AUTHOR=Gao Li-Zhen , Lu Chun-Yue , Guo Gong-De , Zhang Xin , Lin Song 

TITLE=Quantum K-nearest neighbors classification algorithm based on Mahalanobis distance

JOURNAL=Frontiers in Physics

VOLUME=10

YEAR=2022

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2022.1047466

DOI=10.3389/fphy.2022.1047466

ISSN=2296-424X

ABSTRACT=<p>Mahalanobis distance is a distance measure that takes into account the relationship between features. In this paper, we proposed a quantum <italic>K</italic>NN classification algorithm based on the Mahalanobis distance, which combines the classical <italic>K</italic>NN algorithm with quantum computing to solve supervised classification problem in machine learning. Firstly, a quantum sub-algorithm for searching the minimum of disordered data set is utilized to find out <italic>K</italic> nearest neighbors of the testing sample. Finally, its category can be obtained by counting the categories of <italic>K</italic> nearest neighbors. Moreover, it is shown that the proposed quantum algorithm has the effect of squared acceleration compared with the classical counterpart.</p>