An optimized multi-classifiers ensemble learning for identification of ginsengs based on electronic nose

•The framework proposes an optimized two-layer Adaboost.M2 ensemble model.•It utilizes the diversity among several classical classifiers with probabilistic forms.•Efficient algebraic fusion rules are employed for combining decisions from classifiers.•It contributes to a flexible tool for valid probabilistic prediction and online classification.