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Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification?
Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate decision support algorithms available for microarray gene e...
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| Hauptverfasser: | , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
American Medical Informatics Association
2007
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2655823/ https://ncbi.nlm.nih.gov/pubmed/18693924 |
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