Since this approach reduces the error of the random forest model, it identifies all features that are either highly significant or unrelated ( 32 , 42 , 43 ).
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Identifying potential circulating miRNA biomarkers for the diagnosis and prediction of ovarian cancer using machine-learning approach: application of Boruta.
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