Question

Which of the following are cost functions used to evaluate linear regression models?

A.Accuracy
B.Mean squared error (MSE)
C.Root mean squared error (RMSE)
D.Recall

Answer 1

The cost functions used to evaluate linear regression models are Mean squared error (MSE) and Root mean squared error (RMSE).

Step-by-step explanation:

The cost functions used to evaluate linear regression models are:

• Mean squared error (MSE): This cost function measures the average of the squared differences between the predicted and actual values, giving more weight to larger errors.
• Root mean squared error (RMSE): This cost function is the square root of the MSE and is commonly used to provide a measure of the average size of the errors in the predictions.