Table 1 Comparison of different classification methods
From: Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis
| Â | Recognition rate | Prediction rate | Sensitivity | Specificity | Accuracy rate |
|---|---|---|---|---|---|
Ctrl/PLS-DA | 95.5% (63/66) | 75.0% (24/32) | 91.2% (52/57) | 85.4% (35/41) | 89.8% (88/98) |
UV/PLS-DA | 98.5% (65/66) | 78.1% (25/32) | 91.2% (52/57) | 92.7% (38/41) | 91.8% (90/98) |
DOSC/PLS-DA | 100% (66/66) | 84.4% (27/32) | 93.0% (53/57) | 95.1% (40/41) | 94.9% (93/98) |
O-PLS/PLS-DA | 100% (66/66) | 81.3% (26/32) | 91.2% (52/57) | 95.1% (40/41) | 93.9% (92/98) |
FC/DOSC/PLS-DA | 98.5% (65/66) | 90.6% (29/32) | 94.7% (54/57) | 97.6% (40/41) | 95.9% (94/98) |
KNN (K = 3) | 95.5% (63/66) | 71.9% (23/32) | 84.2% (48/57) | 92.7% (38/41) | 87.8% (86/98) |
SIMCA | 90.9% (60/66) | 75.0% (24/32) | 87.7% (50/57) | 82.9% (34/41) | 85.7% (84/98) |
FC/KNN (K = 3) | 95.5% (63/66) | 81.3% (26/32) | 93.0% (53/57) | 87.8% (36/41) | 90.8% (89/98) |
SVM | 100% (66/66) | 81.3% (26/32) | 94.7% (54/57) | 92.7% (38/41) | 93.9% (92/98) |
DOSC/SVM | 100% (66/66) | 87.5% (28/32) | 94.7% (54/57) | 97.6% (40/41) | 95.9% (94/98) |
FC/SVM | 100% (66/66) | 90.6% (29/32) | 96.5% (55/57) | 97.6% (40/41) | 96.9% (95/98) |
FC/DOSC/SVM | 100% (66/66) | 96.9% (31/32) | 100% (57/57) | 97.6% (40/41) | 99.0% (97/98) |