Research Article
The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest
Table 2
Performance of proposed and compared methods under 10 classifications.
| Method | Training accuracy (%) | Testing accuracy (%) |
| RF | 37.42 | 39.10 | ET | 43.19 | 40.35 | XGBoost | 47.68 | 44.36 | LightGBM | 55.02 | 57.89 | SVM | 67.13 | 73.43 | LSTM | 57.65 | 57.89 | gcForest | 95.31 | 94.99 | Proposed method | 98.05 | 96.99 |
|
|