[Retracted] Prediction and Analysis of Length of Stay Based on Nonlinear Weighted XGBoost Algorithm in Hospital

Table 4

Quantitative prediction indicators of different algorithms.

Model	ACC	RMSE	F1-score	Kappa coefficient
Naive Bayes	0.7912	2.211	0.725	0.8017
Decision tree	0.8247	1.885	0.829	0.8182
SVM	0.8661	1.592	0.865	0.8611
KNN	0.8117	1.721	0.773	0.8482
XGBoost	0.7958	1.807	0.782	0.8251
The proposed model	0.8211	1.523	0.851	0.8622