Table 2.

Metrics and Scoring for Quantifying the Quality of Model Performance with 5-Fold Stratified Cross-Validation on Test Set

	Accuracy_scores	Precision	Recall	F1-scores	AUC
	No-survivor	No-survivor	No-survivor	No-survivor
ANN	0.67±0.09	0.66±0.07	0.65±0.07	0.67±0.09	0.782 ± 0.025
CatBoost	0.62±0.10	0.64±0.13	0.62±0.10	0.62±0.10	0.757 ± 0.060
Decision Tree	0.55±0.10	0.55±0.14	0.54±0.14	0.49±0.08	0.631 ± 0.086
GBM	0.57±0.08	0.54±0.08	0.54±0.08	0.52±0.08	0.715 ± 0.063
GNB	0.57±0.11	0.54±0.18	0.58±0.11	0.54±0.15	0.793 ± 0.041
KNN	0.74±0.09	0.75±0.10	0.74±0.09	0.74±0.10	0.745 ± 0.040
Logistic	0.66±0.09	0.66±0.08	0.66±0.09	0.65±0.09	0.793 ± 0.031
Random Forest	0.64±0.14	0.66±0.12	0.61±0.09	0.58±0.06	0.728 ± 0.053
SVM	0.69±0.09	0.70±0.09	0.69±0.09	0.69±0.09	0.786 ± 0.037

LASSO least absolute shrinkage and selection operator, ANN artificial neural network, GBM gradient boosting machine, GNB Gaussian NB, KNN K-nearest neighbor, SVM supported vector machine