Logistic Regression, Stochastic Gradient, Regularization.
the loss function. Logistic loss with L2: Here, similar to what we did above we just changed from absolute w to squared w’s. We square each weight value and sum them up. Now, both the above Loss functions are summations across all n points. In reality we want to look at average loss for all the