Mean squared error

The mean squared error, or \(MSE\), is a way to measure the fit of the model on training data.

It can also be used to measure the fit of the model on the test data.

Note: \(MSE\) doesn't inherently increase with more predictors, making it a more "honest" metric when tweaking model complexity.