etas = [1, 1e-1, 1e-2, 1e-3, 1e-4, 1e-5] acc_list = [] accuracys_train = [] costs_train = [] accuracys_test = [] costs_test = [] for eta in etas: a, b, c, d = logReg.fit(Xtrain, ytrain, eta=eta, n_epochs=2000, Xtest=Xtest, ytest=ytest) acc_list.append(logReg.accuracy(Xtest, ytest)) accuracys_train.append(a) costs_train.append(b) accuracys_test.append(c) costs_test.append(d) print("Accuracy vs. test data, own logreg:", acc_list[-1]) plt.figure(figsize=(10, 8)) plt.title("Accuracy score for varying learning rate, logistic regression") plt.xlabel("Epoch") plt.ylabel("Accuracy") for i, eta in enumerate(etas): color = color_list[i] plt.plot(accuracys_train[i],