{"created":"2023-06-20T12:59:57.796845+00:00","id":4033,"links":{},"metadata":{"_buckets":{"deposit":"a2c08910-13f8-4724-b79a-155a64bc1986"},"_deposit":{"created_by":2,"id":"4033","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"4033"},"status":"published"},"_oai":{"id":"oai:fun.repo.nii.ac.jp:00004033","sets":["22:28","25:81:101"]},"author_link":["7250","95"],"item_5_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2011","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicPageEnd":"272","bibliographicPageStart":"249","bibliographicVolumeNumber":"85","bibliographic_titles":[{"bibliographic_title":"Machine Learning"}]}]},"item_5_description_3":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"2値判別器の統合による多値判別のアプローチの1つとしてブラッドリー・テリーモデルに基づく手法があり，様々な拡張がなされている．このアプローチでは予め定めた符号表と呼ばれる行列に従い多値判別問題を複数の2値判別問題に分解する．本論文では，符号表の定義を拡張した際に起こる致命的な問題を解決するための方法を提案した．またブラッドリー・テリーモデルに基づく手法では，例題毎に最適化が必要であるため計算量が増大しがちであったが，提案法の改良により劇的に計算量を削減することが可能となった．その結果，精度を保ったまま数十〜数百倍程度高速化することが出来た．","subitem_description_type":"Abstract"}]},"item_5_publisher_17":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Springer"}]},"item_5_select_10":{"attribute_name":"単著共著","attribute_value_mlt":[{"subitem_select_item":"共著/joint"}]},"item_5_select_8":{"attribute_name":"査読有無","attribute_value_mlt":[{"subitem_select_item":"あり/yes"}]},"item_5_select_9":{"attribute_name":"研究業績種別","attribute_value_mlt":[{"subitem_select_item":"原著論文/Original Paper"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takenouchi, Takashi"}],"nameIdentifiers":[{"nameIdentifier":"95","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"50403340","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=50403340"}]},{"creatorNames":[{"creatorName":"Ishii, Shin"}],"nameIdentifiers":[{"nameIdentifier":"7250","nameIdentifierScheme":"WEKO"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions"}]},"item_type_id":"5","owner":"2","path":["28","101"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-04-15"},"publish_date":"2013-04-15","publish_status":"0","recid":"4033","relation_version_is_last":true,"title":["Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions"],"weko_creator_id":"2","weko_shared_id":-1},"updated":"2023-06-20T13:32:12.337261+00:00"}