Loss functions

Linear regression

1. Mean squared error (MSE) : $$MSE = \frac{1}{n}\sum_{i=1}^n (y_i- \hat{y_i})^2 $$
2. R-squared ($R^2$): $$R^2 = 1 - \frac{\sum_{i=1}^n (y_i - \hat{y}i)^2}{\sum^n (y_i - \bar{y})^2} $$