Suppose that we are using k$-$NN with just two training points, which have different $($binary$)$ labels. Assuming we are using k $=1$ and Euclidean distance, what is the decision boundary? Include a drawing with a brief explanation. b$.(2$ pts$)$ For binary classification, given infinite data points, can k$-$NN with k $=1$ express any decision boundary? If yes, describe the $($infinite$)$ dataset you would use to realize a given classification decision boundary. If no$,$ give an example of a decision boundary that cannot be achieved.