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Fig. 5 | BMC Microbiology

Fig. 5

From: In silico analysis of intestinal microbial instability and symptomatic markers in mice during the acute phase of severe burns

Fig. 5

Results of machine learning classification of three groups of samples. (A) Confusion matrix for the classification of burn and control groups using the XGBoost algorithm; (B) Confusion matrix for the classification of burn and control groups using the Randomforest algorithm; (C) Confusion matrix for the classification of burn and control groups using the Gaussian Naive Bayes algorithm; (D) ROC curves for classification of burn and control groups; (E) Confusion matrix for the classification of 4-hour post-burn group and the 6-hour post-burn group using the Randomforest algorithm; (F) Confusion matrix for the classification of 4-hour post-burn group and the 6-hour post-burn group using the SVM algorithm; (G) Confusion matrix for the classification of 4-hour post-burn group and the 6-hour post-burn group using the NaiveBayes algorithm; (H) ROC curves for classification of two burn groups

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