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Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data
PURPOSE: It is common that a trained classification model is applied to the operating data that is deviated from the training data because of noise. This paper will test an ensemble method, Diversified Multiple Tree (DMT), on its capability for classifying instances in a new laboratory using the cla...
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| Publicado en: | Health Inf Sci Syst |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Springer International Publishing
2017
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5634968/ https://ncbi.nlm.nih.gov/pubmed/29062476 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s13755-017-0025-x |
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