{"id":"https://openalex.org/W2019778169","doi":"https://doi.org/10.1080/095400996116839","title":"Error Correlation and Error Reduction in Ensemble Classifiers","display_name":"Error Correlation and Error Reduction in Ensemble Classifiers","publication_year":1996,"publication_date":"1996-12-01","ids":{"openalex":"https://openalex.org/W2019778169","doi":"https://doi.org/10.1080/095400996116839","mag":"2019778169"},"language":"en","primary_location":{"id":"doi:10.1080/095400996116839","is_oa":false,"landing_page_url":"https://doi.org/10.1080/095400996116839","pdf_url":null,"source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5084748531","display_name":"Kagan Tumer","orcid":"https://orcid.org/0009-0007-3809-7257"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"KAGAN TUMER","raw_affiliation_strings":["\n                   \n               Department of Electrical and Computer Engineering, University of Texas, Austin, TX, 78712-108 4, USA","Department of Electrical and Computer Engineering , University of Texas , Austin, TX, 78712-108 4, USA"],"affiliations":[{"raw_affiliation_string":"\n                   \n               Department of Electrical and Computer Engineering, University of Texas, Austin, TX, 78712-108 4, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Texas , Austin, TX, 78712-108 4, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103071668","display_name":"Joydeep Ghosh","orcid":"https://orcid.org/0000-0002-7366-3548"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"JOYDEEP GHOSH","raw_affiliation_strings":["\n                   \n               Department of Electrical and Computer Engineering, University of Texas, Austin, TX, 78712-108 4, USA","Department of Electrical and Computer Engineering , University of Texas , Austin, TX, 78712-108 4, USA"],"affiliations":[{"raw_affiliation_string":"\n                   \n               Department of Electrical and Computer Engineering, University of Texas, Austin, TX, 78712-108 4, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Texas , Austin, TX, 78712-108 4, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084748531"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":null,"fwci":11.3849,"has_fulltext":false,"cited_by_count":600,"citation_normalized_percentile":{"value":0.98575403,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"8","issue":"3-4","first_page":"385","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T10057","display_name":"Face and Expression Recognition","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976999759674072,"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/random-subspace-method","display_name":"Random subspace method","score":0.8241288661956787},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7794039249420166},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7133532166481018},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7034915685653687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6641702651977539},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.627156138420105},{"id":"https://openalex.org/keywords/cascading-classifiers","display_name":"Cascading classifiers","score":0.6223396062850952},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5062560439109802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4800109267234802},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47325947880744934},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14149653911590576}],"concepts":[{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.8241288661956787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7794039249420166},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7133532166481018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7034915685653687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6641702651977539},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.627156138420105},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.6223396062850952},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5062560439109802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4800109267234802},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47325947880744934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14149653911590576},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1080/095400996116839","is_oa":false,"landing_page_url":"https://doi.org/10.1080/095400996116839","pdf_url":null,"source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:elartu.tntu.edu.ua:lib/36653","is_oa":false,"landing_page_url":"http://elartu.tntu.edu.ua/handle/lib/36653","pdf_url":null,"source":{"id":"https://openalex.org/S4306401453","display_name":"ELARTU (Ternopil National Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I92130990","host_organization_name":"Ternopil Ivan Pul'uj National Technical University","host_organization_lineage":["https://openalex.org/I92130990"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Master Thesis"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.36.4465","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.36.4465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ftp://ftp.lans.ece.utexas.edu/pub/papers/tumer_consci96.ps.Z","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.89.5032","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.5032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://web.engr.oregonstate.edu/~ktumer/publications/files/tumer-ghosh_cs96.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W40337337","https://openalex.org/W51589798","https://openalex.org/W1481519903","https://openalex.org/W1502099172","https://openalex.org/W1527532036","https://openalex.org/W1588861010","https://openalex.org/W1622484071","https://openalex.org/W1969557815","https://openalex.org/W1980501707","https://openalex.org/W1992408997","https://openalex.org/W2006413922","https://openalex.org/W2029896651","https://openalex.org/W2031692264","https://openalex.org/W2034917891","https://openalex.org/W2040615655","https://openalex.org/W2048890562","https://openalex.org/W2084362125","https://openalex.org/W2096077802","https://openalex.org/W2102734279","https://openalex.org/W2104179665","https://openalex.org/W2109703216","https://openalex.org/W2110593694","https://openalex.org/W2112081648","https://openalex.org/W2114720696","https://openalex.org/W2124181495","https://openalex.org/W2124776405","https://openalex.org/W2128073546","https://openalex.org/W2133263698","https://openalex.org/W2135293965","https://openalex.org/W2136591887","https://openalex.org/W2141278204","https://openalex.org/W2145513251","https://openalex.org/W2148245374","https://openalex.org/W2149110629","https://openalex.org/W2150884987","https://openalex.org/W2152457075","https://openalex.org/W2158441306","https://openalex.org/W2164568552","https://openalex.org/W2169273134","https://openalex.org/W2250079085","https://openalex.org/W2485024998","https://openalex.org/W2485341146","https://openalex.org/W2912934387","https://openalex.org/W2914369697","https://openalex.org/W3026721701","https://openalex.org/W3084873685"],"related_works":["https://openalex.org/W2046975922","https://openalex.org/W2388864896","https://openalex.org/W1933712933","https://openalex.org/W2407804800","https://openalex.org/W2057416691","https://openalex.org/W2968660735","https://openalex.org/W4256395896","https://openalex.org/W2913388591","https://openalex.org/W2117265009","https://openalex.org/W2245276335"],"abstract_inverted_index":{"Using":[0],"an":[1,92],"ensemble":[2,93],"of":[3,6,28,106],"classifiers,":[4,111],"instead":[5],"a":[7,65],"single":[8],"classifier,":[9],"can":[10],"lead":[11],"to":[12,32,58,100,127,130],"improved":[13],"generalization.":[14],"The":[15],"gains":[16],"obtained":[17],"by":[18,25,36],"combining":[19,39,66],"however,":[20],"are":[21,98],"often":[22],"affected":[23],"more":[24,94],"the":[26,33,37,73,77,89,102,108,114],"selection":[27,51],"what":[29],"is":[30,42,117,135],"presented":[31],"combiner,":[34],"than":[35],"actual":[38],"method":[40],"that":[41,71,87],"chosen.":[43],"In":[44],"this":[45],"paper":[46],"we":[47,83],"focus":[48],"on":[49],"data":[50,116],"and":[52,104],"classifier":[53],"training":[54,115],"methods,":[55],"in":[56,91,118],"order":[57],""prepare"":[59],"classifiers":[60,90],"for":[61,68,75],"combining.":[62],"We":[63],"review":[64],"framework":[67],"classification":[69],"problems":[70],"quantifies":[72],"need":[74],"reducing":[76,107],"correlation":[78,109],"among":[79,110],"individual":[80],"classifiers.":[81],"Then,":[82],"discuss":[84],"several":[85],"methods":[86],"make":[88],"complementary.":[95],"Experimental":[96],"results":[97],"provided":[99],"illustrate":[101],"benefits":[103],"pitfalls":[105],"especially":[112],"when":[113],"limited":[119],"supply.":[120],"2":[121],"1":[122],"Introduction":[123],"A":[124],"classifier's":[125],"ability":[126],"meaningfully":[128],"respond":[129],"novel":[131],"patterns,":[132],"or":[133],"generalize,":[134],"perhaps":[136],"its":[137],"most":[138],"important":[139],"property":[140],"(Levin":[141],"et":[142],"al.,":[143],"1990;":[144],"Wolpert,":[145],"1990).":[146],"In...":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":19},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":15},{"year":2014,"cited_by_count":23},{"year":2013,"cited_by_count":17},{"year":2012,"cited_by_count":28}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}