Fig. 2From: Using machine learning to explore core risk factors associated with the risk of eating disorders among non-clinical young women in China: A decision-tree classification analysisSensitivity and specificity for different test set. Note: The random state determines the randomness in the split of training set and test set. Therefore, different random states correspond to different test sets. Our proposed model was evaluated by each test set and the test sensitivity and specificity were recorded for each test set. In the figure above, the blue curve represents the change of test sensitivity with different test sets and the red curve represents the change of test specificity with different test setsBack to article page