In the context of MLPs$,$ how does increasing the number of hidden layers affect its classification capability?

Group of answer choices

It turns the MLP into a non$-$universal approximator

It reduces the computational complexity

It allows the MLP to learn more complex decision boundaries

It always improves classification accuracy