Table 3.
Recognition performance on the Accelerometer dataset.
| Model | NB | NB-NB | NB-KNN | NB-SVM | NB-DT | KNN | KNN-NB | KNN-KNN | KNN-SVM | KNN-DT |
| Accuracy | 81.07 | 81.07 | 83.98 | 91.48 | 84.56 | 84.32 | 81.41 | 84.32 | 91.89 | 85.04 |
| Precision | 80.38 | 80.38 | 83.72 | 91.50 | 84.29 | 84.03 | 80.70 | 84.03 | 91.88 | 84.73 |
| Recall | 82.63 | 82.63 | 84.19 | 91.72 | 84.58 | 84.55 | 82.85 | 84.55 | 92.16 | 85.08 |
| F1 | 81.49 | 81.49 | 83.95 | 91.61 | 84.44 | 84.29 | 81.76 | 84.29 | 92.02 | 84.90 |
| Model | SVM | SVM-NB | SVM-KNN | SVM-SVM | SVM-DT | DT | DT-NB | DT-KNN | DT-SVM | DT-DT |
| Accuracy | 91.89 | 81.34 | 84.32 | 91.89 | 84.97 | 84.93 | 81.57 | 84.32 | 91.96 | 85.14 |
| Precision | 91.87 | 80.64 | 84.03 | 91.88 | 84.67 | 84.63 | 80.87 | 84.03 | 91.95 | 84.82 |
| Recall | 92.16 | 82.77 | 84.55 | 92.16 | 85.01 | 84.99 | 83.03 | 84.58 | 92.24 | 85.19 |
| F1 | 92.02 | 81.69 | 84.29 | 92.02 | 84.84 | 84.81 | 81.94 | 84.30 | 92.09 | 85.01 |