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Machine Learning Class Numbers of Real Quadratic Fields
- Publication Year :
- 2022
-
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.<br />Comment: 26 pages, 20 figures
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2209.09283
- Document Type :
- Working Paper