Logistic Regression, Stochastic Gradient, Regularization.
optimization and one good reason to do this is to make the optimization function easier to differentiate as derivative of w² is 2w. The 2’s would cancel out and give us (λw)/n. Now, we get our final derivatives for log loss with L2 regularization: Gradient Descent and Stochastic Gradient Descent