Now I have binary classification problem with positive samples roughly 100 times the number of negative samples. In this case the normal accuracy measure (predict == label) is not a good measure. What other measures there are? Is precision,recall for negative sample fine or F-1 measure the best? If the model is a probability model, is AUC(Area under curve) a good measure?