Additionally, relevant features associated with a biological condition can be identified using feature selection methods, such
as random forest or iterative linear regression.
Feature selection methods are based on the premise that data frequently contains
many features that are either redundant or irrelevant, and can thus be removed
without incurring much loss of information. Feature selection algorithms identify
new feature subsets that best predict an outcome of interest (in this case a factor
defined in the meta annotation file).
In a nutshell
Select feature selection method
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