{"id":38824,"updated":"2025-01-22T13:10:12.714454+00:00","links":{},"created":"2025-01-18T23:06:19.971953+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00038824","sets":["1164:3206:3296:3297"]},"path":["3297"],"owner":"1","recid":"38824","title":["標本数が少ない状況下における識別器の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"1992-12-17"},"_buckets":{"deposit":"9e3c35fa-4282-4d72-b578-a046fcf25c41"},"_deposit":{"id":"38824","pid":{"type":"depid","value":"38824","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"標本数が少ない状況下における識別器の評価","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"標本数が少ない状況下における識別器の評価"},{"subitem_title":"Evaluation of classifiers in a small sample size case","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"1992-12-17","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"山口大学工学部"},{"subitem_text_value":"大島商船高等専門学校"},{"subitem_text_value":"山口大学工学部"},{"subitem_text_value":"山口大学工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Yamaguchi University","subitem_text_language":"en"},{"subitem_text_value":"Oshima National College of Maritime Technology","subitem_text_language":"en"},{"subitem_text_value":"Yamaguchi University","subitem_text_language":"en"},{"subitem_text_value":"Yamaguchi University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"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/38824/files/IPSJ-CG92060014.pdf"},"date":[{"dateType":"Available","dateValue":"1994-12-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CG92060014.pdf","filesize":[{"value":"925.7 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":"28"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e7e767f3-f2a6-45be-97be-935fc330a66c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1992 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"浜本, 義彦"},{"creatorName":"内村, 俊二"},{"creatorName":"金岡, 泰保"},{"creatorName":"富田, 真吾"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshihiko, Hamamoto","creatorNameLang":"en"},{"creatorName":"Shunji, Uchimura","creatorNameLang":"en"},{"creatorName":"Taiho, Kanaoka","creatorNameLang":"en"},{"creatorName":"Shingo, Tomita","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10100541","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"統計的パターン認識における主要な問題は，識別器を設計することである。識別器は，有限個の訓練サンプルを用いて学習される。特に，識別性能の高い識別器を得るためには，大量の訓練サンプルが必要である。ところが，実際のパターン認識問題では，特徴数に対する訓練サンプル数の比が小さい場合が多い。そこで，そのような状況下で，誤識別率の意味で，いずれの識別器が最良かという疑問が生じる。本論文では，人工データを用いて，よく知られている識別器を識別性能の観点から比較する。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The main problem in statistical pattern recognition is to design a classifier. The classifier must be learned from the training samples. A large training sample is essential to design a classifier with a very low error probability. In any practical situations, the ratio of sample size to dimensionality is small. One may ask which of classfiers is best in terms of the error probability, when the ratio of sample size to dimensionality is small. We compare the classification performances of the well-known classifiers on three artificial data sets.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"108","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告グラフィクスとCAD（CG）"}],"bibliographicPageStart":"101","bibliographicIssueDates":{"bibliographicIssueDate":"1992-12-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"101(1992-CG-060)","bibliographicVolumeNumber":"1992"}]},"relation_version_is_last":true,"weko_creator_id":"1"}}