Research Article
Modified Kernel Marginal Fisher Analysis for Feature Extraction and Its Application to Bearing Fault Diagnosis
Table 4
Performance comparisons for various feature extraction approaches.
| | Methods | | | Average accuracy (%) |
| | KMFA () | 1.455 | 3.11 × 10−3 | 85.36 | | KPCA () | 0.4329 | 0.7747 | 73.20 | | KFDA () | 2.238 | 3.50 × 10−3 | 89.63 | | SKLPP () | 3.086 | 1.24 × 10−3 | 91.27 | | MKMFA () | 6.501 | 8.71 × 10−5 | 97.45 | | SSKMFA () | 3.473 | 4.59 × 10−4 | 95.39 |
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