Which metric is commonly used to evaluate the accuracy of a predictive model in classification tasks?

Accuracy is a common metric used to evaluate the performance of a predictive model in classification tasks. It represents the ratio of correctly predicted instances to the total instances and provides a general measure of the model's correctness. Other metrics, such as precision, recall, and F1 score, are also used depending on the specific requirements of the task.