Table 6 Multi-condition (MC) classification results of different algorithms with e-scaled weight ensemble learning (-e) at the second-stage TsEL (unit: %)

DNN

94.70

95.80

92.10

87.70

92.58

ELM

93.91 ± 0.71

94.34 ± 0.61

93.90 ± 0.86

91.51 ± 0.91

93.42 ± 0.77

ELM-AE

94.50 ± 1.04

94.48 ± 1.04

94.50 ± 0.77

93.68 ± 0.94

94.29 ± 0.95

B-ELM-AE

96.95 ± 0.66

96.50 ± 0.46

96.48 ± 0.58

95.45 ± 0.53

96.35 ± 0.56

MC-ELM-AE-C

95.60 ± 0.94

95.53 ± 0.67

95.83 ± 0.61

94.58 ± 0.90

95.39 ± 0.78

MC-ELM-AE-TsEL-V

95.28 ± 0.69

95.23 ± 0.43

95.55 ± 0.79

94.40 ± 0.92

95.11 ± 0.71

MC-ELM-AE-TsEL-W

96.13 ± 0.61

96.38 ± 0.64

96.50 ± 0.63

95.35 ± 0.66

96.09 ± 0.64

B-MC-ELM-AE-C

96.53 ± 0.49

96.33 ± 0.62

96.43 ± 0.53

95.68 ± 0.77

96.24 ± 0.60

B-MC-ELM-AE-TsEL-V

96.73 ± 0.63

96.73 ± 0.46

96.53 ± 0.83

95.60 ± 0.58

96.39 ± 0.62

B-MC-ELM-AE-TsEL-W

97.43 ± 0.65

97.35 ± 0.43

97.20 ± 0.78

96.40 ± 0.36

97.10 ± 0.56