{"id":13722,"updated":"2025-01-23T01:06:15.749329+00:00","links":{},"created":"2025-01-18T22:47:44.087087+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00013722","sets":["581:742:753"]},"path":["753"],"owner":"1","recid":"13722","title":["ID3 - GAによる非独立性属性データ問題へのアプローチ"],"pubdate":{"attribute_name":"公開日","attribute_value":"1996-02-15"},"_buckets":{"deposit":"c885f100-f497-4c0d-8db9-a69d564edd88"},"_deposit":{"id":"13722","pid":{"type":"depid","value":"13722","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"ID3 - GAによる非独立性属性データ問題へのアプローチ","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ID3 - GAによる非独立性属性データ問題へのアプローチ"},{"subitem_title":"ID3 - GA for the Dependent Attribute Problem","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"論文","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"1996-02-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海道大学工学部情報工学科"},{"subitem_text_value":"北海道大学工学部精密工学科"},{"subitem_text_value":"北海道大学工学部精密工学科"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Division of Information Engineering, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Department of Precision Engineering, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Department of Precision Engineering, Hokkaido University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/13722/files/IPSJ-JNL3702001.pdf"},"date":[{"dateType":"Available","dateValue":"1998-02-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL3702001.pdf","filesize":[{"value":"802.5 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d1c7ffb0-2055-4974-9333-a85f164f5132","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1996 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"本堂直浩"},{"creatorName":"成瀬, 継太郎"},{"creatorName":"嘉数, 侑昇"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Naohiro, Hondo","creatorNameLang":"en"},{"creatorName":"Keitarou, Naruse","creatorNameLang":"en"},{"creatorName":"Yukinori, Kakazu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ID3は  分類のための決定木生成アルゴリズムとして知られているが  データの性質によっては分類精度が低下する特性を持つ. 特に  データ中の属性がセマンティクス的に非独立である場合  その傾向は顕著である. 本論ではこれに対し従来の情報エントロピーによる属性情報の獲得のほかに  属性のセマンティクスを表現する重み付けパラメータを設定し  決定木の生成を行うID3-GAによるアプローチを行っている. 特に  本論ではこの最適パラメータの決定には遺伝的アルゴリズムを用いている. ここでは計算機実験において  非独立性属性を含むデータに対し実験を行い  ID3-GAの有効性  挙動  特性の検証を行っている.","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"ID3 is an algorithm of making decision trees for classification and has a wide use and a high quality mechanism of concept acquisition. However, it has some features that the classificational accuracy becomes lower in some data. Especially, if the data have dependence attributes on semantics, the tendency becomes more conspicuous. In this paper, we propose a new parameter that shows conceptual weight of attribute, in addition to conventional information entropy criterion. The parameter works to make trees with the entropy in ID3. The optimal parameters are acquired using genetic algorithms in this paper. Experiments show that proposed ID3 makes it possible to classify the data more carefully. Finally, the nature of approach is discussed through several experiments.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"178","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"169","bibliographicIssueDates":{"bibliographicIssueDate":"1996-02-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"37"}]},"relation_version_is_last":true,"item_2_alternative_title_2":{"attribute_name":"その他タイトル","attribute_value_mlt":[{"subitem_alternative_title":"知識獲得"}]},"weko_creator_id":"1"}}