Table 5.

Evaluation metrics result obtained on prediction of multiclass problems.

Classes	Number of features	Classifier	Accuracy (%)	Precision	Recall	F1-score
A–E	50	RF	100	1.0	1.0	1.0
B–E	100	RF	100	1.0	1.0	1.0
AB–CD–E	700	Bagged k-NN	99	0.99	0.99	0.99
AB–C–D–E	1000	LR	94.4	0.95	0.94	0.94
A–B–C–D–E	3367	SVM	93.6	0.94	0.94	0.94
Ictal vs. Preictal	500	Ensemble	97.1	0.97	0.97	0.97