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Table 4 Performance evaluation of the algorithms applied to ‘Wine quality_red’ dataset

From: Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications

Algorithm Accuracy Sensitivity
(Class ‘3’)
Sensitivity
(Class ‘5’)
Specificity
(Class ‘3’)
Running time (s) Memory usage (M)
C4.5 0.9099 0.8000 0.9266 0.9956 0.15 0.02
SVM 0.6717 0 0.8062 1.0000 0.79 0.53
AdaBoost 0.6629 0 0.7871 1.0000 34.02 11.33
kNN 0.8705 0.7000 0.9178 1.0000 0.11 0.39
Naïve Bayes 0.5604 0.3000 0.6696 0.9975 0.00 0.01
Random forest 1.0000 1.0000 1.0000 1.0000 1.42 10.33
Logistic regression 0.6079 0.2000 0.7518 0.9981 0.23 0.34