Fig. 2From: Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learningBoxplots, training results (AUROC), postoperative VAS (left) and Q score (right), all models, hip replacement surgery. Note: Outliers depicted as blue dots. XGB: Extreme gradient boosting, MSAENET: Multi-step elastic-net, LM: Linear model, RF: Random forests, NNET: Neural net, LB: Logistic boost, NB: Naïve Bayes, KNN: K-nearest neighborsBack to article page