{"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/beyond-sparsity-tree-regularization-of-deep","title":"Beyond Sparsity: Tree Regularization of Deep Models for Interpretability","arxiv_id":"1711.06178","date":"2017-11-16","proceeding":null,"authors":["Mike Wu","Michael C. Hughes","Sonali Parbhoo","Maurizio Zazzi","Volker Roth","Finale Doshi-Velez"],"abstract":"The lack of interpretability remains a key barrier to the adoption of deep\nmodels in many applications. In this work, we explicitly regularize deep models\nso human users might step through the process behind their predictions in\nlittle time. Specifically, we train deep time-series models so their\nclass-probability predictions have high accuracy while being closely modeled by\ndecision trees with few nodes. Using intuitive toy examples as well as medical\ntasks for treating sepsis and HIV, we demonstrate that this new tree\nregularization yields models that are easier for humans to simulate than\nsimpler L1 or L2 penalties without sacrificing predictive power.","url_abs":"http://arxiv.org/abs/1711.06178v1","url_pdf":"http://arxiv.org/pdf/1711.06178v1.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":"beyond-sparsity-tree-regularization-of-deep","repo_url":"https://github.com/dtak/tree-regularization-public","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"beyond-sparsity-tree-regularization-of-deep","repo_url":"https://github.com/wangyue2334/anomelies","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[{"method_slug":"interpretability","method_name":"Interpretability"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1711.06178","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}