TABLE 3.

Parameters and their ranges tested with support vector machine (SVM) algorithm on the dataset. Parameters in bold font are the ones that provided the highest classification accuracy

Kernels	linear, radial basis function, polynomial, sigmoid
SVM type	C – SVM, ν – SVM
Degree of polynomial function	3, 4, 5, 6, 7
C	2, 4, 10, 12, 16, 20 (N/A in ν–SVM)
Gamma (γ)	0.001, 0.003, 0.01, 0.03, 0.05, 0.1
Coefficient	0.01, 0.1, 1, 5, 10, 15, 20
Nu (ν)	0.2, 0.3, 0.4, 0.5
Normalization	Normalized and not normalized training set