{"id":"https://openalex.org/W2596124285","doi":"https://doi.org/10.3233/jifs-161062","title":"A case based method to predict optimal k value for k-NN algorithm","display_name":"A case based method to predict optimal k value for k-NN algorithm","publication_year":2017,"publication_date":"2017-03-14","ids":{"openalex":"https://openalex.org/W2596124285","doi":"https://doi.org/10.3233/jifs-161062","mag":"2596124285"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-161062","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-161062","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-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":null,"display_name":"Yang Zhongguo","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhongguo","raw_affiliation_strings":["Department of Computer, China University of Petroleum, Beijing, China","Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067065399","display_name":"Hongqi Li","orcid":"https://orcid.org/0000-0003-4898-4857"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Hongqi","raw_affiliation_strings":["Department of Computer, China University of Petroleum, Beijing, China","Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101627418","display_name":"Liping Zhu","orcid":"https://orcid.org/0000-0002-7841-5578"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu Liping","raw_affiliation_strings":["Department of Computer, China University of Petroleum, Beijing, China","Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103657745","display_name":"Liu Qiang","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu Qiang","raw_affiliation_strings":["Department of Computer, China University of Petroleum, Beijing, China","Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026401762","display_name":"Sikandar Ali","orcid":"https://orcid.org/0000-0002-2753-8615"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sikandar Ali","raw_affiliation_strings":["Department of Computer, China University of Petroleum, Beijing, China","Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Key Lab of Petroleum Data Mining, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067065399"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.02249085,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"33","issue":"1","first_page":"55","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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":0.9977999925613403,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/algorithm","display_name":"Algorithm","score":0.5925883054733276},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5803847908973694},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5739885568618774},{"id":"https://openalex.org/keywords/combing","display_name":"Combing","score":0.5362730622291565},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5281636118888855},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.48834583163261414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46387091279029846},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44782790541648865},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.43398451805114746},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.4225744605064392},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4125068187713623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39281120896339417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3142506778240204},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2941737771034241},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12429183721542358}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5925883054733276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5803847908973694},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5739885568618774},{"id":"https://openalex.org/C2778952367","wikidata":"https://www.wikidata.org/wiki/Q3491532","display_name":"Combing","level":2,"score":0.5362730622291565},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5281636118888855},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.48834583163261414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46387091279029846},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44782790541648865},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.43398451805114746},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.4225744605064392},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4125068187713623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39281120896339417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3142506778240204},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2941737771034241},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12429183721542358},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-161062","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-161062","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.75,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W21152038","https://openalex.org/W78907429","https://openalex.org/W1519451279","https://openalex.org/W1589492330","https://openalex.org/W1600984911","https://openalex.org/W1607561346","https://openalex.org/W1657060916","https://openalex.org/W1973030322","https://openalex.org/W2011809255","https://openalex.org/W2013916093","https://openalex.org/W2050913223","https://openalex.org/W2059154668","https://openalex.org/W2078772598","https://openalex.org/W2079100340","https://openalex.org/W2081475785","https://openalex.org/W2090136295","https://openalex.org/W2105223996","https://openalex.org/W2112702040","https://openalex.org/W2122111042","https://openalex.org/W2122379760","https://openalex.org/W2137839571","https://openalex.org/W2142827986","https://openalex.org/W2143913545","https://openalex.org/W2157686535","https://openalex.org/W2158457715","https://openalex.org/W2160675518","https://openalex.org/W2176705192","https://openalex.org/W2395028581","https://openalex.org/W3099414278","https://openalex.org/W4235792399","https://openalex.org/W4248760000"],"related_works":["https://openalex.org/W2382950503","https://openalex.org/W2374316087","https://openalex.org/W2351264995","https://openalex.org/W2359486762","https://openalex.org/W2374605473","https://openalex.org/W2366644843","https://openalex.org/W3181959032","https://openalex.org/W2063629221","https://openalex.org/W3119869160","https://openalex.org/W3207388504"],"abstract_inverted_index":{"The":[0,34,171],"k-nearest-neighbor":[1],"classifier":[2],"is":[3,13],"a":[4,21,37,62,80,85,101,106,157,185],"vital":[5],"algorithm.":[6],"In":[7,104],"practice,":[8],"the":[9,16,30,45,49,92,114,120,128,145,168,175,181,192],"choice":[10,50],"of":[11,36,51,79,100,124,184],"k":[12,122,154,194],"decided":[14],"by":[15,67,90,112,133],"cross-validation":[17,136],"method.":[18,170],"We":[19],"propose":[20],"new":[22,158],"method":[23],"for":[24,58,156,195,197],"neighborhood":[25],"size":[26],"selection":[27],"based":[28,143],"on":[29,144],"data":[31,38,81,102,125,159,186],"set":[32,39,109,126,148,187],"profile.":[33],"distribution":[35],"and":[40,61,96,119,149],"its":[41],"intrinsic":[42],"characteristics":[43],"are":[44,164],"fundamental":[46],"factors":[47],"to":[48,75,151,166],"k.":[52],"A":[53,138],"local":[54,70,93,176],"complexity":[55,63,71,94,177],"was":[56,65,88,110,131,141],"computed":[57],"each":[59],"example":[60],"profile":[64,95],"constructed":[66,111],"sorting":[68],"these":[69],"values":[72],"which":[73,130,188],"try":[74],"capture":[76],"inner":[77,182],"structure":[78,183],"set.":[82,103,160],"After":[83],"this,":[84],"feature":[86,115],"vector":[87,116],"built":[89],"combing":[91],"some":[97],"statistic":[98],"features":[99,178],"addition,":[105],"history":[107],"meta-data":[108,147],"using":[113,134],"as":[117,127],"attributes":[118],"optimum":[121,153,193],"value":[123,155],"label,":[129],"calculated":[132],"ten":[135],"methods.":[137],"predict":[139,152],"model":[140],"trained":[142],"historic":[146],"used":[150],"Some":[161],"exclusive":[162],"experiments":[163],"conducted":[165],"verify":[167],"proposed":[169],"results":[172],"shows":[173],"that":[174],"could":[179,189],"reflect":[180],"help":[190],"find":[191],"k-NN":[196],"different":[198],"domains.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}