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Composite large margin classifiers with latent subclasses for heterogeneous biomedical data
High dimensional classification problems are prevalent in a wide range of modern scientific applications. Despite a large number of candidate classification techniques available to use, practitioners often face a dilemma of choosing between linear and general nonlinear classifiers. Specifically, sim...
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| Publicado en: | Stat Anal Data Min |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2016
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4912001/ https://ncbi.nlm.nih.gov/pubmed/27326311 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sam.11300 |
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