{"id":"https://openalex.org/W2128152410","doi":"https://doi.org/10.1109/ijcnn.2003.1223406","title":"An ensemble of classifiers approach for the missing feature problem","display_name":"An ensemble of classifiers approach for the missing feature problem","publication_year":2004,"publication_date":"2004-03-02","ids":{"openalex":"https://openalex.org/W2128152410","doi":"https://doi.org/10.1109/ijcnn.2003.1223406","mag":"2128152410"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","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/A5103102771","display_name":"Stefanie Krause","orcid":"https://orcid.org/0000-0002-1271-7514"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"S. Krause","raw_affiliation_strings":["Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","[Dept. of Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA]"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","institution_ids":["https://openalex.org/I44265643"]},{"raw_affiliation_string":"[Dept. of Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA]","institution_ids":["https://openalex.org/I44265643"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025314990","display_name":"Robi Polikar","orcid":"https://orcid.org/0000-0002-2739-4228"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Polikar","raw_affiliation_strings":["Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","[Dept. of Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA]"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","institution_ids":["https://openalex.org/I44265643"]},{"raw_affiliation_string":"[Dept. of Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA]","institution_ids":["https://openalex.org/I44265643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103102771"],"corresponding_institution_ids":["https://openalex.org/I44265643"],"apc_list":null,"apc_paid":null,"fwci":2.6982,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.91068557,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"553","last_page":"558"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9955999851226807,"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":0.9955999851226807,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9925000071525574,"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/T12676","display_name":"Machine Learning and ELM","score":0.9865000247955322,"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/missing-data","display_name":"Missing data","score":0.7432160377502441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7122253179550171},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6231981515884399},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6033065915107727},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.5378823280334473},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5372329354286194},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5280126929283142},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.514393150806427},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.4570912718772888},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44390103220939636},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39848485589027405},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.35162755846977234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1737157106399536}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7432160377502441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122253179550171},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6231981515884399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6033065915107727},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.5378823280334473},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5372329354286194},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5280126929283142},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.514393150806427},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4570912718772888},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44390103220939636},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39848485589027405},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.35162755846977234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1737157106399536},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2003.1223406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4300000071525574,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1605688901","https://openalex.org/W1985669629","https://openalex.org/W1988790447","https://openalex.org/W2035044274","https://openalex.org/W2084812512","https://openalex.org/W2093825590","https://openalex.org/W2100206501","https://openalex.org/W2103753221","https://openalex.org/W2110873266","https://openalex.org/W2130867619","https://openalex.org/W2135293965","https://openalex.org/W2144847675","https://openalex.org/W2151779605","https://openalex.org/W2158275940","https://openalex.org/W2160767978","https://openalex.org/W2610550445","https://openalex.org/W4239390603","https://openalex.org/W4285719527","https://openalex.org/W6675244696","https://openalex.org/W6681673332","https://openalex.org/W6682706280"],"related_works":["https://openalex.org/W1981866886","https://openalex.org/W1964832275","https://openalex.org/W2389865566","https://openalex.org/W2052615004","https://openalex.org/W2407804800","https://openalex.org/W2197698372","https://openalex.org/W2388864896","https://openalex.org/W2888937984","https://openalex.org/W2046975922","https://openalex.org/W2031173026"],"abstract_inverted_index":{"A":[0],"new":[1,151,169],"learning":[2,143],"algorithm":[3,14,177,186],"is":[4,53,76,154],"introduced":[5],"that":[6,46,64,87,153,159],"can":[7,109,127],"accommodate":[8],"data":[9,167],"with":[10,28,130,195],"missing":[11,132,181,202],"features.":[12,37,133],"The":[13,21,38,134,184],"uses":[15],"an":[16,47],"ensemble":[17,25],"of":[18,31,35,42,50,92,101,124,199],"classifiers":[19,22],"approach.":[20],"in":[23,54,61,71,77,140,203],"the":[24,32,43,51,58,72,102,105,121,131,141,174,180,200,204],"are":[26,65,116],"trained":[27],"random":[29],"subsets":[30],"total":[33],"number":[34,91,123],"available":[36],"approach":[39,136],"takes":[40],"advantage":[41],"basic":[44],"assumption":[45,75],"unknown":[48],"subset":[49],"features":[52,70,115,201],"fact":[55],"adequate":[56],"for":[57,80,178],"classification,":[59],"or":[60],"other":[62],"words,":[63],"redundant,":[66],"and":[67],"possibly":[68],"irrelevant":[69],"data.":[73,208],"This":[74],"general":[78],"true":[79],"most":[81],"practical":[82],"applications.":[83],"We":[84,171],"empirically":[85],"show":[86],"if":[88,113],"a":[89,95],"certain":[90],"networks":[93,126],"produce":[94],"particular":[96],"classification":[97,107],"performance":[98,108,190],"using":[99],"all":[100],"features,":[103],"then":[104],"same":[106,122],"be":[110,128],"reached":[111],"even":[112,164],"some":[114],"missing,":[117],"as":[118,120],"long":[119],"usable":[125],"generated":[129],"proposed":[135,185],"has":[137],"its":[138],"roots":[139],"incremental":[142],"algorithm,":[144],"Learn/sup":[145,175],"++/":[146,176],"which":[147],"seeks":[148],"to":[149,197],"learn":[150],"information":[152],"provided":[155],"by":[156],"additional":[157],"datasets":[158],"may":[160],"later":[161],"become":[162],"available,":[163],"when":[165],"such":[166],"introduce":[168],"classes.":[170],"have":[172],"modified":[173],"addressing":[179],"feature":[182],"problem.":[183],"showed":[187],"surprisingly":[188],"remarkable":[189],"on":[191],"three":[192],"real-world":[193],"applications,":[194],"up":[196],"10%":[198],"validation":[205],"/":[206],"field":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
