Table 4.

Majority vote classification accuracies for individual features. Features are ordered by LDA classification accuracy. The best classifier result for each feature is in bold.

Feature	Classification Accuracy (%)			Feature	Classification Accuracy (%)
	LDA	SVM	RF		LDA	SVM	RF
MFL	76.54	73.45	59.88	MMAV1	64.81	54.94	62.35
MYOP	74.69	66.67	58.64	HFD	64.20	62.35	59.88
MSD	74.69	54.94	55.56	MAVS	64.20	50.00	56.17
AR4	74.07	59.88	50.00	PKF	63.58	67.9	61.11
MSF	72.84	72.84	54.94	MAV	63.58	55.60	64.81
MNPPS	70.99	64.20	52.47	MSA	63.58	53.70	62.35
PSR	70.99	66.67	56.17	MTW	62.96	50.62	64.20
ApEn	69.14	65.43	57.41	RMS	62.35	57.41	65.43
LOG	69.14	57.41	63.58	MHW	61.73	51.85	62.34
MNF	69.14	68.52	54.32	SM3	60.49	61.73	60.49
ZC	68.52	62.35	55.56	MNP	59.88	52.47	63.58
DASDV	68.52	51.85	61.73	TTP	58.79	51.85	64.20
VCF	68.52	57.41	56.17	VAR	58.64	52.47	64.20
AAC	67.90	51.85	59.88	FR	58.02	67.90	58.02
MSS	67.90	51.85	56.17	SM1	58.02	51.85	61.11
MMAV2	67.38	54.32	61.73	SKEW	57.41	53.09	50.00
WL	66.05	51.85	56.17	DFA	56.80	46.30	50.00
CC4	66.05	51.23	50.62	SM2	55.56	56.79	59.23
MDF	65.43	65.43	56.79	WAMP	54.32	56.17	50.62
SampleEn	65.43	64.81	56.17	KURT	52.47	53.70	50.00
SSC	64.81	61.73	51.85