Table 3 Accuracy of baseline, transfer learning and Multi-kernel benchmark methods
Methods | FDG | VBM |
|---|---|---|
SVM | 61.20 ±7.22 | 57.64 ±5.89 |
Logistic Reg | 64.40 ±7.60 | 58.72 ±6.98 |
rMLTFL | 63.33 ±9.02 | 62.53 ±9.08 |
IW | 60.10 ±8.41 | 59.56 ±7.49 |
TCA | 59.83 ±6.02 | 57.02 ±8.27 |
SUBA | 64.68 ±4.34 | 52.44 ±8.33 |
RBA | 61.46 ±8.21 | 58.17 ±8.02 |
FLDA | 63.90 ±10.00 | 60.11 ±9.05 |
TrAdaBoost | 61.45 ±8.56 | 58.98 ±7.43 |
Easy MKL | 64.72 ±9.75 | 60.38 ±7.46 |
Average MKL | 63.34 ±9.08 | 60.11 ±7.14 |
PWMK | 64.19 ±9.80 | 60.11 ±7.14 |
GRAM | 64.72 ±9.75 | / |
RMKL | 63.91 ±9.53 | 60.11 ±7.14 |
CKA | 59.56 ±7.49 | 59.56 ±7.49 |