{"id":"https://openalex.org/W2084226631","doi":"https://doi.org/10.1109/ijcnn.2013.6707016","title":"Characterization measures of ensemble systems using a meta-learning approach","display_name":"Characterization measures of ensemble systems using a meta-learning approach","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2084226631","doi":"https://doi.org/10.1109/ijcnn.2013.6707016","mag":"2084226631"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2013.6707016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038141799","display_name":"Regina R. Parente","orcid":null},"institutions":[{"id":"https://openalex.org/I94328231","display_name":"University of Rio Grande and Rio Grande Community College","ror":"https://ror.org/02sghbs34","country_code":"US","type":"education","lineage":["https://openalex.org/I94328231"]},{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR","US"],"is_corresponding":true,"raw_author_name":"Regina R Parente","raw_affiliation_strings":["Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","Inf. & Appl. Math. Dept., Fed. Univ. of Rio Grande do Norte (UFRN), Natal, Brazil"],"affiliations":[{"raw_affiliation_string":"Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152"]},{"raw_affiliation_string":"Inf. & Appl. Math. Dept., Fed. Univ. of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152","https://openalex.org/I94328231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019144108","display_name":"Anne M. P. Canuto","orcid":"https://orcid.org/0000-0002-3684-3814"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]},{"id":"https://openalex.org/I94328231","display_name":"University of Rio Grande and Rio Grande Community College","ror":"https://ror.org/02sghbs34","country_code":"US","type":"education","lineage":["https://openalex.org/I94328231"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Anne M P Canuto","raw_affiliation_strings":["Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","Inf. & Appl. Math. Dept., Fed. Univ. of Rio Grande do Norte (UFRN), Natal, Brazil"],"affiliations":[{"raw_affiliation_string":"Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152"]},{"raw_affiliation_string":"Inf. & Appl. Math. Dept., Fed. Univ. of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152","https://openalex.org/I94328231"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039883944","display_name":"Jo\u00e3o C. Xavier-J\u00fanior","orcid":"https://orcid.org/0000-0003-1517-2211"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]},{"id":"https://openalex.org/I94328231","display_name":"University of Rio Grande and Rio Grande Community College","ror":"https://ror.org/02sghbs34","country_code":"US","type":"education","lineage":["https://openalex.org/I94328231"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Joao C. Xavier","raw_affiliation_strings":["Universidade Federal do Rio Grande do Norte, Natal, RN, BR","Digital Metropolis Inst., Fed. Univ. of Rio Grande do Norte, Natal, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio Grande do Norte, Natal, RN, BR","institution_ids":["https://openalex.org/I35046152"]},{"raw_affiliation_string":"Digital Metropolis Inst., Fed. Univ. of Rio Grande do Norte, Natal, Brazil","institution_ids":["https://openalex.org/I94328231"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038141799"],"corresponding_institution_ids":["https://openalex.org/I35046152","https://openalex.org/I94328231"],"apc_list":null,"apc_paid":null,"fwci":1.9236,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88480902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"5769","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9253000020980835,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9233999848365784,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.8130127787590027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.77275550365448},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7403227090835571},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.698614239692688},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.6798352003097534},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5584368109703064},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5201176404953003},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49378570914268494},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44720470905303955},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09447190165519714}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.8130127787590027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77275550365448},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7403227090835571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.698614239692688},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.6798352003097534},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5584368109703064},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5201176404953003},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49378570914268494},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44720470905303955},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09447190165519714},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2013.6707016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W36364317","https://openalex.org/W1564069282","https://openalex.org/W1962838048","https://openalex.org/W1985789779","https://openalex.org/W1987458475","https://openalex.org/W2089213632","https://openalex.org/W2112076978","https://openalex.org/W2123504579","https://openalex.org/W2123604854","https://openalex.org/W2124096713","https://openalex.org/W2135293965","https://openalex.org/W2141408223","https://openalex.org/W2142334564","https://openalex.org/W2145680191","https://openalex.org/W2147216278","https://openalex.org/W2154225404","https://openalex.org/W2160567154","https://openalex.org/W2163212577","https://openalex.org/W2466512847","https://openalex.org/W2487087946","https://openalex.org/W2809054435","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4252731897","https://openalex.org/W6676769703"],"related_works":["https://openalex.org/W4376643315","https://openalex.org/W4324137541","https://openalex.org/W2900445707","https://openalex.org/W2091347716","https://openalex.org/W98577079","https://openalex.org/W4285741730","https://openalex.org/W1191482210","https://openalex.org/W4285046548","https://openalex.org/W4210302090","https://openalex.org/W3201464374"],"abstract_inverted_index":{"In":[0,23,49,131],"a":[1,20,28,36,85,95],"decision":[2,29,96],"making":[3],"process,":[4],"we":[5,134],"are":[6],"usually":[7],"oriented":[8],"to":[9,93,167],"take":[10],"into":[11],"consideration":[12],"all":[13],"the":[14,33,40,46,60,70,81,107,110,126,136,141,144,169,175],"relevant":[15],"features":[16],"(characteristics)":[17],"involved":[18],"in":[19,69,80,125,174],"specific":[21],"problem.":[22],"Machine":[24],"Learning,":[25],"for":[26,87,154],"instance,":[27],"is":[30,43,98,113,166],"made":[31],"through":[32,59],"use":[34,61,137],"of":[35,62,66,75,109,128,138,143,157,163,171,177],"learning":[37],"algorithm":[38],"and":[39,118,151,179],"characterization":[41],"process":[42],"represented":[44],"by":[45],"corresponding":[47],"datasets.":[48],"this":[50,132,164],"context,":[51],"classification":[52,67],"algorithms":[53],"can":[54,120],"be":[55],"applied,":[56],"individually":[57],"or":[58],"ensemble":[63,76,111,158,181],"systems":[64,77],"(combination":[65],"methods),":[68],"decision-making":[71],"process.":[72],"The":[73,160],"concept":[74],"has":[78],"emerged":[79],"last":[82],"decades":[83],"as":[84],"strategy":[86],"combining":[88],"independent":[89],"classifiers":[90],"(components),":[91],"aiming":[92],"provide":[94],"that":[97],"potentially":[99],"more":[100],"effective":[101],"than":[102],"any":[103],"single":[104],"component.":[105],"However,":[106],"design":[108,176],"structure":[112],"not":[114],"an":[115,122],"easy":[116],"task":[117],"it":[119],"have":[121],"important":[123],"impact":[124],"performance":[127],"these":[129],"systems.":[130,159,182],"paper,":[133],"investigate":[135],"meta-learning":[139,173],"on":[140],"selection":[142],"best":[145],"configuration":[146],"parameters":[147],"(learning":[148],"strategy,":[149],"size":[150],"individual":[152],"classifiers)":[153],"homogeneous":[155],"structures":[156],"main":[161],"aim":[162],"analysis":[165],"assess":[168],"effect":[170],"using":[172],"efficient":[178],"robust":[180]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
