{"created":"2023-07-27T06:24:45.570805+00:00","id":7797,"links":{},"metadata":{"_buckets":{"deposit":"2fc67c87-3a8f-4555-b9f3-bc2253a719f9"},"_deposit":{"created_by":3,"id":"7797","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"7797"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00007797","sets":["934:935:936"]},"author_link":["353","10603"],"item_8_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1998-05-01","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"2252","bibliographicPageStart":"2247","bibliographicVolumeNumber":"34","bibliographic_titles":[{"bibliographic_title":"IEEE International Conference on Neural Networks - Conference Proceedings"}]}]},"item_8_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, a training data selection method for multilayer neural networks (MLNNs) in on-line training is proposed. Purpose of the reduction in training data is reducing the computation complexity of the training and saving the memory to store the data without losing generalization performance. This method uses a pairing method, which selects the nearest neighbor data by finding the nearest data in the different classes. The network is trained by the selected data. Since the selected data located along data class boundary, the trained network can guarantee generalization performance. Efficiency of this method for the on-line training is evaluated by computer simulation.","subitem_description_type":"Abstract"}]},"item_8_description_5":{"attribute_name":"提供者所属","attribute_value_mlt":[{"subitem_description":"金沢大学大学院自然科学研究科情報システム","subitem_description_type":"Other"}]},"item_8_publisher_17":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Institute of Electrical and Electronics Engineers (IEEE)"}]},"item_8_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1098-7576","subitem_source_identifier_type":"ISSN"}]},"item_8_version_type_25":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hara, Kazuyuki"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nakayama, Kenji"}],"nameIdentifiers":[{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-10-03"}],"displaytype":"detail","filename":"TE-PR-NAKAYAMA-K-2247.pdf","filesize":[{"value":"294.8 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"TE-PR-NAKAYAMA-K-2247.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/7797/files/TE-PR-NAKAYAMA-K-2247.pdf"},"version_id":"7d9bd2b9-5e0f-47b2-9996-f97b59c6b15d"}]},"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":"A training data selection in on-line training for multilayer neural networks","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A training data selection in on-line training for multilayer neural networks"}]},"item_type_id":"8","owner":"3","path":["936"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-03"},"publish_date":"2017-10-03","publish_status":"0","recid":"7797","relation_version_is_last":true,"title":["A training data selection in on-line training for multilayer neural networks"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-07-28T02:19:25.214403+00:00"}