Table 4.

Prediction of the polarity of an acute affective episode and euthymia among different individuals: model and generalization on unseen patients.

Individuals with affective episodes and performance metric		Model	Generalization
6 patients (acute affective episodes and euthymia) and 1 HCa
	Accuracyb (%)	70	15.7
	F1-score	0.6927	0.1516
	Precision	0.6889	0.1513
	Recall	0.6934	0.1517
	AUROCc	0.6900	0.1510
7 HCs
	Accuracyb (%)	50	—d
	F1-score	0.4923	—
	Precision	0.4911	—
	Recall	0.4988	—
	AUROC	0.4998	—

^aHC: healthy control.

^bAccuracy expected by chance for a 3-class classification task is 1/3=33%. Thus, accuracies above 33% suggest that the model can predict outcomes better than random guessing, and higher values for accuracy indicate better predictive capacity of the model. Note that the test set was designed to have the same number of samples in each class. This is reflected in the values of F₁-score, precision, and recall being very close to each other and to that of accuracy.

^cAUROC: area under the receiver operating characteristic.

^dAs we were interested in predicting affective psychopathology, we tested the degree to which a model can generalize to different individuals for each task except for the one about distinguishing members of a group of only HCs.