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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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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2013
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3687811/ https://ncbi.nlm.nih.gov/pubmed/23433084 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-64 |
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