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Random forest for evaluation of the importance of the study variables in the prediction of BA. RF classification algorithm using RF package with 500 regression tree was constructed for the prediction of BA using the five variables (gender, weight, DB, ln(ALP), and ln(GGT)), in time lags with more than five steps were trained. The importance of each variable was subsequently evaluated in RF.
