Research Article
Comparison of Bagging and Boosting Ensemble Machine Learning Methods for Automated EMG Signal Classification
Table 2
EMG signal classification results for bagging.
| ā | Accuracy (%) | F-measure | ROC area | Kappa |
| ANN | 83.33 | 0.83 | 0.89 | 0.81 | k-NN | 91.42 | 0.914 | 0.986 | 0.8712 | SVM | 98.00 | 0.980 | 0.994 | 0.97 | RF | 98.92 | 0.989 | 1 | 0.9837 | C4.5 | 98.08 | 0.981 | 0.998 | 0.9712 | Random Tree | 97.54 | 0.975 | 0.997 | 0.9631 | REPTree | 97.54 | 0.975 | 0.997 | 0.9631 | LADTree | 88.33 | 0.883 | 0.912 | 0.825 | NB | 89.71 | 0.895 | 0.968 | 0.8456 |
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