Quantum Random Forest for the Regression Problem
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915886359642112 |
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| author | Khadiev, Kamil Safina, Liliya |
| author_facet | Khadiev, Kamil Safina, Liliya |
| contents | The Random Forest model is one of the popular models of Machine learning. We present a quantum algorithm for testing (forecasting) process of the Random Forest machine learning model for the Regression problem. The presented algorithm is more efficient (in terms of query complexity or running time) than the classical counterpart. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_22790 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quantum Random Forest for the Regression Problem Khadiev, Kamil Safina, Liliya Quantum Physics Artificial Intelligence The Random Forest model is one of the popular models of Machine learning. We present a quantum algorithm for testing (forecasting) process of the Random Forest machine learning model for the Regression problem. The presented algorithm is more efficient (in terms of query complexity or running time) than the classical counterpart. |
| title | Quantum Random Forest for the Regression Problem |
| topic | Quantum Physics Artificial Intelligence |
| url | https://arxiv.org/abs/2603.22790 |