BMC Medical Informatics and Decision Making

Table 2 Evaluation Metrics for Spot-checked Base Models

From: Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia

Algorithms	AUC-ROC	Precision	Recall	F	Brier Score
LR	0.7251082	0.4000000	0.3333333	0.3636364	0.07386198
NB	0.7424242	0.2352941	0.6666667	0.3478261	0.17025580
ANN	0.7619048	0.5714286	0.6666667	0.6153846	0.06708493
RF	0.8116883	0.6666667	0.3333333	0.4444444	0.05335981
TBAG	0.7835498	0.2000000	0.1666667	0.1818182	0.07612530
SGB	0.7240260	0.4000000	0.3333333	0.3636364	0.05739256

Bold: stands for selected as the best across the column.

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