{"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/automatic-induction-of-neural-network","title":"Automatic Induction of Neural Network Decision Tree Algorithms","arxiv_id":"1811.10735","date":"2018-11-26","proceeding":null,"authors":["Chapman Siu"],"abstract":"This work presents an approach to automatically induction for non-greedy\ndecision trees constructed from neural network architecture. This construction\ncan be used to transfer weights when growing or pruning a decision tree,\nallowing non-greedy decision tree algorithms to automatically learn and adapt\nto the ideal architecture. In this work, we examine the underpinning ideas\nwithin ensemble modelling and Bayesian model averaging which allow our neural\nnetwork to asymptotically approach the ideal architecture through weights\ntransfer. Experimental results demonstrate that this approach improves models\nover fixed set of hyperparameters for decision tree models and decision forest\nmodels.","url_abs":"http://arxiv.org/abs/1811.10735v4","url_pdf":"http://arxiv.org/pdf/1811.10735v4.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":"automatic-induction-of-neural-network","repo_url":"https://github.com/chappers/automatic-induction-neural-decision-tree","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[{"method_slug":"pruning","method_name":"Pruning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}