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Sc."],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:p> 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. <\/jats:p>","DOI":"10.1142\/s2810939223500016","type":"journal-article","created":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T04:55:11Z","timestamp":1698555311000},"page":"107-134","source":"Crossref","is-referenced-by-count":1,"title":["Machine learning class numbers of real quadratic fields"],"prefix":"10.1142","volume":"01","author":[{"given":"Malik","family":"Amir","sequence":"first","affiliation":[{"name":"Microsoft Research New England, One Memorial Drive, Cambridge, MA 02140, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang-Hui","family":"He","sequence":"additional","affiliation":[{"name":"London Institute for Mathematical Sciences, Royal Institution, London W1S 4BS, UK"},{"name":"Department of Mathematics, City, University of London, EC1V 0HB, UK"},{"name":"Merton College, University of Oxford, OX14JD, UK"},{"name":"School of Physics, NanKai University, Tianjin, 300071, P. 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