Research Article
[Retracted] An Effective Approach for Human Activity Classification Using Feature Fusion and Machine Learning Methods
Table 8
Classification results of experiment 5.
| Weizmann | KTH | Method | (%) | (%) | (%) | (%) | (%) | (%) | (%) | (%) |
| Linear-SVM | 80.0 | 96.68 | 90.0 | 87.5 | 50.83 | 95.49 | 57.16 | 80.2 | Cubic-SVM | 80.0 | 96.20 | 90.31 | 86.3 | 50.42 | 95.37 | 55.03 | 79.5 | Complex tree | 85.32 | 97.8 | 85.31 | 88.4 | 98.49 | 99.69 | 97.93 | 98.6 | Fine-KNN | 33.42 | 84.1 | 87.63 | 46.7 | 39.47 | 93.6 | 84.92 | 57.6 | Subspace-KNN | 88.72 | 97.96 | 90.81 | 92.0 | 99.97 | 99.99 | 99.95 | 99.9 |
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