{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T16:46:13Z","timestamp":1772124373059,"version":"3.50.1"},"reference-count":95,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006162","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Ci\u00eancia e Tecnologia do Estado de Pernambuco","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006162","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1109\/tnnls.2024.3366615","type":"journal-article","created":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T15:07:07Z","timestamp":1708960027000},"page":"4805-4819","source":"Crossref","is-referenced-by-count":10,"title":["Meta-Scaler: A Meta-Learning Framework for the Selection of Scaling Techniques"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2725-6527","authenticated-orcid":false,"given":"Lucas B. V.","family":"de Amorim","sequence":"first","affiliation":[{"name":"Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7714-2283","authenticated-orcid":false,"given":"George D. C.","family":"Cavalcanti","sequence":"additional","affiliation":[{"name":"Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9446-1040","authenticated-orcid":false,"given":"Rafael M. O.","family":"Cruz","sequence":"additional","affiliation":[{"name":"École de Technologie Supérieure, Université du Quebéc, Montreal, QC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(00)00112-4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10247-4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105524"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-82014-5_41"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.109924","article-title":"The choice of scaling technique matters for classification performance","volume":"133","author":"de Amorim","year":"2023","journal-title":"Appl. Soft Comput."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_2"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45547-1_16"},{"issue":"2","key":"ref8","first-page":"4760","article-title":"Automated data cleansing through meta-learning","volume-title":"Proc. AAAI","volume":"31","author":"Gemp"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA52953.2021.00194"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-022-06200-0"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012450327387"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/S0065-2458(08)60520-3","article-title":"The algorithm selection problem","volume":"15","author":"Rice","year":"1976","journal-title":"Adv. Comput."},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2016.04.003"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964726"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487629"},{"key":"ref16","first-page":"66","article-title":"TPOT: A tree-based pipeline optimization tool for automating machine learning","volume-title":"Proc. Workshop Automatic Machine Learning","author":"Olson"},{"key":"ref17","first-page":"1","article-title":"AlphaD3M: Machine learning pipeline synthesis","volume-title":"Proc. ICML AutoML Workshop","author":"Drori"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_6"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1023\/A:1019956318069"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2008.4634333"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.12.044"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2009.09.020"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2004.03.008"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000015879.28004.9b"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9354"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.12.025"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-012-0280-z"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3148435"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3165627"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1456650.1456656"},{"key":"ref31","first-page":"743","article-title":"Meta-learning by landmarking various learning algorithms","volume-title":"Proc. 7th ICML","author":"Pfahringer"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/34.990132"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/11526018_45"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.10.043"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5681-1"},{"key":"ref36","article-title":"Characterizing classification datasets: A study of meta-features for meta-learning","author":"Rivolli","year":"2018","journal-title":"arXiv:1808.10406"},{"key":"ref37","first-page":"4503","article-title":"MFE: Towards reproducible meta-feature extraction","volume":"21","author":"Alcoba\u010da","year":"2020","journal-title":"J. Mach. Learn. Research"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.108101"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67024-5_4"},{"key":"ref40","first-page":"66","article-title":"More robust concept learning using dynamically-variable bias","volume-title":"Proc. 4th Internat. Workshop Mach. Learn.","author":"Rendell"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-247-2.50006-1"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-57868-4_52"},{"key":"ref43","volume-title":"Machine Learning, Neural and Statistical Classification","volume":"4","author":"Michie","year":"1994"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tai.2000.889901"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0026680"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36182-0_14"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45372-5_32"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8640.1990.tb00298.x"},{"key":"ref49","first-page":"391","article-title":"Learning despite concept variation by finding structure in attribute-based data","volume-title":"Proc. ICML","author":"Perez"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1080\/03610927408827101"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/S1088-467X(99)00026-8"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1023\/a:1021713901879"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2005.65"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2018.12.020"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-023-00687-7"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2004.12.002"},{"issue":"4","key":"ref57","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1142\/S0218213001000647","article-title":"Model selection via meta-learning: A comparative study","volume":"10","author":"Alexandros","year":"2001","journal-title":"Int. J. Artif. Intell. Tools"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7687-1_543"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3831"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-016-0475-9"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-013-5387-y"},{"key":"ref62","first-page":"1","article-title":"AutoBagging: Learning to rank bagging workows with metalearning","volume-title":"Proc. CEUR Workshop","volume":"1998","author":"Pinto"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.04.008"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.35784\/iapgos.62"},{"key":"ref65","first-page":"729","article-title":"Study the influence of normalization\/transformation process on the accuracy of supervised classification","volume-title":"Proc. ICSSIT","author":"Raju"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7"},{"issue":"2","key":"ref67","first-page":"255","article-title":"KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework","volume":"17","author":"Alcal\u00e1-Fdez","year":"2011","journal-title":"J. Multiple-Valued Logic Soft Comput."},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17711-8_4"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/1830483.1830674"},{"issue":"3","key":"ref70","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1007\/bf00058655"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007662407062"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/3206.001.0001"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(89)90049-0"},{"key":"ref75","first-page":"423","article-title":"Generalized learning vector quantization","volume-title":"Proc. 8th ICNIPS","author":"Sato"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/34.588027"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(00)00150-3"},{"issue":"5","key":"ref78","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1016\/j.patcog.2007.10.015","article-title":"From dynamic classifier selection to dynamic ensemble selection","volume":"41","author":"Ko","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref79","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"Fernandez-Delgado","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020496"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.12.006"},{"issue":"5","key":"ref82","first-page":"4785","article-title":"Use of ID3 decision tree algorithm for placement prediction","volume":"6","author":"Bhatt","year":"2015","journal-title":"Int. J. Comput. Sci. Inform. Technol."},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.15276\/aait.05.2022.5"},{"issue":"5","key":"ref84","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1016\/j.patcog.2014.12.003","article-title":"META-DES: A dynamic ensemble selection framework using meta-learning","volume":"48","author":"Cruz","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.03.002"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"issue":"8","key":"ref87","first-page":"1","article-title":"DESlib: A dynamic ensemble selection library in Python","volume":"21","author":"Cruz","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489661"},{"key":"ref90","first-page":"152","article-title":"Should we really use post-hoc tests based on mean-ranks?","volume":"17","author":"Benavoli","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref91","doi-asserted-by":"crossref","DOI":"10.1201\/9781315139470","volume-title":"Classification and Regression Trees","author":"Breiman","year":"2017"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1145\/3347711"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177730103"},{"key":"ref94","first-page":"37","article-title":"Feature selection for classification: A review","volume-title":"Data Classification: Algorithms and Applications","author":"Tang","year":"2014"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3222047"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10908444\/10445017.pdf?arnumber=10445017","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T18:39:24Z","timestamp":1764959964000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10445017\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":95,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2024.3366615","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3]]}}}