{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235861","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"235861","title":["複数の分類器の出力を統合する決定木に対する確信度の計算手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"4339aff5-cc73-44d8-82d7-2055c536a2e3"},"_deposit":{"id":"235861","pid":{"type":"depid","value":"235861","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"複数の分類器の出力を統合する決定木に対する確信度の計算手法","author_link":["644551"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"複数の分類器の出力を統合する決定木に対する確信度の計算手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社クレスコ"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/235861/files/IPSJ-Z86-6B-01.pdf","label":"IPSJ-Z86-6B-01.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-6B-01.pdf","filesize":[{"value":"557.5 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1a98723b-3ae3-4644-9598-c4c0521dee4e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"綾塚, 祐二"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"機械学習を用いた分類では、一つの分類器のみでは十分な精度が得られずとも複数の分類器の出力を各種手法で統合することでより良い精度が得られることも多い。我々の研究でも、画像から疾患が進行性か否かを分類する6種の分類器の出力を、各出力に応じて分岐する決定木で統合することで高い精度を得ている。このような場合、統合された出力値は0/1など離散的なものになってしまい、元の分類器の出力する確信度の大小の情報は大きく失われてしまっている。我々は、このような決定木による分類に対し、ファジー論理の考え方を用いて、元の分類器の確信度出力から統合された確信度へ、分類精度への影響なく変換する手法を提案する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"28","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"27","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235861,"updated":"2025-01-19T09:29:24.043644+00:00","links":{},"created":"2025-01-19T01:37:35.411871+00:00"}