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Table 3 Best performance obtained for the methodologies studied using the PCG database (scenario 1)

From: Time–frequency based feature selection for discrimination of non-stationary biosignals

Original size of thet–f representation: 512 × 480= 245760. Number of neighbors: 1
Methodology ρ min n rel n =( n c × n r ) Accuracy (%) Sensitivity (%) Specificity (%)
PCA with NA NA 18=(9×2) 92.52±2.32 92.70±6.21 92.30±3.69
tiling [5]       
PLS with NA NA 18=(9×2) 93.80±2.85 94.52±5.48 93.02±4.78
tiling [5]       
Vectorized NA NA NA 91.22±2.76 90.50±2.60 91.88±6.51
PCA [14]       
Vectorized NA NA NA 94.89±2.24 94.55±3.05 95.25±4.24
PLS [14]       
Algorithm 2 + NA NA NA 99.28±1.52 99.64±1.13 98.90±2.48
2D–PCA       
(no relevance)       
Algorithm 2 + NA NA NA 99.28±1.52 99.64±1.13 98.90±2.48
2D–PLS       
(no relevance)       
Method 1 45% 110592 27 93.07±3.50 92.72±4.18 93.43±4.10
Method 2 15% 36864 12 96.72±2.06 95.62±3.76 97.78±3.98
Method 3 40% 98304 26 98.18±1.49 98.20±2.54 98.16±2.61
Method 4 15% 36864 21 98.72±1.23 98.90±1.77 98.53±1.90
Method 5 40% 97920 21=(7× 3) 97.09±2.12 97.43±3.00 96.72±2.04
Method 6 10% 24576 70=(10× 7) 99.28±1.25 99.64±1.13 98.92±1.75
Method 7 40% 97920 60=(12× 5) 97.46±1.94 98.17±2.56 96.72±2.69
Method 8 10% 24576 70=(10× 7) 99.64±0.76 99.64±1.13 99.63±1.17