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Fig. 4 | BMC Infectious Diseases

Fig. 4

From: Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method

Fig. 4

Receiver operating characteristic (ROC) curves of LR, GNB and SVM models in predicting hospital mortality by K-fold cross-validation. The fold value of k is taken as 5 in this study. A ROC curves of LR; B ROC curves of GNB; C ROC curves of GNB; The y-axis represents the TPR of the risk prediction, the x-axis represents the FPR of the risk prediction. fivefold cross-validation divides the dataset into five parts. Four of them is used for training and one of them is used for testing. This process is repeated five times until all data are used for testing and only once. We integrated the results of five validations, took the average value, and expressed it by mean ROC (blue solid line in each graph). LR logistic regression analysis, GNB Gaussian Naive Bayes, SVM support vector machines

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