w_true = np.array([2.0,-1.0])
n_objects = 200
n_features = 2
X1 = np.random.uniform(-2,2, (n_objects, 1))
X2 = np.random.normal(1,2, (n_objects, 1))
X = np.hstack((X1, X2))
y = X.dot(w_true) + np.random.normal(0,1, (n_objects))
w_0 = np.random.uniform(-2, 2, (n_features))