Quantum K-nearest neighbor classification algorithm based on Hamming distance

• URL: http://arxiv.org/abs/2103.04253v2
• Date: Fri, 31 Mar 2023 07:47:34 GMT
• Title: Quantum K-nearest neighbor classification algorithm based on Hamming distance
• Authors: Jing Li, Song Lin, Yu Kai, Gongde Guo
• Abstract summary: We propose a quantum K-nearest neighbor classification algorithm with Hamming distance. It is shown that the proposed algorithm can achieve a quadratical speedup by analyzing its time complexity briefly.
• Score: 3.4501155479285326
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: K-nearest neighbor classification algorithm is one of the most basic algorithms in machine learning, which determines the sample's category by the similarity between samples. In this paper, we propose a quantum K-nearest neighbor classification algorithm with Hamming distance. In this algorithm, quantum computation is firstly utilized to obtain Hamming distance in parallel. Then, a core sub-algorithm for searching the minimum of unordered integer sequence is presented to find out the minimum distance. Based on these two sub-algorithms, the whole quantum frame of K-nearest neighbor classification algorithm is presented. At last, it is shown that the proposed algorithm can achieve a quadratical speedup by analyzing its time complexity briefly.

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