Mean Square Error Loss(L2 regularization)

Also called:

  • Mean Squared Error (MSE)
  • Least Squared Error (LSE)
  • L2 regularization
  • L2 Loss

Is used for Regression tasks, It tells you how close a regression line is to a set of data points.


  • Calculating derivation is easier in MSE .
  • MSE is more sensitive to outliers due to using the square difference.