```R
mean((training.data - predict(training.model))^2)
```

Code to evaluate LR using MSE in R

University of Michigan - Ann Arbor

Mean Square Error (MSE) reflects the degree of difference between the estimated value and the actual value. If the predicted response value is close to the real response value, MSE will be very small. If the predicted response value is substantially different from the real response value, MSE will be very large.
$$ MSE = \frac{1}{m} \sum_{i=1}^{m} (y_m - \hat{y_m})^2 $$


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