in[ ]add the squared first feature x_new np hstack([xx[: :* ]from mpl_toolkits mplot import axes daxes figure plt figure(visualize in ax axes (figureelev=- azim=- plot first all the points with = then all with = mask = ax scatter(x_new[mask ]x_new[mask ]x_new[mask ] =' 'cmap=mglearn cm = ax scatter(x_new[~mask ]x_new[~mask ]x_new[~mask ] =' 'marker='^'cmap=mglearn cm = ax set_xlabel("feature "ax set_ylabel("feature "ax set_zlabel("feature * " supervised learning