{"id":"https://openalex.org/W3038008545","doi":"https://doi.org/10.3233/jifs-190821","title":"HIBoost: A hubness-aware ensemble learning algorithm for high-dimensional imbalanced data classification","display_name":"HIBoost: A hubness-aware ensemble learning algorithm for high-dimensional imbalanced data classification","publication_year":2020,"publication_date":"2020-06-24","ids":{"openalex":"https://openalex.org/W3038008545","doi":"https://doi.org/10.3233/jifs-190821","mag":"3038008545"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-190821","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-190821","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 &amp; 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":"https://openalex.org/A5076767274","display_name":"Qin Wu","orcid":"https://orcid.org/0000-0002-7470-8429"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Wu","raw_affiliation_strings":["College of Information Science and Engineering, Hunan University, Changsha, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Hunan University, Changsha, P.R. China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018617528","display_name":"Yaping Lin","orcid":"https://orcid.org/0000-0002-9052-9789"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaping Lin","raw_affiliation_strings":["College of Information Science and Engineering, Hunan University, Changsha, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Hunan University, Changsha, P.R. China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089907202","display_name":"Tuanfei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tuanfei Zhu","raw_affiliation_strings":["College of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China","institution_ids":["https://openalex.org/I198357462"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100333738","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0002-6327-5023"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Hunan University, Changsha, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Hunan University, Changsha, P.R. China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018617528"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.9279,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80251913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":"1","first_page":"133","last_page":"144"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9937000274658203,"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":0.9879000186920166,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.679262638092041},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6782859563827515},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6469926834106445},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6211704611778259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6086549162864685},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5989810228347778},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5674114227294922},{"id":"https://openalex.org/keywords/high-dimensional","display_name":"High dimensional","score":0.5129773020744324},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4706299304962158},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46867355704307556},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4594190716743469},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.43218228220939636},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37794822454452515},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3566267490386963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21199250221252441},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.09290695190429688}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.679262638092041},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6782859563827515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6469926834106445},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6211704611778259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6086549162864685},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5989810228347778},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5674114227294922},{"id":"https://openalex.org/C3019722297","wikidata":"https://www.wikidata.org/wiki/Q4440864","display_name":"High dimensional","level":2,"score":0.5129773020744324},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4706299304962158},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46867355704307556},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4594190716743469},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.43218228220939636},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37794822454452515},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3566267490386963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21199250221252441},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.09290695190429688},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-190821","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-190821","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 &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W592737779","https://openalex.org/W769353746","https://openalex.org/W1563938718","https://openalex.org/W1965895350","https://openalex.org/W1975664724","https://openalex.org/W1976035027","https://openalex.org/W1977405994","https://openalex.org/W1984323748","https://openalex.org/W2031798371","https://openalex.org/W2036181987","https://openalex.org/W2040010062","https://openalex.org/W2073645537","https://openalex.org/W2087240369","https://openalex.org/W2096945460","https://openalex.org/W2097477220","https://openalex.org/W2099454382","https://openalex.org/W2103614420","https://openalex.org/W2107138773","https://openalex.org/W2109826612","https://openalex.org/W2118978333","https://openalex.org/W2119498311","https://openalex.org/W2127017215","https://openalex.org/W2148143831","https://openalex.org/W2154706222","https://openalex.org/W2157133710","https://openalex.org/W2158896888","https://openalex.org/W2250875882","https://openalex.org/W2267568327","https://openalex.org/W2327900220","https://openalex.org/W2520599539","https://openalex.org/W2521888291","https://openalex.org/W2540352327","https://openalex.org/W2562319768","https://openalex.org/W2612835976","https://openalex.org/W2624913439","https://openalex.org/W2728217542","https://openalex.org/W2736435690","https://openalex.org/W2782578088","https://openalex.org/W2897482969","https://openalex.org/W2906183097","https://openalex.org/W3010805239","https://openalex.org/W4212883601"],"related_works":["https://openalex.org/W3162910294","https://openalex.org/W2488605529","https://openalex.org/W2364156185","https://openalex.org/W4398131260","https://openalex.org/W783379390","https://openalex.org/W1580499159","https://openalex.org/W2176851649","https://openalex.org/W3143121722","https://openalex.org/W2943557160","https://openalex.org/W2346063003"],"abstract_inverted_index":{"Learning":[0],"from":[1],"high-dimensional":[2,92,96,191],"imbalanced":[3,79,192],"data":[4,19,97,172,193],"is":[5],"prevalent":[6],"in":[7,82,112,141,173],"many":[8],"vital":[9],"real-world":[10],"applications,":[11],"which":[12,107],"poses":[13],"a":[14,131],"severe":[15],"challenge":[16],"to":[17,33,46,75,99,134,168,178],"traditional":[18,42],"mining":[20],"and":[21,105,123],"machine":[22],"learning":[23,44,80],"algorithms.":[24],"The":[25],"existing":[26],"works":[27],"generally":[28],"use":[29],"dimension":[30],"reduction":[31,55],"methods":[32],"deal":[34],"with":[35],"the":[36,48,58,65,78,90,101,120,136,142,149,170,180,196],"curse":[37],"of":[38,50,60,116,139,144,151,183,198],"dimensionality,":[39],"then":[40],"apply":[41],"imbalance":[43,163],"techniques":[45],"combat":[47],"problem":[49,81],"class":[51,162],"imbalance.":[52],"However,":[53],"dimensionality":[54],"may":[56],"cause":[57],"loss":[59],"useful":[61],"information,":[62],"especially":[63],"for":[64],"minority":[66],"classes.":[67],"This":[68],"paper":[69],"introduces":[70,130],"an":[71],"ensemble-based":[72],"method,":[73],"HIBoost,":[74],"directly":[76],"handle":[77],"high":[83,127],"dimensional":[84],"space.":[85],"HIBoost":[86,129,165],"takes":[87],"into":[88],"account":[89],"inherent":[91],"hubness":[93],"phenomenon,":[94],"i.e.,":[95],"tends":[98],"contain":[100],"singular":[102,121],"points":[103],"(hubs":[104],"anti-hubs)":[106],"frequently":[108],"or":[109],"rarely":[110],"occur":[111],"k":[113],"-nearest":[114],"neighbors":[115],"other":[117],"points.":[118],"For":[119,161],"hubs":[122],"anti-hubs":[124],"induced":[125],"by":[126],"dimension,":[128],"discount":[132],"factor":[133],"restrict":[135],"weight":[137],"growth":[138],"them":[140],"process":[143],"updating":[145],"weight,":[146],"so":[147,176],"that":[148],"risk":[150],"over":[152],"fitting":[153],"can":[154],"be":[155],"reduced":[156],"when":[157],"training":[158,171],"component":[159,184],"classifiers.":[160,185],"problem,":[164],"uses":[166],"SMOTE":[167],"balance":[169],"each":[174],"iteration":[175],"as":[177],"alleviate":[179],"prediction":[181],"bias":[182],"Experimental":[186],"results":[187],"based":[188],"on":[189],"sixteen":[190],"sets":[194],"demonstrate":[195],"effectiveness":[197],"HIBoost.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-02-06T02:01:19.302388","created_date":"2025-10-10T00:00:00"}
