# TRAIN:
n = x_train.shape[0]
ATrain = np.c_[np.ones(n), x_train] # Líkan: f(x_train) = θ_1 + θ_2*x_train

theta,res,rank,_ = np.linalg.lstsq(ATrain, y_train, rcond=False)
w = theta[1:]
vTrain = theta[0]
yx = np.dot(x_train, w) + vTrain
ypredTrain = np.sign(yx)
skekkja = np.sum(y_train != ypredTrain)/n
print("Train-skekkja: ", skekkja)

# TRAIN:
n = x_test.shape[0]
ATest = np.c_[np.ones(n), x_test] # Líkan: f(x_test) = θ_1 + θ_2*x_test

theta,res,rank,_ = np.linalg.lstsq(ATest, y_test, rcond=False)
w = theta[1:]
vTest = theta[0]
yx = np.dot(x_test, w) + vTest
ypredTest = np.sign(yx)
skekkja = np.sum(y_test != ypredTest)/n
print("Test-skekkja: ", skekkja)