Table 2.
The performance comparison of the proposed feature selection method with using all features and the state‐of‐the‐art techniques applied to HC subjects from the J‐ADNI dataset
| No. of features | MAE | RMSE | |
|---|---|---|---|
| Franke et al., 2010 | 410a | 4.98 | 6.28 |
| Franke & Gaser, 2014 | – | 5.10 | – |
| Koutsouleris et al., 2014 | 400a | 4.60 | – |
| Wang et al., 2012 | – | 4.60 | 5.60 |
| Gaser et al., 2013 | – | 3.80 | – |
| Lin et al., 2016 | 720 | 4.29 | 5.09 |
| Using all features | 3747 | 4.35 | 5.41 |
| Proposed method | 665 | 4.02 | 5.10 |
MAE: mean absolute error; RMSE: root mean square error.
a
The number of principal components per subject.