Find the neighbor

It is clear that the local outlier factor algorithm depends a lot on the idea of a nearest neighbor, which in turn depends on the choice of distance metric. So you decide to experiment some more with the hepatitis dataset introduced in the previous lesson. You are given three examples stored in features, whose classes are stored in labels. You will identify the nearest neighbor to the first example (row with index 0) using three different distance metrics, Euclidean, Hamming and Chebyshev, and on the basis of that choose which distance metric to use. You will import the necessary module as part of the exercise, but pandas and numpy already available, as are features and their labels labels.