{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-tutorial-on-canonical-correlation-methods","title":"A Tutorial on Canonical Correlation Methods","arxiv_id":"1711.02391","date":"2017-11-07","proceeding":null,"authors":["Viivi Uurtio","João M. Monteiro","Jaz Kandola","John Shawe-Taylor","Delmiro Fernandez-Reyes","Juho Rousu"],"abstract":"Canonical correlation analysis is a family of multivariate statistical\nmethods for the analysis of paired sets of variables. Since its proposition,\ncanonical correlation analysis has for instance been extended to extract\nrelations between two sets of variables when the sample size is insufficient in\nrelation to the data dimensionality, when the relations have been considered to\nbe non-linear, and when the dimensionality is too large for human\ninterpretation. This tutorial explains the theory of canonical correlation\nanalysis including its regularised, kernel, and sparse variants. Additionally,\nthe deep and Bayesian CCA extensions are briefly reviewed. Together with the\nnumerical examples, this overview provides a coherent compendium on the\napplicability of the variants of canonical correlation analysis. By bringing\ntogether techniques for solving the optimisation problems, evaluating the\nstatistical significance and generalisability of the canonical correlation\nmodel, and interpreting the relations, we hope that this article can serve as a\nhands-on tool for applying canonical correlation methods in data analysis.","url_abs":"http://arxiv.org/abs/1711.02391v1","url_pdf":"http://arxiv.org/pdf/1711.02391v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-tutorial-on-canonical-correlation-methods","repo_url":"https://github.com/aalto-ics-kepaco/cca-tutorial","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1711.02391","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}