{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T12:51:34Z","timestamp":1782996694576,"version":"3.54.5"},"reference-count":63,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2966296","type":"journal-article","created":{"date-parts":[[2020,1,13]],"date-time":"2020-01-13T20:40:13Z","timestamp":1578948013000},"page":"13527-13540","source":"Crossref","is-referenced-by-count":38,"title":["Learning From High-Dimensional Biomedical Datasets: The Issue of Class Imbalance"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3983-6844","authenticated-orcid":false,"given":"Barbara","family":"Pes","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/WETICE.2017.28"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012487302797"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbs006"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2012.183"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.2165\/00822942-200504030-00004"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2014.7051906"},{"key":"ref37","year":"0","journal-title":"WEKA 3 Data mining software in JAVA"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16327-2_36"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-14-64"},{"key":"ref34","first-page":"164","article-title":"Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers","volume":"74","author":"ksieniewicz","year":"2017","journal-title":"Mach Learn Res"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2015.06.005"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2756904"},{"key":"ref61","doi-asserted-by":"crossref","first-page":"1738","DOI":"10.3390\/s19071738","article-title":"Fear level classification based on emotional dimensions and machine learning techniques","volume":"19","author":"b?lan","year":"2019","journal-title":"SENSORS"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2921087"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/s18041096"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.11192"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/nrc2294"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01184-9_12"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s11634-017-0285-y"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/WETICE.2019.00040"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2018.00059"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2013.07.007"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001409007326"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.04.007"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2010.2048428"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.191502998"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38326-7_15"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/0-306-47815-3_9"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2007.46"},{"key":"ref56","author":"witten","year":"2016","journal-title":"Data Mining Practical Machine Learning Tools and Techniques"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-377-6.50023-2"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1162\/089976601300014493"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/tpj.2010.56"},{"key":"ref52","first-page":"148","article-title":"Experiments with a new boosting algorithm","author":"freund","year":"1996","journal-title":"Proc 13th Int Conf Mach Learn"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/198363"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.01.035"},{"key":"ref40","first-page":"111","article-title":"The class imbalance problem: Significance and strategies","author":"japkowicz","year":"2000","journal-title":"Proc Int Conf Artif Intell"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-92639-1_20"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2837654"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2012.33"},{"key":"ref15","first-page":"1357","article-title":"Variable selection using SVM based criteria","volume":"3","author":"rakotomamonjy","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0028210"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2012.6303031"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2922987"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-19066-2_19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.08.010"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.05.042"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-21858-8"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm344"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.2202\/1544-6115.1147"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.01.069"},{"key":"ref49","year":"2019","journal-title":"OpenML Datasets"},{"key":"ref9","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"guyon","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2907070"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0177678"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/nm0102-68"},{"key":"ref47","first-page":"1602","article-title":"Gene expression-based classification of malignant gliomas correlates better with survival than histological classification","volume":"63","author":"nutt","year":"2003","journal-title":"Cancer Res"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2008.239"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273614"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1186\/s13040-017-0155-3"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.02.023"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/08957486.pdf?arnumber=8957486","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T15:56:05Z","timestamp":1642002965000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8957486\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":63,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2966296","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}