Machine Learning Class Numbers of Real Quadratic Fields : WestminsterResearch

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Title	Machine Learning Class Numbers of Real Quadratic Fields
Type	Journal article
Authors	Oliver, T.
	Amir, M.
	He, Y.-H.
	Lee, K.-H.
	Sultanow, E.
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.
Journal	International Journal of Data Science in the Mathematical Sciences
Journal citation	1 (2), pp. 107-134
ISSN	2810-9392
	2810-9406
Year	2023
Publisher	World Scientific Publishing
Accepted author manuscript	AHLOS-23-Aug-23.pdf File Access Level Open (open metadata and files)
Digital Object Identifier (DOI)	https://doi.org/10.1142/s2810939223500016
Published online	09 Dec 2023

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Machine Learning Class Numbers of Real Quadratic Fields

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