{"created":"2025-01-19T01:29:15.275593+00:00","updated":"2025-01-19T11:23:35.493422+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229847","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229847","title":["変数を細分類化する特徴選択方法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"1a6c5b49-87d9-4937-9780-4f9719313edc"},"_deposit":{"id":"229847","pid":{"type":"depid","value":"229847","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"変数を細分類化する特徴選択方法","author_link":["618302"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"変数を細分類化する特徴選択方法"}]},"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":"2023-02-16","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":"東理大"}]},"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/229847/files/IPSJ-Z85-2D-03.pdf","label":"IPSJ-Z85-2D-03.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-2D-03.pdf","filesize":[{"value":"456.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"6d72142b-0fd9-4c0d-bc36-0f573309c19e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"鄭, 弯弯"}],"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":"特徴選択は容疑なく機械学習の精度向上、計算コストの削減、モデルの解釈可能性に対して、重要なアプローチである。特徴選択において、変数とクラスの相関、変数と変数の相関、変数と変数の相互作用の三つの要素から変数の重要度を判定できるが、現時点の特徴選択方法はどちら一方しか測っていなく、汎化能力に欠如している。また、変数は(1)独立で有効、(2)他の変数とセットとして有効、(3)1と２の性質両方がある、(4)冗長、(5)無効五つの種類に分けられるが、既存方法は主に無効な変数を取り除くことを目的としている。本研究は、相関と相互作用の機能を考慮し、変数を細分類化する特徴選択方法を構築した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"92","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"91","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229847,"links":{}}