Table 2. The classification accuracy of the implemented machine learning-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
LDA	95.8	82.8	36.3	66.7	61.93 ± 23.61	67.9	68.2	70.6	69.4	65.2	68.26 ± 2.01	93.6	87.1	90.8	81.4	61.4	64.1	56.3	86.2	82.2	78.12 ± 13.81
Naïve Bayes	97.1	91.1	73.3	94.2	86.20 ± 11.27	89.3	73.9	82.9	78.2	76.6	80.18 ± 6.05	90.2	85.6	89.1	83.2	58.4	60.2	47.4	88.4	79.6	75.78 ± 16.05
SVM	98.1	91.4	57.5	82.1	77 ± 17.51	93.6	90.4	88.4	89.4	86.4	89.64 ± 2.66	96.8	91.2	93.4	88.4	64.6	78.6	62.4	90.6	84.2	83.35 ± 12.42
k-NN	97.5	88.1	57.9	86.3	77.43 ± 16.94	89.6	88.6	86.8	90.2	87.6	88.56 ± 1.39	92.6	88.4	90.1	81.4	69.4	70.1	59.1	79.8	77.1	78.66 ± 11.02
RF	96.4	86.4	76.3	83.8	82.16 ± 5.24	91.8	92.2	89.4	88.6	86.2	89.64 ± 2.45	89.2	90.2	92.6	88.1	60.8	59.6	59.8	88.2	79.6	78.67 ± 14.39
ERS- k-NN	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