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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2010-06-01
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| Series: | BMC Genetics |
| Online Access: | http://www.biomedcentral.com/1471-2156/11/49 |