{"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/ctbnctoolkit-continuous-time-bayesian-network","title":"CTBNCToolkit: Continuous Time Bayesian Network Classifier Toolkit","arxiv_id":"1404.4893","date":"2014-04-18","proceeding":null,"authors":["Daniele Codecasa","Fabio Stella"],"abstract":"Continuous time Bayesian network classifiers are designed for temporal\nclassification of multivariate streaming data when time duration of events\nmatters and the class does not change over time. This paper introduces the\nCTBNCToolkit: an open source Java toolkit which provides a stand-alone\napplication for temporal classification and a library for continuous time\nBayesian network classifiers. CTBNCToolkit implements the inference algorithm,\nthe parameter learning algorithm, and the structural learning algorithm for\ncontinuous time Bayesian network classifiers. The structural learning algorithm\nis based on scoring functions: the marginal log-likelihood score and the\nconditional log-likelihood score are provided. CTBNCToolkit provides also an\nimplementation of the expectation maximization algorithm for clustering\npurpose. The paper introduces continuous time Bayesian network classifiers. How\nto use the CTBNToolkit from the command line is described in a specific\nsection. Tutorial examples are included to facilitate users to understand how\nthe toolkit must be used. A section dedicate to the Java library is proposed to\nhelp further code extensions.","url_abs":"http://arxiv.org/abs/1404.4893v1","url_pdf":"http://arxiv.org/pdf/1404.4893v1.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":"ctbnctoolkit-continuous-time-bayesian-network","repo_url":"https://github.com/dcodecasa/CTBNCToolkit","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}