Which statement is true in the context of evaluating metrics for machine learning algorithms?

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

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Answer: B