Quantum K-nearest neighbor classification algorithm based on Hamming distance

K-nearest neighbor classification algorithm is one of the most basic algorithms in machine learning, which determines sample's category by similarity between samples. In this paper, we propose a quantum with Hamming distance. algorithm, computation firstly utilized to obtain distance parallel. Then, core sub-algorithm for searching minimum unordered integer sequence presented find out Based on these two sub-algorithms, whole frame presented. At last, it shown that proposed can achieve quadratical speedup analyzing its time complexity briefly.