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Feature Selection

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

  1. Select feature selection method
  2. Press "Run Analysis"