Table 3 Cross-validated classification accuracy of all models. Average accuracy of categorical prediction in the 3- and 8-class problems is given as measured by the accuracy metric Q k , the Matthews correlation, r(), and SOV. All predictions are for 10-fold cross-validation on the training set (set-174). When standard errors are given in parentheses, the predicted value is the mean of five randomized repeats of cross-validation. The best results are shown in bold.
model | 3-class problem | 8-class problem | ||||
|---|---|---|---|---|---|---|
Q 3 | r(H) | r(E) | r(C) | SOV | Q 8 | |
NBDP | 61.2 | 0.40 | 0.34 | 0.41 | 52.9 | 46.1 |
PNN | 76.4 (0.09) | 0.68 | 0.62 | 0.57 | 67.4 | 61.4 (0.09) |
CPNN | 77.3 (0.07) | 0.69 | 0.63 | 0.58 | 73.8 | 62.8 (0.05) |
CCNN | 77.2 (0.08) | 0.69 | 0.63 | 0.59 | 72.8 | 62.5 (0.15) |