{"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/crad-clustering-with-robust-autocuts-and","title":"CRAD: Clustering with Robust Autocuts and Depth","arxiv_id":"1904.04020","date":"2019-04-08","proceeding":null,"authors":["Xin Huang","Yulia R. Gel"],"abstract":"We develop a new density-based clustering algorithm named CRAD which is based\non a new neighbor searching function with a robust data depth as the\ndissimilarity measure. Our experiments prove that the new CRAD is highly\ncompetitive at detecting clusters with varying densities, compared with the\nexisting algorithms such as DBSCAN, OPTICS and DBCA. Furthermore, a new\neffective parameter selection procedure is developed to select the optimal\nunderlying parameter in the real-world clustering, when the ground truth is\nunknown. Lastly, we suggest a new clustering framework that extends CRAD from\nspatial data clustering to time series clustering without a-priori knowledge of\nthe true number of clusters. The performance of CRAD is evaluated through\nextensive experimental studies.","url_abs":"http://arxiv.org/abs/1904.04020v1","url_pdf":"http://arxiv.org/pdf/1904.04020v1.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":"crad-clustering-with-robust-autocuts-and","repo_url":"https://github.com/DataMining-ClusteringAnalysis/CRAD-Clustering","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"},{"task_slug":"time-series-clustering","task_name":"Time Series Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}