Table 1.

Performance measures for non-deep learning classifiers. Shown are averages across 10-fold cross-validation, and standard deviation of the mean in parentheses. All methods were trained using data augmentation.

Classifier	Accuracy [%]	Precision	Recall	F1-Score	AUC
Random Forest	56 (1.)	0.62 (.03)	0.36 (.02)	0.51 (.03)	0.78 (.01)
Logistic Regression	53 (1.)	0.44 (.05)	0.31 (.01)	0.41 (.03)	0.73 (.01)
Gradient Boosting	55 (1.)	0.58 (.04)	0.34 (.01)	0.48 (.02)	0.75 (.01)
KNN	52 (1.)	0.49 (.04)	0.31 (.01)	0.43 (.02)	0.73 (.01)