A regularization method for regression models that penalizes the size of regression coefficients $\beta_i$ and biases them towards zero. Elastic net includes two penalty terms, one proportional to $\sum |\beta_i|$ and another proportional to $\sum \beta_i^2$. When used alone, these penalty terms lead to Lasso regression and ridge regression respectively.