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 the sample’s category by the similarity between samples. In this paper, we propose a quantum K -nearest neighbor classification algorithm with the Hamming distance. In this algorith...
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| Published in | Quantum information processing Vol. 21; no. 1 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.01.2022
Springer Nature B.V |
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| Online Access | Get full text |
| ISSN | 1570-0755 1573-1332 |
| DOI | 10.1007/s11128-021-03361-0 |
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| 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 the Hamming distance. In this algorithm, quantum computation is utilized to obtain the Hamming distance in parallel at first. 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 significant speedup by analyzing its time complexity briefly. |
|---|---|
| AbstractList | 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 the Hamming distance. In this algorithm, quantum computation is utilized to obtain the Hamming distance in parallel at first. 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 significant speedup by analyzing its time complexity briefly. 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 the Hamming distance. In this algorithm, quantum computation is utilized to obtain the Hamming distance in parallel at first. 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 significant speedup by analyzing its time complexity briefly. |
| ArticleNumber | 18 |
| Author | Li, Jing Guo, Gongde Lin, Song Yu, Kai |
| Author_xml | – sequence: 1 givenname: Jing surname: Li fullname: Li, Jing organization: College of Mathematics and Informatics, Fujian Normal University – sequence: 2 givenname: Song orcidid: 0000-0003-0907-4594 surname: Lin fullname: Lin, Song organization: Digital Fujian Internet-of-Things Laboratory of Environmental Monitoring, Fujian Normal University – sequence: 3 givenname: Kai surname: Yu fullname: Yu, Kai organization: College of Mathematics and Informatics, Fujian Normal University – sequence: 4 givenname: Gongde surname: Guo fullname: Guo, Gongde organization: College of Mathematics and Informatics, Fujian Normal University |
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| Cites_doi | 10.1007/s10773-017-3514-4 10.1103/PhysRevLett.103.150502 10.1103/PhysRevLett.114.140504 10.1007/s00500-005-0503-y 10.1103/PhysRevLett.100.160501 10.1103/PhysRevA.78.052310 10.1038/nphys3029 10.1007/s11128-019-2364-9 10.1103/PhysRevA.99.032311 10.1007/s11128-013-0687-5 10.1103/PhysRevA.94.042311 10.1103/PhysRevLett.79.325 10.1103/PhysRevLett.87.167902 10.1109/TIT.1967.1053964 10.1103/PhysRevA.96.032301 10.1103/PhysRevLett.113.130503 10.1089/big.2018.0175 10.1103/PhysRevA.96.012335 10.1038/nature23474 10.1007/s11128-018-2004-9 10.1103/PhysRevLett.114.110504 10.1007/978-3-319-74971-6_16 10.1090/conm/305/05215 |
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-nearest neighbor classification algorithm is one of the most basic algorithms in machine learning, which determines the sample’s category by the similarity... K-nearest neighbor classification algorithm is one of the most basic algorithms in machine learning, which determines the sample’s category by the similarity... |
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| Title | Quantum K-nearest neighbor classification algorithm based on Hamming distance |
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