Improved shrunken centroid classifiers for high-dimensional class-imbalanced data

BACKGROUND: PAM, a nearest shrunken centroid method (NSC), is a popular classification method for high-dimensional data. ALP and AHP are NSC algorithms that were proposed to improve upon PAM. The NSC methods base their classification rules on shrunken centroids; in practice the amount of shrinkage i...

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Detalles Bibliográficos
Autores principales: Blagus, Rok, Lusa, Lara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3687811/
https://www.ncbi.nlm.nih.gov/pubmed/23433084
http://dx.doi.org/10.1186/1471-2105-14-64

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3687811/
https://www.ncbi.nlm.nih.gov/pubmed/23433084
http://dx.doi.org/10.1186/1471-2105-14-64

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