7 min readSupervised Learning
Regularization: Ridge and Lasso
Adding a penalty on coefficient size to trade a little bias for a large reduction in variance, and why the L1 penalty sets coefficients exactly to zero while L2 only shrinks them, with both fitted numerically.
StatisticsMachine LearningOptimization