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=Volume 10 - 2022

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=Mahalanobis distance is a distance measure that takes into account the relationship between features.In this paper, we proposed a quantum KNN classification algorithm based on the Mahalanobis distance, which combines the classical KNN algorithm with quantum computing to solve supervised classification problem in machine learning. Firstly, the quantum parallelism is utilized to calculate the Mahalanobis distance between the training samples and the test one. Then, a quantum sub-algorithm for searching the minimum of disordered data set is utilized to find out K nearest neighbors of the testing sample. Finally, its category can be obtained by counting the categories of K nearest neighbors. It is shown that the proposed quantum algorithm has the effect of squared acceleration compared with the classical counterpart.