{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T14:14:27Z","timestamp":1773411267810,"version":"3.50.1"},"reference-count":111,"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\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004595","name":"Universiti Sains Malaysia","doi-asserted-by":"publisher","award":["1001\/PKOMP\/8014084"],"award-info":[{"award-number":["1001\/PKOMP\/8014084"]}],"id":[{"id":"10.13039\/501100004595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3081366","type":"journal-article","created":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T21:24:42Z","timestamp":1621286682000},"page":"74127-74142","source":"Crossref","is-referenced-by-count":20,"title":["Multiple Filter-Based Rankers to Guide Hybrid Grasshopper Optimization Algorithm and Simulated Annealing for Feature Selection With High Dimensional Multi-Class Imbalanced Datasets"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7136-8409","authenticated-orcid":false,"given":"Abdulrauf Garba","family":"Sharifai","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8908-5263","authenticated-orcid":false,"given":"Zurinahni Binti","family":"Zainol","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"94","article-title":"Feature selection: A data perspective","volume":"50","author":"li","year":"2016","journal-title":"ACM Comput Surv"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.07.155"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.03.002"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.01.018"},{"key":"ref31","first-page":"1","article-title":"Applying adaptive over-sampling technique based on data density and cost-sensitive SVM to imbalanced learning","author":"wang","year":"2012","journal-title":"Proc Int Joint Conf Neural Netw (IJCNN)"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s13748-016-0094-0"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.09.006"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.3390\/genes11070717"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2016.10.008"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.02.017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2781298"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0192-5"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.187"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2005.01.009"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1321440.1321461"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.05.030"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1002\/9781118646106.ch6"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277927"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1986.289288"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-018-0853-2"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.04.053"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2014.2306838"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/BF00175354"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2017.01.004"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2019.8789974"},{"key":"ref58","first-page":"1531","article-title":"Archimedes optimization algorithm: A new metaheuristic algorithm for solving optimization problems","volume":"51","author":"hashim","year":"2021","journal-title":"Int J Speech Technol"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103300"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105190"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113377"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.02.028"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113702"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.03.055"},{"key":"ref40","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":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2011.2161285"},{"key":"ref3","article-title":"VOS: A method for variational oversampling of imbalanced data","author":"fajardo","year":"2018","journal-title":"arXiv 1809 02596"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-018-0151-6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.12.035"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref49","first-page":"81","article-title":"Particle swarm optimization: Developments, applications and resources","author":"shi","year":"2001","journal-title":"Proc Congr Evol Comput"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2771290"},{"key":"ref9","first-page":"878","article-title":"Borderline-SMOTE: A new over-sampling method in imbalanced data sets learning","author":"han","year":"2005","journal-title":"Proc Int Conf Intell Comput"},{"key":"ref46","first-page":"289","article-title":"Applying weighted particle swarm optimization to imbalanced data in software defect prediction","author":"brezo?nik","year":"2018","journal-title":"Proc Int Conf New Technol Develop Appl"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.09.045"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2011.02.032"},{"key":"ref47","first-page":"569","author":"nguyen","year":"2014","journal-title":"PSO and statistical clustering for feature selection A new representation"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2006.877949"},{"key":"ref41","first-page":"27","article-title":"Practical feature selection: From correlation to causality","author":"guyon","year":"2008","journal-title":"Mining Massive Data Sets for Security Advances in Data Mining Search Social Networks and Text Mining and Their Applications to Security"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1504\/IJDMB.2017.090987"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2019.106839"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.2528\/PIERC19040909"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.06.023"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-017-1019-8"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-017-1074-1"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/ICEEI.2015.7352552"},{"key":"ref77","first-page":"46","article-title":"Using deep learning to classify class imbalanced gene-expression microarrays datasets","author":"reyes-nava","year":"2018","journal-title":"Proc Iberoamerican Congr Pattern Recognit"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.07.015"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-017-0037-9"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21870"},{"key":"ref79","first-page":"17","article-title":"Multilabel classification","author":"herrera","year":"2016","journal-title":"Multilabel Classification"},{"key":"ref60","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","author":"kirkpatrick","year":"1983","journal-title":"Science"},{"key":"ref62","first-page":"71","article-title":"Data clustering with grasshopper optimization algorithm","author":"kowalski","year":"2017","journal-title":"Proc Federated Conf Comput Sci Inf Syst"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/3298460"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.3390\/rs11091134"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3343-2"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2018.07.044"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2891673"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.3390\/rs11091134"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/s00202-019-00762-4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbs006"},{"key":"ref69","first-page":"924","article-title":"A modified grasshopper optimization algorithm combined with CNn for content based image retrieval","volume":"32","author":"sezavar","year":"2019","journal-title":"Int J Eng"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1504\/IJDMB.2020.105437"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.04.039"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-016-2385-6"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37453-1_45"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3469-2"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04962-0_53"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.01.047"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1016\/j.aci.2018.08.003"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105581"},{"key":"ref105","first-page":"4429","article-title":"A novel gene selection method using modified MRMR and hybrid bat-inspired algorithm with SS -hill climbing","volume":"48","author":"alomari","year":"2018","journal-title":"Int J Speech Technol"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/DMIA.2015.17"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0219683"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/239628"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.3390\/informatics5010013"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-27520-8_7"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.03.101"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1145\/2480741.2480752"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.1997.637339"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-011-0043-y"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.12.037"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2012.09.002"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.06.108"},{"key":"ref11","first-page":"1322","article-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning","author":"he","year":"2008","journal-title":"Proc IEEE Int Joint Conf Neural Netw IEEE World Congr Comput Intell"},{"key":"ref12","first-page":"107","article-title":"SMOTEBoost: Improving prediction of the minority class in boosting","author":"chawla","year":"2003","journal-title":"Proc Eur Conf Princ Data Mining Knowl Discovery"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.134"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.12988\/ams.2015.58562"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-9-S6-S7"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-012-0570-1"},{"key":"ref17","first-page":"973","article-title":"The foundations of cost-sensitive learning","volume":"17","author":"elkan","year":"2001","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref81","first-page":"101","article-title":"In defense of one-vs-all classification","volume":"5","author":"rifkin","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref18","first-page":"231","article-title":"Cost-sensitive learning and the class imbalance problem","volume":"2011","author":"ling","year":"2008","journal-title":"Encyc of Mach Learn"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.01.017"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-87479-9_51"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1028144844"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-27338-9"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1007\/s40745-015-0060-x"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1613\/jair.105"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2002.1005608"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti033"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1186\/s40709-016-0045-8"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09433565.pdf?arnumber=9433565","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:56:10Z","timestamp":1639770970000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9433565\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":111,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3081366","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}