The first algorithm applied is the Nearest Neighbor. To classify a new
instance we consider the k nearest points in terms of Euclidean
distance. The refinement considered is to weight the contribution of
each of the k nearest neighbors according to the query point, giving
greater weight to closer neighbors. This weight is 
, where x is the new instance to classify.