{"id":"https://openalex.org/W2013409079","doi":"https://doi.org/10.1109/fskd.2010.5569116","title":"Fuzzy-rough k-nearest neighbor algorithm for imbalanced data sets learning","display_name":"Fuzzy-rough k-nearest neighbor algorithm for imbalanced data sets learning","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2013409079","doi":"https://doi.org/10.1109/fskd.2010.5569116","mag":"2013409079"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2010.5569116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569116","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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/A5089555942","display_name":"Hui Han","orcid":"https://orcid.org/0000-0003-3811-5682"},"institutions":[{"id":"https://openalex.org/I31683504","display_name":"Beijing Forestry University","ror":"https://ror.org/04xv2pc41","country_code":"CN","type":"education","lineage":["https://openalex.org/I1327237609","https://openalex.org/I31683504","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hui Han","raw_affiliation_strings":["School of Information Science and Technology, Beijing Forestry University, Beijing, China","School of Information Science and Technology, Beijing Forestry University, China#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Beijing Forestry University, Beijing, China","institution_ids":["https://openalex.org/I31683504"]},{"raw_affiliation_string":"School of Information Science and Technology, Beijing Forestry University, China#TAB#","institution_ids":["https://openalex.org/I31683504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059956497","display_name":"Binghuan Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binghuan Mao","raw_affiliation_strings":["School of Statistics, Central University of Finance and Economics, Beijing, China","[School of Statistics, Central University of Finance and Economics, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"School of Statistics, Central University of Finance and Economics, Beijing, China","institution_ids":["https://openalex.org/I137867983"]},{"raw_affiliation_string":"[School of Statistics, Central University of Finance and Economics, Beijing, China]","institution_ids":["https://openalex.org/I137867983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089555942"],"corresponding_institution_ids":["https://openalex.org/I31683504"],"apc_list":null,"apc_paid":null,"fwci":0.7418,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.71843473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1286","last_page":"1290"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6833524107933044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6685886979103088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5546624660491943},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5374596118927002},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.536124587059021},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.5222576260566711},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4900137484073639},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.48782995343208313},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4658872187137604},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4617045521736145},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3400745689868927}],"concepts":[{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6833524107933044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6685886979103088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5546624660491943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5374596118927002},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.536124587059021},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.5222576260566711},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4900137484073639},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.48782995343208313},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4658872187137604},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4617045521736145},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3400745689868927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2010.5569116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569116","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W1557923305","https://openalex.org/W1560208207","https://openalex.org/W1563938718","https://openalex.org/W1992795012","https://openalex.org/W2027654459","https://openalex.org/W2030832258","https://openalex.org/W2053724458","https://openalex.org/W2067594023","https://openalex.org/W2185093231","https://openalex.org/W2799061466","https://openalex.org/W2914019270","https://openalex.org/W3120740533","https://openalex.org/W4212771256","https://openalex.org/W4239875977","https://openalex.org/W6633571703","https://openalex.org/W7048602932"],"related_works":["https://openalex.org/W2392963705","https://openalex.org/W2107349454","https://openalex.org/W2382278777","https://openalex.org/W2353240132","https://openalex.org/W1587347718","https://openalex.org/W2375932290","https://openalex.org/W2978519593","https://openalex.org/W2102746356","https://openalex.org/W4390066334","https://openalex.org/W2096751418"],"abstract_inverted_index":{"Learning":[0],"from":[1],"imbalanced":[2,41],"data":[3,42,132],"sets":[4,43],"presents":[5,31],"a":[6,32],"new":[7,33,111],"challenge":[8],"to":[9,18,45,104],"machine":[10],"learning":[11,44],"community,":[12],"as":[13],"traditional":[14],"methods":[15],"are":[16],"biased":[17],"majority":[19,102],"classes":[20],"and":[21,66,75,85,96],"produce":[22],"poor":[23],"detection":[24],"rate":[25],"of":[26,50,63,87,91,101,119,129],"minority":[27,51,64,105,120],"classes.":[28],"This":[29],"paper":[30],"approach,":[34],"namely":[35],"fuzzy-rough":[36],"k-nearest":[37],"neighbor":[38],"algorithm":[39],"for":[40],"improve":[46],"the":[47,72,83,88,99,116,126,130],"classification":[48,117,127],"performance":[49,118,128],"class.":[52,106],"The":[53,80],"approach":[54,81,112],"defines":[55],"fuzzy":[56,68],"membership":[57],"function":[58],"that":[59,109],"is":[60],"in":[61],"favor":[62],"class":[65,103,121],"constructs":[67],"equivalent":[69],"relation":[70],"between":[71],"unlabeled":[73],"instance":[74,93],"its":[76],"k":[77],"nearest":[78,89],"neighbors.":[79],"takes":[82],"fuzziness":[84],"roughness":[86],"neighbors":[90],"an":[92],"into":[94],"consideration,":[95],"can":[97],"reduce":[98],"disturbance":[100],"Experiments":[107],"show":[108],"our":[110],"improves":[113],"not":[114],"only":[115],"more":[122],"effectively,":[123],"but":[124],"also":[125],"whole":[131],"set":[133],"comparing":[134],"with":[135],"other":[136],"methods.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}