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arXiv · 2209.09283

Machine Learning Class Numbers of Real Quadratic Fields

Malik Amir·Yang-Hui He·Kyu-Hwan Lee·Thomas Oliver·Eldar Sultanow
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Abstract

We implement and interpret various supervised learning experiments involving real quadratic fields with class numbers 1, 2 and 3. We quantify the relative difficulties in separating class numbers of matching/different parity from a data-scientific perspective, apply the methodology of feature analysis and principal component analysis, and use symbolic classification to develop machine-learned formulas for class numbers 1, 2 and 3 that apply to our dataset.

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Malik Amir, Yang-Hui He, Kyu-Hwan Lee, Thomas Oliver, Eldar Sultanow. 2022-09-19. Machine Learning Class Numbers of Real Quadratic Fields. https://doi.org/10.1142/s2810939223500016

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