{"id":"https://openalex.org/W3135092014","doi":"https://doi.org/10.1155/2021/5520990","title":"A Survey of <i>k</i> Nearest Neighbor Algorithms for Solving the Class Imbalanced Problem","display_name":"A Survey of <i>k</i> Nearest Neighbor Algorithms for Solving the Class Imbalanced Problem","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3135092014","doi":"https://doi.org/10.1155/2021/5520990","mag":"3135092014"},"language":"en","primary_location":{"id":"doi:10.1155/2021/5520990","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5520990","pdf_url":"https://downloads.hindawi.com/journals/wcmc/2021/5520990.pdf","source":{"id":"https://openalex.org/S235346","display_name":"Wireless Communications and Mobile Computing","issn_l":"1530-8669","issn":["1530-8669","1530-8677"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wireless Communications and Mobile Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/wcmc/2021/5520990.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101610048","display_name":"Bo Sun","orcid":"https://orcid.org/0000-0003-2142-8869"},"institutions":[{"id":"https://openalex.org/I74485261","display_name":"Shandong Agricultural University","ror":"https://ror.org/02ke8fw32","country_code":"CN","type":"education","lineage":["https://openalex.org/I74485261"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Shandong Agricultural University, China"],"raw_orcid":"https://orcid.org/0000-0003-2142-8869","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Shandong Agricultural University, China","institution_ids":["https://openalex.org/I74485261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100367987","display_name":"Haiyan Chen","orcid":"https://orcid.org/0000-0002-8565-6417"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haiyan Chen","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China"],"raw_orcid":"https://orcid.org/0000-0002-8565-6417","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100367987","https://openalex.org/A5101610048"],"corresponding_institution_ids":["https://openalex.org/I74485261","https://openalex.org/I9842412"],"apc_list":{"value":2300,"currency":"USD","value_usd":2550},"apc_paid":{"value":2300,"currency":"USD","value_usd":2550},"fwci":2.081,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.88806007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9527999758720398,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9139000177383423,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.802064061164856},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7730741500854492},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.635003387928009},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.533941924571991},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5323596000671387},{"id":"https://openalex.org/keywords/best-bin-first","display_name":"Best bin first","score":0.5262248516082764},{"id":"https://openalex.org/keywords/nearest-neighbor-chain-algorithm","display_name":"Nearest-neighbor chain algorithm","score":0.43729168176651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31715792417526245},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.07954329252243042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.802064061164856},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7730741500854492},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.635003387928009},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.533941924571991},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5323596000671387},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.5262248516082764},{"id":"https://openalex.org/C102164700","wikidata":"https://www.wikidata.org/wiki/Q17162702","display_name":"Nearest-neighbor chain algorithm","level":5,"score":0.43729168176651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31715792417526245},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.07954329252243042},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/5520990","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5520990","pdf_url":"https://downloads.hindawi.com/journals/wcmc/2021/5520990.pdf","source":{"id":"https://openalex.org/S235346","display_name":"Wireless Communications and Mobile Computing","issn_l":"1530-8669","issn":["1530-8669","1530-8677"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wireless Communications and Mobile Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b3009c5e65ad4984a65fed618b5ae2be","is_oa":false,"landing_page_url":"https://doaj.org/article/b3009c5e65ad4984a65fed618b5ae2be","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wireless Communications and Mobile Computing, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/5520990","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5520990","pdf_url":"https://downloads.hindawi.com/journals/wcmc/2021/5520990.pdf","source":{"id":"https://openalex.org/S235346","display_name":"Wireless Communications and Mobile Computing","issn_l":"1530-8669","issn":["1530-8669","1530-8677"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wireless Communications and Mobile Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G4793002741","display_name":null,"funder_award_id":"ZR2018QF002","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3135092014.pdf","grobid_xml":"https://content.openalex.org/works/W3135092014.