Logistic Regression, Stochastic Gradient, Regularization.
variable x and for that variable we need to find w. Now, lets calculate the Log loss by using a large w value. Let w be 10000. Lets assume we have no bias so z = σ(wx) For the first case when y = 0, wx = 10000 * -13, then σ(wx) ≈ 0 and thus log(1 — σ(z)) ≈ log(1) = 0 Similarly, for case2 when y =