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Fig. 6 | BMC Medical Informatics and Decision Making

Fig. 6

From: Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches

Fig. 6

ROC curves of 6 ML classifiers based on all 696 features (a) and top 100 features (b). All 696 features or the top 100 features evaluated by multiple decision trees were incorporated into 6 ML classifiers to calculate the ROC curves. AUC values of the models were indicated in the caption. Twenty iterations were performed for each model. The mean ROC curve (blue) and standard deviation (grey shade area) are presented

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