{"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/rule-mining-based-classification-a-benchmark","title":"Rule-Mining based classification: a benchmark study","arxiv_id":"1706.10199","date":"2017-06-30","proceeding":null,"authors":["Margaux Luck","Nicolas Pallet","Cecilia Damon"],"abstract":"This study proposed an exhaustive stable/reproducible rule-mining algorithm\ncombined to a classifier to generate both accurate and interpretable models.\nOur method first extracts rules (i.e., a conjunction of conditions about the\nvalues of a small number of input features) with our exhaustive rule-mining\nalgorithm, then constructs a new feature space based on the most relevant rules\ncalled \"local features\" and finally, builds a local predictive model by\ntraining a standard classifier on the new local feature space. This local\nfeature space is easy interpretable by providing a human-understandable\nexplanation under the explicit form of rules. Furthermore, our local predictive\napproach is as powerful as global classical ones like logistic regression (LR),\nsupport vector machine (SVM) and rules based methods like random forest (RF)\nand gradient boosted tree (GBT).","url_abs":"http://arxiv.org/abs/1706.10199v1","url_pdf":"http://arxiv.org/pdf/1706.10199v1.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":"rule-mining-based-classification-a-benchmark","repo_url":"https://github.com/Museau/Rule-Mining","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"logistic-regression","method_name":"Logistic Regression"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}