An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

<p>Abstract</p> <p>Background</p> <p>As computational power improves, the application of more advanced machine learning techniques to the analysis of large genome-wide association (GWA) datasets becomes possible. While most traditional statistical methods can only eluci...

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Bibliographic Details
Main Authors: Hubbard Alan E, Goldstein Benjamin A, Cutler Adele, Barcellos Lisa F
Format: Article
Language:English
Published: BMC 2010-06-01
Series:BMC Genetics
Online Access:http://www.biomedcentral.com/1471-2156/11/49

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