X = np.array([[0],[1],[2],[4]])
y = np.array([4,1,2,5])

poly = sklearn.preprocessing.PolynomialFeatures(3)
Omega = poly.fit_transform(X)
weights = {}
print(Omega.shape[0])
reg_fact = [0, 1, 10]
for i in reg_fact:
    weights['reg_fact={}'.format(i)] = la.multi_dot([la.inv(np.dot(Omega.T,Omega) + np.multiply(i, np.identity(Omega.shape[0]))), Omega.T, y])
print(weights)