11. Which of the following is a correct statement about Mean-Square Error (MSE)?以下哪個對均方誤差 (MSE) 的説法是正確的？A smaller numerical value of MSE means a smaller difference between the predicted value and the real value. 均方誤差數值越小，代表預測值與真實值誤差越小。The numerical value of MSE does not reflect the difference between the predicted value and the real value. 均方誤差數值並不能反映預測值與真實值的誤差。The numerical value of MSE is only able to measure the difference between the predicted value and the real value in particular situations. 均方誤差數值只有在某些情況下能量度預測值與真實值的誤差。A smaller numerical value of MSE means a bigger difference between the predicted value and the real value. 均方誤差數值越小，代表預測值與真實值誤差越大。

s the formula for the mean square error?Review Later

Which of the following is a correct implementation of mean squared error (MSE) metric?Note: numpy library has been imported as np.def MSE(real_target, predicted_target):return np.mean((np.square(real_target) – np.square(predicted_target)))def MSE(real_target, predicted_target):return np.mean((real_target – predicted_target)**2)def MSE(real_target, predicted_target):return np.sqrt(np.mean((np.square(real_target) – np.square(predicted_target))))None of the above

Error is the difference between the actual value and Predicted value and the goal is to reduce this difference.TrueFalse

Which of the following is called Standard Error? T-statistic squared Square root of SSE Square root of SST Square root of MSE

Question 9In Linear Regression, which statement is correct about Sum Squared Error?1 pointThe Sum Squared Error measures the distance between the truth and predicted values.The Sum Squared Error measures the distance between the truth and the average values of the truth.The Sum Squared Error is a measure of the explained variation of our model.The Sum Squared Error measures the distance between the predicted values and the average values of the truth.