International Journal of Computational Intelligence Systems

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Volume 14, Issue 1, 2021, Pages 248 - 256

Quantum Clustering Ensemble

Authors
Peizhou Tian1, Shuang Jia1, *, Ping Deng2, Hongjun Wang2
1China Aerodynamics Research and Development Center, Miyanyang, 621000, P.R. China
2School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 611756, P.R. China
*Corresponding author. Email: jason_swjtu@163.com
Received 14 July 2020, Accepted 11 November 2020, Available Online 25 November 2020.
DOI
10.2991/ijcis.d.201119.001How to use a DOI?
Keywords
Clustering ensemble; Quantum clustering ensemble; Base clustering
Abstract

Clustering ensemble combines several base clustering results into a definitive clustering solution which has better robustness, accuracy, and stability, and it can also be used in knowledge reuse, distributed computing, and privacy preservation. In this paper, we propose a novel quantum clustering ensemble (QCE) technique derived from quantum mechanics. The idea is that basic labels are associated with a vector in Hilbert space, and a scale-space probability function can be constructed for clustering ensemble. In detail, an operator in Hilbert space is represented by the Schrodinger equation of the probability function as a solution. Firstly, the base clustering results are regarded as new features of the original dataset, and they can be transformed into Hilbert space as vectors. Secondly, a QCE model is designed and the corresponding objective function is illustrated in detail. Furthermore, the objective function is inferred and optimized to obtain the minimum result, which is then used to determine the centers. At last, 5 base clustering algorithms and 5 clustering ensemble algorithms are tested on 12 several datasets for comparing experiments, and the experimental results show that the QCE is very competitive and outperforms the state of the art algorithms.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
248 - 256
Publication Date
2020/11/25
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.201119.001How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Peizhou Tian
AU  - Shuang Jia
AU  - Ping Deng
AU  - Hongjun Wang
PY  - 2020
DA  - 2020/11/25
TI  - Quantum Clustering Ensemble
JO  - International Journal of Computational Intelligence Systems
SP  - 248
EP  - 256
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201119.001
DO  - 10.2991/ijcis.d.201119.001
ID  - Tian2020
ER  -