{"created":"2023-05-15T09:58:52.417028+00:00","id":2921,"links":{},"metadata":{"_buckets":{"deposit":"736f07f3-4b5e-4504-aec9-ff38bb3b7ab6"},"_deposit":{"created_by":5,"id":"2921","owner":"5","owners":[5],"pid":{"revision_id":0,"type":"depid","value":"2921"},"status":"published"},"_oai":{"id":"oai:miyazaki-u.repo.nii.ac.jp:00002921","sets":["73","73:36","73:36:330","73:36:330:319"]},"author_link":["7975","12201","11805","11807"],"item_10002_alternative_title_1":{"attribute_name":"その他（別言語等）のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Implementation and Evaluation of Parallel Support Vector Machine using Divide and Conquer Method on Parallel Computer"}]},"item_10002_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-09-30","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"366","bibliographicPageStart":"361","bibliographicVolumeNumber":"38","bibliographic_titles":[{"bibliographic_title":"宮崎大学工学部紀要","bibliographic_titleLang":"ja"},{"bibliographic_title":"Memoirs of Faculty of Engineering, University of Miyazaki","bibliographic_titleLang":"en"}]}]},"item_10002_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Support Vector Machine (SVM) is a kind of pattern classification method. Because learning of SVM is based on quadratic optimization, SVM can easily handle large scale problems with many training examples. But learning of SVM takes a long time for such large problems. In this paper, we parallelize Support Vector Machine using divide and conquer method. In addition, we discuss accuracy of parallel SVM, and evaluated learning time. 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