Random k conditional nearest neighbor for high-dimensional data

Today's article comes from the PeerJ journal of Computer Science. The authors are Lu et al., from the University of Western Ontario, in Canada. In this paper, they reveal a new variant of the k-Nearest Neighbors algorithm. This gives us an excuse to do a thorough deep-dive on kNN and all of the associated concepts and key terms. Let's jump into it.

DOI: 10.7717/peerj-cs.2497