Which of the following are true for the k$-$nearest neighbor $($k$-$NN$)$ algorithm?

Group of answer choices

As k increases, the bias usually increases

k$-$NN can be used only for classification.

As k increases, the variance usually increases.

The decision boundary looks smoother with smaller values of k$.$