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Table 5 Accuracies for each individual class (bicarbonate, formaldehyde, peroxide, raw, starch, and sucrose) for multiclass classifications considering RF, GBM and CNN classifiers, in each of the selected training and test datasets: 90/10%, 75/25%, and 50/50%

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

Classifier Dataset Bicarbonate Formaldehyde Peroxide Raw Starch Sucrose
RF 90/10% 0.7804 0.7209 0.7916 0.9883 0.8048 0.9636
  75/25% 0.7540 0.6884 0.7524 0.9839 0.8099 0.8773
  50/50% 0.7634 0.6259 0.7847 0.9805 0.7444 0.8953
GBM 90/10% 0.7804 0.7441 0.7291 0.9766 0.7560 0.9272
  75/25% 0.8032 0.6739 0.7623 0.9759 0.7768 0.8867
  50/50% 0.7551 0.6259 0.7309 0.9780 0.7356 0.8870
CNN 90/10% 0.9756 0.9302 0.8958 0.9844 0.9024 0.9636
  75/25% 0.9918 0.9057 0.9108 0.9887 0.9421 1.0000
  50/50% 0.9958 0.9236 0.8340 0.9861 0.8854 0.9539