Robust evaluation of classical and quantum machine learning under noise, imbalance, feature reduction and explainability
Abstract Quantum machine learning (QML) has emerged as a promising paradigm for solving complex classification problems by leveraging the computational advantages of quantum systems. While most traditional machine learning models focus on clean, balanced datasets, real-world data is often noisy, imb...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Nature Portfolio
2025-12-01
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| Series: | Scientific Reports |
| Assuntos: | |
| Acceso en liña: | https://doi.org/10.1038/s41598-025-28412-9 |
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