Table 1.
Feature | NFT | HT | NP | |||
---|---|---|---|---|---|---|
Statistical Significance | Times selected (%) | Statistical Significance | Times Selected (%) | Statistical Significance | Times Selected (%) | |
— | — | p < 0.001 | 100% | p < 0.001 | 100% | |
— | — | p < 0.001 | 3% | p < 0.001 | 0% | |
p < 0.001 | 0% | p < 0.001 | 94% | p = 0.013 | 0% | |
p < 0.001 | 0% | p < 0.001 | 3% | p = 0.040 | 0% | |
p < 0.001 | 91% | p = 0.010 | 0% | p < 0.001 | 0% | |
p = 0.136 | 0% | p < 0.001 | 0% | p < 0.001 | 0% | |
p < 0.001 | 9% | p = 0.028 | 0% | p < 0.001 | 0% | |
p < 0.001 | 0% | p = 0.165 | 0% | p = 0.247 | 0% | |
p = 0.248 | 0% | p < 0.001 | 0% | p = 0.468 | 0% | |
p = 0.002 | 0% | p < 0.001 | 0% | p < 0.001 | 0% | |
p < 0.001 | 0% | p < 0.001 | 0% | p < 0.001 | 0% |
Statistical significance is computed using the non-parametric two-sided Mann-Whitney U test. The percentage of times each feature is selected is computed over 33 loops of the leave-one-subject-out validation process for the best-performing configuration. Features selected consistently ( of times) are presented in bold and in all cases, they differ significantly between the two subject groups (p < 0.001). See Supplementary Material Table S.1 and Table S.2 for more detailed information on features.