Sgd, Machine Learning, Stochastic Gradient.
initializations(self, x_tr, y_tr, x_cv, y_cv): self.wait = 0 self.n = x_tr.shape[0] self.x_tr, self.y_tr = x_tr, y_tr self.x_cv, self.y_cv = x_cv, y_cv self.w, self.b = self.np.zeros_like(x_tr[0]), 0 self.tr_log_loss_lst = [self.log_loss(self.x_tr, self.y_tr)] self.cv_log_loss_lst =