Table 5 Classification performance (Accuracy [%]) by using 10-fold cross validation (CV) sampling and holdout (90% training and 10% test percentage split) for HC vs AD, HC vs MCI, MCI vs AD, HC vs CASE, taking into account Wavelet (WT) and Fourier (FT) Coefficients as features
From: Combining EEG signal processing with supervised methods for Alzheimer’s patients classification
Wavelet | Fourier | |||
|---|---|---|---|---|
10-fold CV | Holdout | 10-fold CV | Holdout | |
HC vs AD | 76.4 | 71.4 | 80.6 | 85.7 |
HC vs MCI | 93.3 | 83.3 | 83.3 | 83.3 |
MCI vs AD | 66.3 | 88.9 | 66.7 | 77.2 |
HC vs CASE | 81.7 | 81.8 | 84.4 | 90.9 |