{"created":"2023-06-19T11:41:19.495262+00:00","id":10046,"links":{},"metadata":{"_buckets":{"deposit":"013357a3-89fd-4785-aad4-ad0d3d71b53e"},"_deposit":{"created_by":13,"id":"10046","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"10046"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:00010046","sets":["366:676:677"]},"author_link":["24858","24859","24860"],"item_1706510172288":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Han, Xuexian","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Wakabayashi, Tetsushi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kimura, Fumitaka","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2000-01-01","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"600","bibliographicPageStart":"591","bibliographicVolumeNumber":"1876"}]},"item_3_description_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_3_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"This paper deals with the optimum classifier and the performance evaluation by the Bayesian\napproach. Gaussian population with unknown parameters is assumed. The conditional density given a limited sample of the population has a relationship to the multivariate t-distribution. The mean error rate of the optimum classifier is theoretically evaluated by the quadrature of the conditional density. To verify the optimality of the classifier and the correctness of the mean error calculation, the results of Monte Carlo simulation employing a new sampling procedure are shown. It is also shown by the comparative study that the Bayesian formulas of the mean error rate have the following characteristics.\n1) The unknown population parameters are not required in its calculation.\n2) The expression is simple and clearly shows the limited sample effect on the mean error rate.\n3) The relationship between the prior parameters and the mean error rate is explicitly expressed.","subitem_description_type":"Abstract"}]},"item_3_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"Berlin","subitem_description_type":"Other"},{"subitem_description":"901","subitem_description_type":"Other"},{"subitem_description":"Advances in pattern recognition : joint IAPR International Workshops SSPR 2000 and SPR 2000, Alicante, Spain, August 30-September 1, 2000 : proceedings","subitem_description_type":"Other"},{"subitem_description":"Lecture notes in computer science","subitem_description_type":"Other"}]},"item_3_publisher_30":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Springer"}]},"item_3_relation_11":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1007/3-540-44522-6_61","subitem_relation_type_select":"DOI"}}]},"item_3_relation_37":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"http://www.springerlink.com/content/e01h3er836575j22/?p=19a80a405b4e41c0ac38969c79bf900eπ=88"}]}]},"item_3_relation_8":{"attribute_name":"ISBN","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"9783540679462","subitem_relation_type_select":"ISBN"}}]},"item_3_subject_16":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_3_text_63":{"attribute_name":"ノート","attribute_value_mlt":[{"subitem_text_value":"出版者版電子ジャーナルあり"}]},"item_3_text_65":{"attribute_name":"資源タイプ（三重大）","attribute_value_mlt":[{"subitem_text_value":"Conference Paper / 会議発表論文"}]},"item_3_version_type_15":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-02-20"}],"displaytype":"detail","filename":"40A12189.pdf","filesize":[{"value":"264.6 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"40A12189.pdf","url":"https://mie-u.repo.nii.ac.jp/record/10046/files/40A12189.pdf"},"version_id":"d06faac2-6938-4751-8bcb-e1fa5e4e408e"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Statistical pattern recognition","subitem_subject_scheme":"Other"},{"subitem_subject":"Optimum classifier","subitem_subject_scheme":"Other"},{"subitem_subject":"Monte Carlo simulation","subitem_subject_scheme":"Other"},{"subitem_subject":"Bayesian approach","subitem_subject_scheme":"Other"}]},"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":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"The Optimum Classifier and the Performance Evaluation by Bayesian Approach","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"The Optimum Classifier and the Performance Evaluation by Bayesian Approach","subitem_title_language":"en"}]},"item_type_id":"3","owner":"13","path":["677"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2010-05-24"},"publish_date":"2010-05-24","publish_status":"0","recid":"10046","relation_version_is_last":true,"title":["The Optimum Classifier and the Performance Evaluation by Bayesian Approach"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2024-01-30T00:37:31.654114+00:00"}