Batch Normalization is a layer commonly used in state-of-the-art neural networks. It takes inputs from the previous layer and normalizes it by ... The Area Under Curve metric represents the probability that a classifier will be more confident that a randomly chosen positive than a randomly chosen negative example is positive, in the case of binary classification. It is found on a ROC (Receiving Operator Characteristic) Curve, which plots the true positive rate against the false positive rate. Batch Normalization is a layer commonly used in state-of-the-art neural networks. It takes inputs from the previous layer and normalizes it by removing the mean and rescaling the standard deviation.