X_data, y_data = get_dataset(nsp.get_training_examples)

# Transform a two-dimensional vector x into a three-dimensional vector.
def transform(x):
    return [x[0]**2, np.sqrt(2)*x[0]*x[1], x[1]**2]


fig = plt.figure(figsize=(10,6))
r=np.zeros((16,3))
for i,j in enumerate( X_data):
    r[i]=transform(j)

ax = plt.subplot(projection='3d')
ax.scatter3D(r[:, 0], r[:, 1], r[:,2], c=y_data, s=50, cmap='autumn')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
ax.view_init(12.5, 120)