{"created":"2023-05-15T15:31:50.171160+00:00","id":4579,"links":{},"metadata":{"_buckets":{"deposit":"f3e96806-0150-4e47-9a24-ab728c94c547"},"_deposit":{"created_by":17,"id":"4579","owners":[17],"pid":{"revision_id":0,"type":"depid","value":"4579"},"status":"published"},"_oai":{"id":"oai:barrel.repo.nii.ac.jp:00004579","sets":["1:536","4"]},"author_link":["10009","10006","10007","10008"],"item_1_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2010","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"183","bibliographicPageStart":"169","bibliographicVolumeNumber":"6073","bibliographic_titles":[{"bibliographic_title":"Lecture Notes in Computer Science","bibliographic_titleLang":"en"}]}]},"item_1_description_18":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, we consider K-class classification problem, a significant issue in machine learning or artificial intelligence. In this problem, we are given a training set of samples, where each sample is represented by a nominal-valued vector and is labeled as one of the predefined K classes. The problem asks to construct a classifier that predicts the classes of future samples with high accuracy. For K = 2, we have studied a new visual classifier named 2-class SE-graph based classifier (2-SEC) in our previous works, which is constructed as follows: We first create several decision tables from the training set and extract a bipartite graph called an SE-graph that represents the relationship between the training set and the decision tables. We draw the SE-graph as a twolayered drawing by using an edge crossing minimization technique, and the resulting drawing acts as a visual classifier. We can extend 2-SEC to K-SEC for K > 2 naturally, but this extension does not consider the relationship between classes, and thus may perform badly on some data sets. In this paper, we propose SEC-TREE classifier for K > 2, which decomposes the given K-class problem into subproblems for fewer classes. Following our philosophy, we employ edge crossing minimization technique for this decomposition. Compared to previous decomposition strategies, SEC-TREE can extract any tree as the subproblem hierarchy. In computational studies, SEC-TREE outperforms C4.5 and is competitive with SVM especially when K is large.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_1_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"10009","nameIdentifierScheme":"WEKO"}],"names":[{"name":"原口, 和也","nameLang":"ja"}]}]},"item_1_publisher_6":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Springer Berlin Heidelberg","subitem_publisher_language":"en"}]},"item_1_relation_8":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"info:doi/10.1007/978-3-642-13800-3_13","subitem_relation_type_select":"DOI"}}]},"item_1_rights_13":{"attribute_name":"出版社版URI","attribute_value_mlt":[{"subitem_rights":"http://link.springer.com/chapter/10.1007%2F978-3-642-13800-3_13","subitem_rights_language":"ja"}]},"item_1_rights_14":{"attribute_name":"著作権注記","attribute_value_mlt":[{"subitem_rights":"The original publication is available at www.springerlink.com","subitem_rights_language":"en"}]},"item_1_source_id_7":{"attribute_name":"ISSN / EISSN","attribute_value_mlt":[{"subitem_source_identifier":"0302-9743","subitem_source_identifier_type":"PISSN"}]},"item_1_subject_16":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_language":"ja","subitem_subject_scheme":"NDC"}]},"item_1_subject_17":{"attribute_name":"NIIサブジェクト","attribute_value_mlt":[{"subitem_subject":"情報学","subitem_subject_language":"ja","subitem_subject_scheme":"Other"}]},"item_1_version_type_15":{"attribute_name":"テキストバージョン","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Haraguchi, Kazuya","creatorNameLang":"en","creatorNameType":"Personal"}],"nameIdentifiers":[{"nameIdentifier":"10006","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Hong, Seok-Hee","creatorNameLang":"en","creatorNameType":"Personal"}],"nameIdentifiers":[{"nameIdentifier":"10007","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Nagamochi, Hiroshi","creatorNameLang":"en","creatorNameType":"Personal"}],"nameIdentifiers":[{"nameIdentifier":"10008","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-01-26"}],"displaytype":"detail","filename":"Proc.LION4(LNCS 6073)_169-183.pdf","filesize":[{"value":"732.6 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"Proc.LION4(LNCS 6073)_169-183.pdf","url":"https://barrel.repo.nii.ac.jp/record/4579/files/Proc.LION4(LNCS 6073)_169-183.pdf"},"version_id":"7cf2964c-2009-40a9-b7e9-d0e515ba4057"}]},"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":"Multiclass Visual Classifier Based on Bipartite Graph Representation of Decision Tables","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Multiclass Visual Classifier Based on Bipartite Graph Representation of Decision Tables","subitem_title_language":"en"}]},"item_type_id":"1","owner":"17","path":["4","536"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2013-11-20"},"publish_date":"2013-11-20","publish_status":"0","recid":"4579","relation_version_is_last":true,"title":["Multiclass Visual Classifier Based on Bipartite Graph Representation of Decision Tables"],"weko_creator_id":"17","weko_shared_id":-1},"updated":"2025-03-17T00:21:57.750869+00:00"}