Research Article
[Retracted] An Effective Approach for Human Activity Classification Using Feature Fusion and Machine Learning Methods
Table 7
Classification results of experiment 4.
| Weizmann | KTH | Method | (%) | (%) | (%) | (%) | (%) | (%) | (%) | (%) |
| Linear-SVM | 93.38 | 98.96 | 96.09 | 95.9 | 59.25 | 96.7 | 90.90 | 85.3 | Cubic-SVM | 91.56 | 98.5 | 95.63 | 94.5 | 57.56 | 96.45 | 74.49 | 84.3 | Complex tree | 80.56 | 97.18 | 85.57 | 88.5 | 97.74 | 99.63 | 97.51 | 98.2 | Fine-KNN | 46.29 | 87.54 | 88.81 | 58.2 | 70.14 | 96.30 | 90.90 | 84.0 | Subspace-KNN | 89.21 | 98.37 | 91.44 | 92.5 | 99.97 | 99.99 | 99.45 | 99.9 |
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