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2022

Machine Learning Class Numbers of Real Quadratic Fields

Amir, Malik, He, Yang-Hui, Lee, Kyu-Hwan et al.

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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.

Machine Learning Class Numbers of Real Quadratic Fields · Around

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