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W127422473","https://openalex.org/W385566662","https://openalex.org/W627502383","https://openalex.org/W1533320424","https://openalex.org/W1974825407","https://openalex.org/W1992829486","https://openalex.org/W2027739797","https://openalex.org/W2085661130","https://openalex.org/W2087240369","https://openalex.org/W2098373434","https://openalex.org/W2098994397","https://openalex.org/W2118978333","https://openalex.org/W2138181354","https://openalex.org/W2148143831","https://openalex.org/W2149381612","https://openalex.org/W2189353026","https://openalex.org/W2331846255","https://openalex.org/W2462401346","https://openalex.org/W2512691369","https://openalex.org/W2566546024","https://openalex.org/W2590761734","https://openalex.org/W2624600450","https://openalex.org/W2707074415","https://openalex.org/W2756848027","https://openalex.org/W2757120799","https://openalex.org/W2792744510","https://openalex.org/W2800242529","https://openalex.org/W2900688725","https://openalex.org/W2966679659","https://openalex.org/W2991519556","https://openalex.org/W2999592897","https://openalex.org/W2999899884","https://openalex.org/W4212863985"],"related_works":["https://openalex.org/W2182477562","https://openalex.org/W2375128115","https://openalex.org/W2148008870","https://openalex.org/W2169618946","https://openalex.org/W2381195555","https://openalex.org/W1558159560","https://openalex.org/W2011582495","https://openalex.org/W2519241726","https://openalex.org/W4297819076","https://openalex.org/W1671890395"],"abstract_inverted_index":{"k":[0,4,30,103,155,173],"nearest":[1],"neighbor":[2],"(":[3],"NN)":[5],"is":[6,105,158],"a":[7,131,159,182],"simple":[8],"and":[9,25,45,60,91,145,193,195],"widely":[10],"used":[11],"classifier;":[12],"it":[13],"can":[14],"achieve":[15],"comparable":[16],"performance":[17,124],"with":[18],"more":[19,88,93],"complex":[20],"classifiers":[21],"including":[22],"decision":[23,143],"tree":[24,144],"artificial":[26,146],"neural":[27,147],"network.":[28],"Therefore,":[29],"NN":[31,104,174],"has":[32,115],"been":[33],"listed":[34],"as":[35,57],"one":[36],"of":[37,185],"the":[38,49,63,109,112,135,176],"top":[39],"10":[40],"algorithms":[41],"in":[42,52],"machine":[43],"learning":[44],"data":[46],"mining.":[47],"On":[48],"other":[50,100],"hand,":[51],"many":[53,170],"classification":[54],"problems,":[55],"such":[56],"medical":[58],"diagnosis":[59],"intrusion":[61],"detection,":[62],"collected":[64],"training":[65,113],"sets":[66],"are":[67,78,92,140,204],"usually":[68,86],"class":[69,72,118,132],"imbalanced.":[70],"In":[71,128],"imbalanced":[73,126,133],"data,":[74],"although":[75],"positive":[76,84],"examples":[77,85],"heavily":[79],"outnumbered":[80],"by":[81],"negative":[82,96],"ones,":[83],"carry":[87],"meaningful":[89],"information":[90],"important":[94],"than":[95],"examples.":[97],"Similar":[98],"to":[99,121,142,189],"classical":[101],"classifiers,":[102],"also":[106],"proposed":[107],"under":[108,130],"assumption":[110],"that":[111,139],"set":[114],"approximately":[116],"balanced":[117],"distribution,":[119],"leading":[120],"its":[122],"unsatisfactory":[123],"on":[125],"data.":[127],"addition,":[129],"scenario,":[134],"global":[136],"resampling":[137],"strategies":[138],"suitable":[141],"network":[148],"often":[149],"do":[150],"not":[151],"work":[152],"well":[153],"for":[154,172],"NN,":[156],"which":[157],"local":[160],"information\u2010oriented":[161],"classifier.":[162],"To":[163],"solve":[164],"this":[165],"problem,":[166],"researchers":[167],"have":[168],"conducted":[169],"works":[171,187],"over":[175],"past":[177],"decade.":[178],"This":[179],"paper":[180],"presents":[181],"comprehensive":[183],"survey":[184],"these":[186],"according":[188],"their":[190,197],"different":[191],"perspectives":[192],"analyzes":[194],"compares":[196],"characteristics.":[198],"At":[199],"last,":[200],"several":[201],"future":[202],"directions":[203],"pointed":[205],"out.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2021-03-15T00:00:00"}