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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
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BioData Mining

ISSN: 1756-0381