Sgd, Machine Learning, Stochastic Gradient.
print(f"Convergence after {epoch} epochs time took: {temp} seconds.") self._early_stoing = True self.wait += 1 else: self.wait = 0 def fit(self, x_tr, y_tr, x_cv, y_cv): self.initializations(x_tr, y_tr, x_cv, y_cv) self.now = time.time() for epoch in range(1, self.max_iter+1): if self._early_stoing