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],
