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Table 4 Accuracy from evaluated classifiers (RF, GBM, and CNN) for binary and multiclass classifications

From: On the utilization of deep and ensemble learning to detect milk adulteration

Dataset Classification RF GBM CNN
90/10% Multiclass 0.9093 0.8907 0.9608
  Binary 0.9856 0.9711 0.9794
75/25% Multiclass 0.8812 0.8787 0.9695
  Binary 0.9744 0.9686 0.9876
50/50% Multiclass 0.8700 0.8609 0.9538
  Binary 0.9736 0.9653 0.9546
  1. All classifiers were evaluated with 3 pairs of training and test datasets randomly selected from our milk samples, identified by their proportion of training and test samples