{"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/bayesian-quantile-additive-regression-trees","title":"Bayesian quantile additive regression trees","arxiv_id":"1607.02676","date":"2016-07-10","proceeding":null,"authors":["Bereket P. Kindo","Hao Wang","Timothy Hanson","Edsel A. Peña"],"abstract":"Ensemble of regression trees have become popular statistical tools for the\nestimation of conditional mean given a set of predictors. However, quantile\nregression trees and their ensembles have not yet garnered much attention\ndespite the increasing popularity of the linear quantile regression model. This\nwork proposes a Bayesian quantile additive regression trees model that shows\nvery good predictive performance illustrated using simulation studies and real\ndata applications. Further extension to tackle binary classification problems\nis also considered.","url_abs":"http://arxiv.org/abs/1607.02676v1","url_pdf":"http://arxiv.org/pdf/1607.02676v1.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":"bayesian-quantile-additive-regression-trees","repo_url":"https://github.com/bpkindo/bayesqart","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"binary-classification","task_name":"Binary Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"quantile-regression","task_name":"quantile regression"},{"task_slug":"regression-1","task_name":"regression"}],"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}