{"id":"https://openalex.org/W3005523295","doi":"https://doi.org/10.1145/3377713.3377733","title":"A Fuzzy Consensus Clustering Based Undersampling Approach for Class Imbalanced Learning","display_name":"A Fuzzy Consensus Clustering Based Undersampling Approach for Class Imbalanced Learning","publication_year":2019,"publication_date":"2019-12-20","ids":{"openalex":"https://openalex.org/W3005523295","doi":"https://doi.org/10.1145/3377713.3377733","mag":"3005523295"},"language":"en","primary_location":{"id":"doi:10.1145/3377713.3377733","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence","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/A5100663712","display_name":"Xiaokang Wang","orcid":"https://orcid.org/0000-0001-9442-5648"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaokang Wang","raw_affiliation_strings":["School of Economics and, Management, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and, Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101791241","display_name":"Huiwen Wang","orcid":"https://orcid.org/0000-0001-6207-840X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiwen Wang","raw_affiliation_strings":["School of Economics and, Management, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and, Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067621155","display_name":"Dexiang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dexiang Wu","raw_affiliation_strings":["School of Economics and, Management, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and, Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100324203","display_name":"Yihui Wang","orcid":"https://orcid.org/0000-0003-2739-1403"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yihui Wang","raw_affiliation_strings":["Institute for Social and Economic, Research and Policy, Columbia University, New York, USA"],"affiliations":[{"raw_affiliation_string":"Institute for Social and Economic, Research and Policy, Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101510785","display_name":"Rui Zhou","orcid":"https://orcid.org/0000-0003-2476-1130"},"institutions":[{"id":"https://openalex.org/I917184967","display_name":"Bank of China","ror":"https://ror.org/02mt4s337","country_code":"CN","type":"other","lineage":["https://openalex.org/I917184967"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhou","raw_affiliation_strings":["Hua Xia Bank, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Hua Xia Bank, Beijing, China","institution_ids":["https://openalex.org/I917184967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100663712"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67760188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"133","last_page":"137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9689000248908997,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9593999981880188,"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/undersampling","display_name":"Undersampling","score":0.8900167942047119},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.770171046257019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.653571367263794},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5768760442733765},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5678874850273132},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5628817081451416},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.560673177242279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5336604118347168},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4372008442878723},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41528022289276123},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4129719138145447},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.2863551378250122},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24311718344688416}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.8900167942047119},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.770171046257019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.653571367263794},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5768760442733765},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5678874850273132},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5628817081451416},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.560673177242279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5336604118347168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4372008442878723},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41528022289276123},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4129719138145447},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2863551378250122},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24311718344688416},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3377713.3377733","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1836353685","https://openalex.org/W1990063425","https://openalex.org/W1996523702","https://openalex.org/W2087240369","https://openalex.org/W2128965734","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2562319768","https://openalex.org/W2592842236","https://openalex.org/W2612634114","https://openalex.org/W2791146007","https://openalex.org/W2911830614","https://openalex.org/W2919821184","https://openalex.org/W6605866443"],"related_works":["https://openalex.org/W2588528840","https://openalex.org/W2199594781","https://openalex.org/W2767663474","https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2744974730","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W3192757256","https://openalex.org/W4388110928"],"abstract_inverted_index":{"The":[0,73,121],"class":[1,43,102,111],"imbalance":[2],"problem":[3],"is":[4,13,67,76,127],"widely":[5],"studied":[6],"in":[7,15,69,86],"the":[8,46,59,79,83,87,95,100,107,116,124,146],"machine":[9],"learning":[10],"community,":[11],"it":[12],"present":[14],"many":[16],"real":[17,130,157],"world":[18,131],"applications":[19],"such":[20],"as":[21],"spam":[22],"filtering,":[23],"anomaly":[24],"detection":[25],"and":[26],"medical":[27],"diagnosis.":[28],"In":[29,104],"this":[30,105],"paper,":[31],"we":[32],"propose":[33],"an":[34],"adaptive":[35],"fuzzy":[36,147],"c-means":[37],"based":[38,142,150],"consensus":[39,148],"clustering":[40,141,149],"approach":[41,57],"for":[42,63,156],"imbalanced":[44,159],"learning,":[45],"number":[47],"of":[48,123],"base":[49,65],"clusters":[50],"are":[51,91,113,119],"determined":[52,68],"through":[53],"a":[54,70],"balancing":[55],"optimization":[56],"while":[58,115],"initial":[60],"starting":[61],"points":[62],"each":[64],"partition":[66,75,90],"sequential":[71],"manner.":[72],"final":[74,88],"constructed":[77],"via":[78],"co-association":[80],"matrix.":[81],"Finally,":[82],"center":[84],"samples":[85,112,118],"cluster":[89],"selected":[92],"to":[93,139],"form":[94],"reduced":[96],"data":[97,132],"set":[98],"with":[99,129],"minority":[101],"samples.":[103],"way,":[106],"most":[108],"representative":[109],"majority":[110],"chosen":[114],"boundary":[117],"eliminated.":[120],"validity":[122],"proposed":[125],"method":[126,152],"tested":[128],"sets":[133],"which":[134],"demonstrates":[135],"superior":[136],"performance":[137],"compared":[138],"other":[140],"re-sampling":[143],"schemes.":[144],"Thus,":[145],"under-sampling":[151],"can":[153],"be":[154],"used":[155],"life":[158],"problems.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}