Machine (SVM) applications to classification and clustering of channel current data. SVMs are variational-calculus based methods that are constrained to have structural risk minimization (SRM), i.e., they provide noise tolerant solutions for pattern recognition...

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Detalles Bibliográficos
Autores principales: Winters-Hilt, Stephen, Yelundur, Anil, McChesney, Charlie, Landry, Matthew
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1683575/
https://www.ncbi.nlm.nih.gov/pubmed/17118147
http://dx.doi.org/10.1186/1471-2105-7-S2-S4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1683575/
https://www.ncbi.nlm.nih.gov/pubmed/17118147
http://dx.doi.org/10.1186/1471-2105-7-S2-S4

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