Figure 2 | Scientific Reports

Figure 2

From: Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data

Figure 2

Performance of ten different models in internal validation without initial parameters. Area under receiver operating characteristic curve (AUC); Logistic Regression (LR), K Neighbors Classifier (KNN), Decision Tree Classifier (DT), Extra Trees Classifier (ET), Random Forest Classifier (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (Lightgbm), naïve Bayes (NB), Gradient Boosting Classifier (GBC), and Ada Boost Classifier (ADA).

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