In regression tasks, which metric is typically used to measure the difference between predicted and actual values?

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Q: In regression tasks, which metric is typically used to measure the difference between predicted and actual values?

Solution: Mean Absolute Error (MAE) is used in regression tasks to quantify the average absolute difference between predicted and actual values.

Steps: 5

Step 1: Understand that regression tasks involve predicting a continuous value.
Step 2: Know that we need a way to measure how close our predictions are to the actual values.
Step 3: Learn about Mean Absolute Error (MAE), which is a common metric used for this purpose.
Step 4: Realize that MAE calculates the average of the absolute differences between predicted values and actual values.
Step 5: Remember that a lower MAE indicates better predictive accuracy.