Table 3. Performance of ERS- k-NN based classification algorithms.

Metrics	Data-1	Data-2				Data-3						Data-4
		k3b	k6b	l1b	Mean ± SD	aa	al	av	aw	ay	Mean ± SD	A01	A02	A03	A04	A05	A06	A07	A08	A09	Mean ± SD
Accuracy (%)	99.21	98.33	83.33	97.92	93.19 ± 8.54	94.64	94.64	95.00	93.21	90.36	93.57 ± 1.9	98.96	97.57	97.57	93.75	80.21	88.54	71.18	94.79	90.28	90.32 ± 9.24
Sensitivity (%)	99.47	98.33	83.33	97.92	93.19 ± 8.54	92.14	90.00	95.71	90.00	90.71	91.71 ± 2.39	98.96	97.57	97.57	93.75	80.21	88.54	71.18	94.79	90.28	90.32 ± 9.24
Specificity (%)	98.94	99.44	94.44	99.31	97.73 ± 2.85	97.14	99.29	94.29	96.43	90.00	95.43 ± 3.52	99.65	99.19	99.19	97.92	93.40	96.18	90.39	98.26	96.76	96.77 ± 3.08
FPR (%)	1.06	0.56	5.56	0.69	2.27 ± 2.85	2.86	0.71	5.71	3.57	0.10	2.59 ± 2.26	0.35	0.81	0.81	2.08	6.60	3.82	9.61	1.74	3.24	3.22 ± 3.08
Error Rate (%)	0.79	1.67	16.67	2.08	6.81 ± 8.54	5.36	5.36	5.00	6.79	9.64	6.43 ± 1.92	1.04	2.43	2.43	6.25	19.79	11.46	28.82	5.21	9.72	9.68 ± 9.24
Kappa	0.98	0.95	0.55	0.94	0.81 ± 0.23	0.89	0.89	0.90	0.86	0.81	0.87 ± 0.03	0.97	0.93	0.93	0.83	0.47	0.69	0.23	0.86	0.74	0.73 ± 0.24
Precision	0.98	0.98	0.84	0.97	0.93 ± 0.07	0.96	0.99	0.94	0.96	0.90	0.95 ± 0.03	0.98	0.97	0.97	0.93	0.81	0.88	0.71	0.95	0.90	0.90 ± 0.08
F1-Score	0.99	0.98	0.83	0.97	0.93 ± 0.08	0.94	0.94	0.95	0.93	0.90	0.93 ± 0.01	0.98	0.97	0.97	0.93	0.80	0.88	0.71	0.95	0.90	0.89 ± 0.09
MCC	0.98	0.97	0.78	0.97	0.91 ± 0.11	0.89	0.89	0.90	0.87	0.81	0.87 ± 0.03	0.98	0.96	0.96	0.91	0.74	0.85	0.61	0.93	0.87	0.86 ± 0.12
AUC	0.99	0.99	0.96	0.99	0.98 ± 0.01	0.98	0.98	0.99	0.98	0.97	0.98 ± 0.007	0.99	0.99	0.99	0.99	0.90	0.99	0.87	0.99	0.99	0.96 ± 0.04
Time (S)	2.53	1.40	1.35	1.41	1.39 ± 0.03	3.26	3.12	3.08	3.07	2.66	3.04 ± 0.22	3.38	2.78	3.25	2.78	2.79	2.80	2.78	2.78	2.78	2.89 ± 0.22