Quantum-Inspired Applications for Classification Problems
In the context of quantum-inspired machine learning, quantum state discrimination is a useful tool for classification problems. We implement a local approach combining the k-nearest neighbors algorithm with some quantum-inspired classifiers. We compare the performance with respect to well-known clas...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/3/404 |
| _version_ | 1797611926583246848 |
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| author | Cesarino Bertini Roberto Leporini |
| author_facet | Cesarino Bertini Roberto Leporini |
| author_sort | Cesarino Bertini |
| collection | DOAJ |
| description | In the context of quantum-inspired machine learning, quantum state discrimination is a useful tool for classification problems. We implement a local approach combining the k-nearest neighbors algorithm with some quantum-inspired classifiers. We compare the performance with respect to well-known classifiers applied to benchmark datasets. |
| first_indexed | 2024-03-11T06:35:31Z |
| format | Article |
| id | doaj.art-093b9f1b017e4e56a98d601b8e6ae413 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-11T06:35:31Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-093b9f1b017e4e56a98d601b8e6ae4132023-11-17T10:55:45ZengMDPI AGEntropy1099-43002023-02-0125340410.3390/e25030404Quantum-Inspired Applications for Classification ProblemsCesarino Bertini0Roberto Leporini1Department of Management, University of Bergamo, via dei Caniana 2, I-24127 Bergamo, ItalyDepartment of Economics, University of Bergamo, via dei Caniana 2, I-24127 Bergamo, ItalyIn the context of quantum-inspired machine learning, quantum state discrimination is a useful tool for classification problems. We implement a local approach combining the k-nearest neighbors algorithm with some quantum-inspired classifiers. We compare the performance with respect to well-known classifiers applied to benchmark datasets.https://www.mdpi.com/1099-4300/25/3/404quantum-inspired machine learningclassificationlocal approach |
| spellingShingle | Cesarino Bertini Roberto Leporini Quantum-Inspired Applications for Classification Problems Entropy quantum-inspired machine learning classification local approach |
| title | Quantum-Inspired Applications for Classification Problems |
| title_full | Quantum-Inspired Applications for Classification Problems |
| title_fullStr | Quantum-Inspired Applications for Classification Problems |
| title_full_unstemmed | Quantum-Inspired Applications for Classification Problems |
| title_short | Quantum-Inspired Applications for Classification Problems |
| title_sort | quantum inspired applications for classification problems |
| topic | quantum-inspired machine learning classification local approach |
| url | https://www.mdpi.com/1099-4300/25/3/404 |
| work_keys_str_mv | AT cesarinobertini quantuminspiredapplicationsforclassificationproblems AT robertoleporini quantuminspiredapplicationsforclassificationproblems |