M. Amir

Y. He

K. Lee

T. Oliver

E. Sultanow

Supervised learning experiments involving real quadratic fields lead to machine-learned formulas for class numbers 1, 2 and 3, for our dataset.

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