Research Article
[Retracted] An Effective Approach for Human Activity Classification Using Feature Fusion and Machine Learning Methods
Table 6
Classification results of experiment 3 using the linear-SVM method and others.
| Weizmann | KTH | Method | (%) | (%) | (%) | (%) | (%) | (%) | (%) | (%) |
| Linear-SVM | 97.90 | 99.69 | 98.39 | 98.7 | 100 | 99.72 | 98.70 | 98.7 | Cubic-SVM | 97.86 | 99.67 | 98.544 | 98.7 | 91.51 | 99.21 | 96.39 | 96.5 | Complex tree | 85.43 | 97.212 | 85.53 | 88.6 | 98.34 | 99.69 | 97.93 | 98.5 | Fine-KNN | 63.7 | 91.63 | 90.79 | 71.9 | 95.30 | 99.32 | 98.02 | 97.0 | Subspace-KNN | 89.99 | 98.18 | 92.11 | 93.0 | 99.97 | 99.99 | 99.95 | 99.9 |
|
|