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. 2023 Apr 19;8:e40990. doi: 10.2196/40990

Table 2.

Performance of classification models using 10-fold cross-validation (CV) and leave-one-subject-out (LOSO) CV.

Model	AUROC^a			Specificity (%)			Precision (%)			Recall (%)			F₁-score (%)			Accuracy (%)
	LOSO^b	10-fold	LOSO		10-fold	LOSO		10-fold	LOSO		10-fold	LOSO		10-fold	LOSO		10-fold
KNN^c	0.88	0.88	83.15		80.78	82.03		79.92	76.95		76.97	79.41		78.40	79.93		78.83
SVM^d	0.87	0.87	81.15		82.93	81.48		79.98	75.94		77.72	78.28		78.83	78.46		80.24
Random forest	0.88	0.90	80.51		84.48	80.37		82.67	77.45		77.96	78.88		80.24	78.95		81.09
Ensemble learning	N/A^e	N/A	81.51		84.55	80.74		81.53	78.82		78.59	79.76		80.03	80.14		81.46

^aAUROC: area under the receiver operating characteristic curve.

^bLOSO: leave one subject out.

^cKNN: k-nearest neighbor.

^dSVM: support vector machine.

^eN/A: not available.