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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...

詳細記述

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書誌詳細
主要な著者: Statnikov, Alexander, Aliferis, Constantin F.
フォーマット: Artigo
言語:Inglês
出版事項: American Medical Informatics Association 2007
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC2655823/
https://ncbi.nlm.nih.gov/pubmed/18693924
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