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Table 4 Performance measures of the selected machine learning models on original, SMOTE-oversampled dataset1, SMOTE-oversampled dataset4 and ADASYN-oversampled dataset

From: Prediction of neonatal deaths in NICUs: development and validation of machine learning models

Model Data Accuracy Precision Specificity Sensitivity F-score AUC
RF Original data 0.91 0.97 0.62 0.94 0.95 0.90
SMOTE-oversampled dataset1 0.92 0.98 0.94 0.92 0.95 0.97
SMOTE-oversampled dataset4 0.94 0.96 0.92 0.97 0.94 0.98
ADASYN-oversampled dataset 0.96 0.99 0.92 0.99 0.95 0.96
ANN Original data 0.93 0.95 0.43 0.98 0.97 0.93
SMOTE-oversampled dataset1 0.91 0.94 0.84 0.94 0.94 0.96
SMOTE-oversampled dataset4 0.90 0.95 0.85 0.96 0.90 0.96
ADASYN-oversampled dataset 0.88 0.91 0.86 0.91 0.88 0.95
C5.0 Original data 0.94 0.96 0.47 0.98 0.97 0.82
SMOTE-oversampled dataset1 0.92 0.96 0.90 0.93 0.95 0.94
SMOTE-oversampled dataset4 0.94 0.96 0.90 0.97 0.93 0.93
ADASYN-oversampled dataset 0.95 1 0.90 1 0.94 0.97
SVM Original data 0.94 0.96 0.55 0.97 0.97 0.90
SMOTE-oversampled dataset1 0.94 0.97 0.90 0.95 0.96 0.98
SMOTE-oversampled dataset4 0.95 0.98 0.92 0.96 0.95 0.98
ADASYN-oversampled dataset 0.94 0.95 0.82 0.93 0.88 0.97
Bayesian network Original data 0.94 0.97 0.66 0.96 0.96 0.90
SMOTE-oversampled dataset1 0.90 0.95 0.86 0.91 0.93 0.95
SMOTE-oversampled dataset4 0.89 0.89 0.87 0.90 0.88 0.96
ADASYN-oversampled dataset 0.88 0.89 0.86 0.89 0.88 0.94
CHAID tree Original data 0.94 0.95 0.38 0.98 0.98 0.93
SMOTE-oversampled dataset1 0.90 0.96 0.88 0.90 0.93 0.96
SMOTE-oversampled dataset4 0.90 0.96 0.83 0.96 0.89 0.95
ADASYN-oversampled dataset 0.88 0.89 0.86 0.90 0.88 0.95
Ensemble Original data 0.94 0.96 0.48 0.98 0.97 0.94
SMOTE-oversampled dataset1 0.92 0.96 0.88 0.93 0.95 0.98
SMOTE-oversampled dataset4 0.95 0.97 0.84 0.97 0.95 0.98
ADASYN-oversampled dataset 0.95 0.98 0.90 0.96 0.94 0.98