From: A machine learning approach for predicting methionine oxidation sites
Feature set | Accuracy | Sensitivity | Specificity | F-measure | MCC |
---|---|---|---|---|---|
Alternative cutoff: 0.392 | |||||
Primary (52) | 0.5969 | 0.8125 | 0.5664 | 0.3333 | 0.2500 |
Tertiary (24) | 0.6357 | 0.8750 | 0.6018 | 0.3733 | 0.3155 |
Whole (76) | 0.7597 | 0.8125 | 0.7522 | 0.4561 | 0.3998 |
mRMR (54) | 0.7597 | 0.7500 | 0.7611 | 0.4364 | 0.3668 |
Standard cutoff: 0.5 | |||||
Primary (52) | 0.8062 | 0.1875 | 0.8938 | 0.1935 | 0.0836 |
Tertiary (24) | 0.7907 | 0.5625 | 0.8230 | 0.4000 | 0.3044 |
Whole (76) | 0.8372 | 0.5625 | 0.8761 | 0.4615 | 0.3777 |
mRMR (54) | 0.8372 | 0.6250 | 0.8673 | 0.4878 | 0.4105 |