Fair classification by loss balancing via fairness-aware batch sampling

•We disclosed that only balancing the sample size cannot ensure fairness.•We propose a resampling method that dynamically minimizes the loss discrepancy between groups.•We introduce a new metric to evaluate the trade-off performance between fairness and accuracy.•It achieves the best trade-off performances between fairness and accuracy in various settings.