{"id":"https://openalex.org/W4205155551","doi":"https://doi.org/10.1109/smc52423.2021.9659252","title":"A Novel Multi-class Classification Architecture Combining Population-based Sampling and Multi-expert Classifier for Imbalanced Data","display_name":"A Novel Multi-class Classification Architecture Combining Population-based Sampling and Multi-expert Classifier for Imbalanced Data","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W4205155551","doi":"https://doi.org/10.1109/smc52423.2021.9659252"},"language":"en","primary_location":{"id":"doi:10.1109/smc52423.2021.9659252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9659252","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5003805532","display_name":"Haochen Jiang","orcid":"https://orcid.org/0009-0003-4254-6765"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haochen Jiang","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079553918","display_name":"Ziqi Wei","orcid":"https://orcid.org/0000-0001-9402-8386"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqi Wei","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383252","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0001-5261-650X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091850357","display_name":"Xiulong Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiulong Yuan","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014645918","display_name":"Jun Chen","orcid":"https://orcid.org/0000-0002-8784-0314"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chen","raw_affiliation_strings":["Baidu University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu University, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5003805532"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.377,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.60656197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2164","last_page":"2169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9735000133514404,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7412275075912476},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6268264651298523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6220302581787109},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4887387752532959},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4448537528514862},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4305347502231598},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4140712022781372},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.400075763463974},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.059511929750442505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7412275075912476},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6268264651298523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6220302581787109},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4887387752532959},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4448537528514862},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4305347502231598},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4140712022781372},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.400075763463974},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.059511929750442505},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc52423.2021.9659252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9659252","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318547","display_name":"Baidu","ror":"https://ror.org/03vs3wt56"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W25086975","https://openalex.org/W85350352","https://openalex.org/W1591261915","https://openalex.org/W2072615238","https://openalex.org/W2076272581","https://openalex.org/W2083551746","https://openalex.org/W2104933073","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2461041754","https://openalex.org/W2626931877","https://openalex.org/W2913306795","https://openalex.org/W2963212406","https://openalex.org/W2994865507","https://openalex.org/W2998365469","https://openalex.org/W3000870854","https://openalex.org/W3014150937","https://openalex.org/W3027445710","https://openalex.org/W3035054804","https://openalex.org/W3115663295","https://openalex.org/W3120740533","https://openalex.org/W3155649056","https://openalex.org/W6601046002","https://openalex.org/W6603460400","https://openalex.org/W6773055845","https://openalex.org/W6787745904"],"related_works":["https://openalex.org/W2588198209","https://openalex.org/W1909006023","https://openalex.org/W4205824991","https://openalex.org/W3200723557","https://openalex.org/W4312713546","https://openalex.org/W2961085424","https://openalex.org/W2362195430","https://openalex.org/W2347494122","https://openalex.org/W2567983276","https://openalex.org/W2802298219"],"abstract_inverted_index":{"Training":[0],"a":[1,10,68,143],"classifier":[2],"based":[3],"on":[4],"imbalanced":[5,35,58,108],"data":[6,25,36,110,139,148,161],"set":[7,149],"is":[8,92],"considered":[9],"great":[11],"challenge":[12],"in":[13,38,137,146,159],"classification":[14,41,44,60],"tasks,":[15],"as":[16,125],"classifiers":[17],"are":[18,123],"often":[19],"\"biased\"":[20],"due":[21],"to":[22,56,80,94,129],"highly":[23],"skewed":[24],"distribution":[26],"and":[27,67,121,141,156,163],"overlapping":[28],"borderline":[29],"between":[30],"different":[31],"classes.":[32],"When":[33],"the":[34,39,43,63,72,76,82,87,89,96,101,113,126,130,133,166],"appears":[37],"multi-class":[40,59,109],"scenario,":[42],"difficulty":[45],"increases":[46],"exponentially.":[47],"In":[48,71],"this":[49],"paper,":[50],"we":[51,74,104],"propose":[52],"an":[53],"integrated":[54],"approach":[55],"handle":[57],"by":[61,152],"combining":[62],"population-based":[64],"sampling":[65,83],"method":[66],"multi-expert":[69],"classifier.":[70],"implementation,":[73],"choose":[75,105],"Ant":[77],"Colony":[78],"Optimization":[79],"realize":[81],"process.":[84],"As":[85],"for":[86,168],"classifier,":[88],"voting":[90],"mechanism":[91],"applied":[93],"intensify":[95],"weak":[97],"classifiers.":[98],"To":[99],"test":[100],"algorithm\u2019s":[102],"performance,":[103],"10":[106],"representative":[107],"sets":[111,140,162],"from":[112],"UCI":[114],"Machine":[115],"Learning":[116],"Repository.":[117],"G":[118,153],"\u2013":[119,154],"mean":[120],"mAUC":[122],"chosen":[124],"metrics.":[127],"According":[128],"experimental":[131],"results,":[132],"proposed":[134],"algorithm":[135],"dominates":[136],"8":[138],"gets":[142],"second":[144],"place":[145],"1":[147],"when":[150],"evaluated":[151],"mean,":[155],"ranks":[157],"first":[158],"3":[160],"top-3":[164],"among":[165],"most":[167],"mAUC.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
