{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/87407"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/87407","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Partially Bayesian Variable Selection in Classification Trees","abstract":"An algorithm that dynamically incorporates expert opinion in this way has two potential advantages, each improving with the quality of the expert. First, by de-emphasizing certain subsets of variables during the estimation process, unnecessary computational activity can be avoided. Second, by giving an expert's preferred variables priority, we reduce the chance that a spurious variable will appear in the model. Hence, our resulting models are potentially more interpretable and less unstable than those generated by purely data-driven algorithms. We examine these properties in both applied and simulated contexts, and discuss potential extensions of our partially Bayesian algorithm to ensemble trees and other classification and prediction methods.","abstract_html":"An algorithm that dynamically incorporates expert opinion in this way has two potential advantages, each improving with the quality of the expert. First, by de-emphasizing certain subsets of variables during the estimation process, unnecessary computational activity can be avoided. Second, by giving an expert's preferred variables priority, we reduce the chance that a spurious variable will appear in the model. Hence, our resulting models are potentially more interpretable and less unstable than those generated by purely data-driven algorithms. We examine these properties in both applied and simulated contexts, and discuss potential extensions of our partially Bayesian algorithm to ensemble trees and other classification and prediction methods.","abstract_has_math":false,"creators":["Noe, Douglas Alan"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":["He, Xuming"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T16:02:44Z","date_published":"2015-09-28T16:02:44Z","updated_at":"2026-07-22T22:26:30Z","subjects":["Statistics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3242952"],"render_values":[{"text":"(MiAaPQ)AAI3242952","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/87407","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["He, Xuming"]},{"key":"dc:creator","label":"Author","values":["Noe, Douglas Alan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T16:02:44Z","10000-01-01","2006"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Statistics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/87407","(MiAaPQ)AAI3242952"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["An algorithm that dynamically incorporates expert opinion in this way has two potential advantages, each improving with the quality of the expert. 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