{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T08:46:45Z","timestamp":1773737205337,"version":"3.50.1"},"reference-count":90,"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"}],"funder":[{"DOI":"10.13039\/501100002671","name":"Universiti Tunku Abdul Rahman","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002671","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2964726","type":"journal-article","created":{"date-parts":[[2020,1,7]],"date-time":"2020-01-07T20:59:11Z","timestamp":1578430751000},"page":"10262-10281","source":"Crossref","is-referenced-by-count":93,"title":["A Literature Survey and Empirical Study of Meta-Learning for Classifier Selection"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6964-4523","authenticated-orcid":false,"given":"Irfan","family":"Khan","sequence":"first","affiliation":[]},{"given":"Xianchao","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1182-2504","authenticated-orcid":false,"given":"Mobashar","family":"Rehman","sequence":"additional","affiliation":[]},{"given":"Rahman","family":"Ali","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref73","first-page":"111","article-title":"Decision tree-based data characterization for meta-learning","volume":"3","author":"peng","year":"2002","journal-title":"Proc 2nd Int Workshop Integr Collab Aspects Data Mining Decis Support Meta-Lear"},{"key":"ref72","first-page":"319","article-title":"NOEMON: An intelligent assistant for classifier selection","volume":"3","author":"kalousis","year":"1999","journal-title":"Intell Data Anal"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1023\/A:1021713901879"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.02.007"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1782-9_13"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-130599"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-012-0280-z"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-016-0475-9"},{"key":"ref75","first-page":"25","article-title":"Estimating the predictive accuracy of a classifier","author":"bensusan","year":"2007","journal-title":"Proc Eur Conf Mach Learn (ECML)"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-013-9406-y"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5"},{"key":"ref79","volume":"107","author":"mu\u00f1oz","year":"2018","journal-title":"Instance Spaces for Machine Learning Classification"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/1456650.1456656"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2818138"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.08.004"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.02.010"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_2"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50137-6_7"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.10.021"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/S0065-2458(08)60520-3"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.07.009"},{"key":"ref62","first-page":"119","article-title":"God doesn&#x2019;t always shave with Occam&#x2019;s razor&#x2014;Learning when and how to prune","author":"bensusan","year":"1998","journal-title":"Proc 10th Eur Conf Mach Learn"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-016-1003-3"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45372-5_32"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.12.003"},{"key":"ref64","first-page":"743","article-title":"Meta-learning by landmarking various learning algorithms","author":"pfahringer","year":"2000","journal-title":"Proc 17th Int Conf Mach Learn (ICML)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.05.048"},{"key":"ref65","first-page":"131","article-title":"Distances between data sets based on summary statistics","volume":"8","author":"tatti","year":"2007","journal-title":"J Mach Learn Res"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.12.025"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.09.010"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2018.12.020"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2004.12.002"},{"key":"ref69","first-page":"113","article-title":"The data mining advisor: Meta-learning at the Service of Practitioners","author":"giraud-carrier","year":"2006","journal-title":"Proc Int Conf Mach Learning Appl (ICMLA)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.585893"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00242"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.ins.2015.05.010","article-title":"Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges","volume":"317","author":"mu\u00f1oz","year":"2015","journal-title":"Inf Sci"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-53480-0_27"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.04.027"},{"key":"ref24","first-page":"1128","article-title":"Initializing Bayesian hyperparameter optimization via meta-learning","author":"feurer","year":"2015","journal-title":"Proc 29th AAAI Conf Artif Intell"},{"key":"ref23","first-page":"1","article-title":"To tune or not to tune: Recommending when to adjust SVM HYP","author":"vanschoren","year":"2015","journal-title":"Proc Int Joint Conf Neural Netw (IJCNN)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2004.03.008"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2009.09.020"},{"key":"ref50","article-title":"Characterizing classification datasets: A study of meta-features for meta-learning","author":"rivolli","year":"2018","journal-title":"arXiv 1808 10406"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5687-8"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2012.2237023"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/34.990132"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0700-4"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.12.100"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.01.013"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/34.809107"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2008.62"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-57868-4_52"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5686-9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/746"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.artint.2016.12.001","article-title":"ALORS: An algorithm recommender system for Classifiers","volume":"244","author":"mustafa","year":"2017","journal-title":"Artif Intell"},{"key":"ref40","first-page":"1","article-title":"Learning to propagate labels: Transductive propagation network for few-shot learning","author":"liu","year":"2019","journal-title":"Proc ICLR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.07.015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2629474"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.10.043"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.12.033"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.12.044"},{"key":"ref81","author":"teamn","year":"2018","journal-title":"R A language and environment for statistical computing R version 3 1 0"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2327034"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(01)00653-1"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.01.007"},{"key":"ref83","first-page":"1","author":"hornik","year":"2019","journal-title":"R\/Weka Interface Version 0 4-41"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5681-1"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-31753-3_18"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5277-0"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2016.04.003"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.10.004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-015-0689-3"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.11.034"},{"key":"ref85","author":"mitchell","year":"1997","journal-title":"Machine Learning"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1613\/jair.4726"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1209\/0295-5075\/89\/58007"},{"key":"ref7","first-page":"25","article-title":"AutoFolio: An automatically configured algorithm selector","author":"lindauer","year":"2017","journal-title":"Proc Intern Joint Conf Artificial Intel (IJCAI)"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/3347711"},{"key":"ref87","first-page":"1","article-title":"Maximum likelihood from incomplete data via the EM algorithm","volume":"39","author":"dempster","year":"1977","journal-title":"J Roy Statist Soc B Statist Methodol"},{"key":"ref88","first-page":"2962","article-title":"Efficient and robust automated machine learning","author":"feurer","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2480741.2480748"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3831"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1023\/A:1019956318069"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.12.019"},{"key":"ref47","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"dem\u0161ar","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref42","first-page":"3637","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref41","first-page":"1856","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume":"3","author":"finn","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_46"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00760"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/08951014.pdf?arnumber=8951014","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T01:08:06Z","timestamp":1641949686000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8951014\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":90,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2964726","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}