{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T10:40:06Z","timestamp":1768992006498,"version":"3.49.0"},"reference-count":29,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"National Key R&D Program of China","award":["2017YFB1201201"],"award-info":[{"award-number":["2017YFB1201201"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2020.3047741","type":"journal-article","created":{"date-parts":[[2020,12,28]],"date-time":"2020-12-28T20:46:56Z","timestamp":1609188416000},"page":"16030-16040","source":"Crossref","is-referenced-by-count":15,"title":["An Improved MAHAKIL Oversampling Method for Imbalanced Dataset Classification"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8875-897X","authenticated-orcid":false,"given":"Yong","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7758-4353","authenticated-orcid":false,"given":"Tingting","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lichao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2457-9032","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongyi","family":"Xing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.232"},{"key":"ref12","first-page":"152","author":"jeatrakul","year":"2010","journal-title":"Classification of Imbalanced Data by Combining the Complementary Neural Network and SMOTE Algorithm"},{"key":"ref13","first-page":"878","volume":"3644","author":"han","year":"2005","journal-title":"Borderline-SMOTE A New Over-Sampling Method in Imbalanced Data Sets Learning"},{"key":"ref14","first-page":"1","article-title":"Classification of imbalanced data by using the smote algorithm and locally linear embedding","author":"wang","year":"2007","journal-title":"Proc 8th Int Conf Signal Process"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2017.2731766"},{"key":"ref16","first-page":"31","article-title":"Study on classified flood forecasting based on neural network and genetic algorithms","volume":"51","author":"liu","year":"2020","journal-title":"Water Resources and Hydropower"},{"key":"ref17","author":"goldberg","year":"1989","journal-title":"Genetic Algorithms in Search Optimization and Machine Learning"},{"key":"ref18","first-page":"49","article-title":"On the generalized distance in statistics","volume":"1","author":"mahalanobis","year":"1936","journal-title":"Proc Nat Inst Sci India"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-25465-X_15"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2899467"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.fss.2007.12.023"},{"key":"ref27","first-page":"31","article-title":"Using AUC and accuracy in evaluating learning algorithms","volume":"17","author":"huang","year":"2005","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2019.101723"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.01.018"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2961784"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007733"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(02)00257-1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2011.05.002"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2018.06.011"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/j.0824-7935.2004.t01-1-00228.x"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103319"},{"key":"ref20","author":"harrington","year":"2012","journal-title":"Machine Learning in Action"},{"key":"ref22","first-page":"255","article-title":"Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework","volume":"2","author":"alcal\u00e1-fdez","year":"2011","journal-title":"J Multiple-Valued Logic Soft Comput"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","article-title":"KEEL: A software tool to assess evolutionary algorithms for data mining problems","volume":"13","author":"alcal\u00e1-fdez","year":"2009","journal-title":"Soft Comput"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2012.2187280"},{"key":"ref23","author":"quinlan","year":"1993","journal-title":"C4 5 Programs for Machine Learning"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(96)00142-2"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.04.009"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09309241.pdf?arnumber=9309241","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:57:15Z","timestamp":1639771035000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9309241\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3047741","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}