Which statement is true in the context of evaluating metrics for machine learning algorithms?
A. A random classifier has AUC (the area under ROC curve) of 0.5
B. Using only one evaluation metric is sufficient
C. The F-score is always equal to precision
D. Recall of 1 (100%) is always a good result