Final answer:
The correct answer is option 1) Squared values; absolute percentage error.
Step-by-step explanation:
The correct answer is option 1) Squared values; absolute percentage error.
The mean squared error (MSE) is a measure of the average squared difference between the predicted and actual values in a regression analysis. It weighs errors according to their squared values, giving more weight to larger errors.
On the other hand, the mean absolute percentage error (MAPE) measures the average absolute percentage difference between the predicted and actual values. It weighs errors according to the absolute percentage error, giving equal weight to all errors regardless of their magnitude.