Research Article
Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and k-Nearest Neighbor
Table 3
Average recognition rates for each of
, , and
.
| Dataset | Classifier | Average recognition rate (%) | | | |
| BIDMC | k-NN | 99.88 | 99.88 | 100.0 | RF | 96.94 | 97.29 | 95.59 | LDC | 97.54 | 97.15 | 94.45 | NB | 98.20 | 96.89 | 90.96 |
| MIMIC | k-NN | 95.75 | 96.31 | 98.47 | RF | 88.97 | 92.91 | 89.31 | LDC | 92.31 | 91.41 | 91.25 | NB | 96.54 | 97.03 | 96.13 |
| CapnoBase | k-NN | 99.79 | 99.60 | 99.95 | RF | 97.60 | 98.67 | 96.12 | LDC | 98.15 | 97.79 | 94.93 | NB | 99.81 | 99.76 | 99.05 |
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