From: Methodology for biomarker discovery with reproducibility in microbiome data using machine learning
PRJNA325931* | 9 features (REFS) | 3316 features | SelectKbest (k = 9) | |||
---|---|---|---|---|---|---|
Classifier | AUC | MCC | AUC | MCC | AUC | MCC |
AdaBoostClassifier | 0.8000 | 0.6749 | 0.4500 | 0.0438 | 0.7600 | 0.4530 |
Extra trees | 0.8400 | 0.7532 | 0.5000 | 0.0000 | 0.7600 | 0.5512 |
KNeighbors | 0.6500 | 0.4033 | 0.5000 | − 0.0428 | 0.6500 | 0.2319 |
MLP | 0.8800 | 0.8064 | 0.5200 | − 0.0083 | 0.8200 | 0.6792 |
Lasso CV | 0.7800 | 0.5661 | 0.5000 | 0.1828 | 0.7600 | 0.5758 |
Average | 0.7900 | 0.6407 | 0.4940 | 0.0351 | 0.7500 | 0.4982 |
PRJNA554535 | 5 of 9 features (REFS) | SelectKbest (4 of 9 features) | 10-time random selection | |||
---|---|---|---|---|---|---|
Classifier | AUC | MCC | AUC | MCC | AUC | MCC |
AdaBoostClassifier | 0.8200 | 0.6090 | 0.5260 | 0.5800 | 0.8000 | 0.0525 |
Extra Trees | 0.8500 | 0.6504 | 0.5310 | 0.6093 | 0.8000 | 0.0684 |
KNeighbors | 0.6700 | 0.3840 | 0.5230 | 0.4984 | 0.7300 | 0.0374 |
MLP | 0.7100 | 0.4765 | 0.5230 | 0.3952 | 0.6000 | 0.0600 |
Lasso CV | 0.5200 | − 0.0146 | 0.5160 | − 0.0158 | 0.5100 | 0.0296 |
Average | 0.7140 | 0.4210 | 0.5238 | 0.4134 | 0.6880 | 0.0496 |
PRJEB53017 | 5 of 9 features (REFS) | SelectKbest (4 of 9 features) | 10-time random selection | |||
---|---|---|---|---|---|---|
Classifier | AUC | MCC | AUC | MCC | AUC | MCC |
AdaBoostClassifier | 0.6700 | 0.3036 | 0.5200 | 0.0425 | 0.5500 | 0.0517 |
Extra Trees | 0.6900 | 0.3659 | 0.5230 | 0.2526 | 0.6000 | 0.0550 |
KNeighbors | 0.6800 | 0.4124 | 0.4970 | 0.2977 | 0.6200 | −0.0164 |
MLP | 0.6600 | 0.3823 | 0.5270 | 0.0711 | 0.5400 | 0.0741 |
Lasso CV | 0.6100 | 0.2505 | 0.5100 | 0.2035 | 0.6000 | 0.0189 |
Average | 0.6620 | 0.3429 | 0.5154 | 0.1734 | 0.5820 | 0.0366 |