Table 4 The result of a repeated 10-fold cross-validation experiment using naive Bayes, support vector machine (SVM), and C4.5 decision tree with the hybrid feature selection approach that combines the chi-squared and information-gain methods.

Naive Bayes

0.70 ± 0.16

0.65 ± 0.21

0.60 ± 0.20

12

SVM with linear kernel

0.67 ± 0.13

0.62 ± 0.20

0.73 ± 0.19

14

SVM with polynomial kernel

0.62 ± 0.13

0.56 ± 0.21

0.68 ± 0.18

9

SVM with sigmoid kernel

0.64 ± 0.13

0.62 ± 0.20

0.67 ± 0.19

4

SVM with Gaussian radial basis function kernel

0.64 ± 0.13

0.58 ± 0.20

0.71 ± 0.18

3

C4.5 decision tree

0.64 ± 0.13

0.80 ± 0.16

0.46 ± 0.20

2