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. 2022 Mar 24;2022:4795535. doi: 10.1155/2022/4795535

Table 4.

The performances of Reduced-KELM and Relief-F.

Data Model Accuracy (%) Difference SD Time Sensitivity Specificity Precision
German Reduced-KELM 71.53 8.74% 0.06 0.0013 0.5790 0.4962 0.5175
Relief-F 80.27 0.03 0.0012 0.5164 0.5108 0.5068

Image Reduced-KELM 85.70 0.16% 0.03 0.0086 0.8623 0.8510 0.8555
Relief-F 85.86 0.02 0.0063 0.8340 0.8780 0.8815

Ringnorm Reduced-KELM 60.06 0.85% 0.02 0.1128 0.5961 0.6079 0.7786
Relief-F 60.91 0.01 0.1031 0.6135 0.6075 0.7786

Twonorm Reduced-KELM 94.10 -1.65% 0.01 0.1022 0.9401 0.9377 0.9115
Relief-F 92.45 0.01 0.0934 0.9245 0.9216 0.8853

Waveform Reduced-KELM 84.29 0.93% 0.01 0.0474 0.8324 0.8090 0.8148
Relief-F 85.22 0.01 0.0384 0.8169 0.8223 0.8160

HAPT Reduced-KELM 88.52 0.95% 0.08 0.4155 0.9580 0.9434 0.8731
Relief-F 89.47 0.07 0.3753 0.9552 0.8936 0.7479

HARUS Reduced-KELM 84.02 5.66% 0.07 0.3826 0.9470 0.9419 0.8643
Relief-F 89.68 0.06 0.3589 0.9410 0.8851 0.7623

Smartphone Reduced-KELM 85.52 1.03% 0.07 0.1261 0.7749 0.7535 0.7280
Relief-F 86.55 0.07 0.0951 0.7869 0.7926 0.7532