[leecho0]

replace threshold with parameter,

classifiers may have different parameters other than threshold

Area under ROC curves (AUC) are used to evaluate how good the model is considering many parameters can be chosen for it.

However, when you actually want to make a prediction, you still need to pick a value for the parameter (a point on the ROC curve). So F-measure is often more useful for evaluating the predictions. While AUC are more useful at evaluating classifiers.