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An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
BACKGROUND: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal in any given classification application. In addition, for most classification problems, selecting the best performing cla...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2933716/ https://www.ncbi.nlm.nih.gov/pubmed/20716381 http://dx.doi.org/10.1186/1471-2105-11-427 |