This article is a retraction of:
RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree
Frontiers Editorial OfficeA Retraction of the Original Research Article
Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree
by Ji N, Bao R, Mu X, Chen Z, Yang X and Wang S (2023). Front. Phys. 11:1179868. doi: 10.3389/fphy.2023.1179868
The journal retracts the 03 July 2023 article cited above.
Following concerns regarding the originality of the article, an investigation was conducted in accordance with Frontiers’ policies. It was found that the complaint was valid and that the article should be retracted, because of an unacceptable level of similarity to the preprint https://doi.org/10.48550/arXiv.2210.02355 which is now published: Srikumar, M., Hill, C.D. & Hollenberg, L.C.L. A kernel-based quantum random forest for improved classification. Quantum Mach. Intell. 6, 10 (2024). https://doi.org/10.1007/s42484-023-00131-2.
The retraction of the article was approved by the Chief Editor of Frontiers in Physics and the Chief Executive Editor of Frontiers. The authors did not respond to the retraction.
Citation: Frontiers Editorial Office (2024) Retraction: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree. Front. Phys. 12:1465482. doi: 10.3389/fphy.2024.1465482
Received: 16 July 2024; Accepted: 16 July 2024;
Published: 22 July 2024.
Approved by:
Alex Hansen, NTNU, NorwayCopyright © 2024 Frontiers Editorial Office. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Frontiers Editorial Office, cmVzZWFyY2guaW50ZWdyaXR5QGZyb250aWVyc2luLm9yZw==