A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection

Table 8

Values of TP, TN, FP, FN, and MSE for Haar, dB4, and Sym 8 wavelet features in various classifiers with feature selection.

Wavelets	Classifiers	TP	TN	FP	FN	MSE
Haar	Linear regression	52	61	39	48	0.000212
	Nonlinear regression	64	55	45	36	0.00011
	GMM	51	74	26	49	0.000231
	K-NN	55	87	13	45	8.67E − 05
	SVM (linear)	56	53	47	44	0.0002
	SVM (polynomial)	82	80	20	18	1.23E − 05
	SVM (RBF)	85	89	11	15	3.48E − 06
dB4	Linear regression	71	81	19	29	2.12E − 05
	Nonlinear regression	72	77	23	28	2.23E − 05
	GMM	55	78	22	45	0.000106
	K-NN	87	82	18	13	7.44E − 06
	SVM (linear)	66	76	24	34	3.21E − 05
	SVM (polynomial)	63	66	34	37	4.9E − 05
	SVM (RBF)	63	93	7	37	1.96E − 05
Sym8	Linear regression	59	89	11	41	3.64E − 05
	Nonlinear regression	57	52	48	43	0.000233
	GMM	64	51	49	36	0.00029
	K-NN	54	52	48	46	0.000336
	SVM (linear)	53	56	44	47	0.000191
	SVM (polynomial)	55	59	41	45	0.000126
	SVM (RBF)	98	98	2	2	1.96E − 06