Table 3 Performance results for machine learning algorithms using k-fold cross validation method.

From: Discrimination of secondary hypsarrhythmias to Zika virus congenital syndrome and west syndrome based on joint moments and entropy measurements

Classifier

Accuracy (%)

Sensitivity (%)

Specificity (%)

Kappa

MCC

ROC_AUC

Decision tree

74.42

71.05

77.79

0.4884

0.4895

0.80

Discriminant analysis

73.11

52.42

93.79

0.4621

0.5076

0.80

Gentle boost

79.26

76.95

81.58

0.5853

0.5859

0.88

k-nearest-neighbors

74.00

66.32

81.68

0.480

0.4858

0.83

Logistic regression

75.11

69.16

81.05

0.5021

0.5057

0.86

Naive Bayes

69.84

51.37

88.32

0.3968

0.4271

0.78

Artificial neural network

82.32

80.53

84.11

0.6463

0.6467

0.91

Support vector machine

81.05

76.42

85.68

0.6211

0.6237

0.91

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