{"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/an-efficient-clustering-algorithm-from-the","title":"An efficient clustering algorithm from the measure of local Gaussian distribution","arxiv_id":"1709.08470","date":"2017-09-13","proceeding":null,"authors":["Yuan-Yen Tai"],"abstract":"In this paper, I will introduce a fast and novel clustering algorithm based on Gaussian distribution and it can guarantee the separation of each cluster centroid as a given parameter, $d_s$. The worst run time complexity of this algorithm is approximately $\\sim$O$(T\\times N \\times \\log(N))$ where $T$ is the iteration steps and $N$ is the number of features.","url_abs":"https://arxiv.org/abs/1709.08470v2","url_pdf":"https://arxiv.org/pdf/1709.08470v2.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":"an-efficient-clustering-algorithm-from-the","repo_url":"https://github.com/Anrris/glassfire","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"an-efficient-clustering-algorithm-from-the","repo_url":"https://github.com/Anrris/glowfire","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"an-efficient-clustering-algorithm-from-the","repo_url":"https://github.com/yuan-yen/glassfire","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}