{"id":"https://openalex.org/W2086397342","doi":"https://doi.org/10.1109/ijcnn.2012.6252836","title":"Class imbalance robust incremental LPSVM for data streams learning","display_name":"Class imbalance robust incremental LPSVM for data streams learning","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2086397342","doi":"https://doi.org/10.1109/ijcnn.2012.6252836","mag":"2086397342"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2012.6252836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","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/A5100394072","display_name":"Lei Zhu","orcid":"https://orcid.org/0000-0003-1685-7968"},"institutions":[{"id":"https://openalex.org/I872614749","display_name":"Unitec Institute of Technology","ror":"https://ror.org/01px84952","country_code":"NZ","type":"education","lineage":["https://openalex.org/I4387152882","https://openalex.org/I872614749"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Lei Zhu","raw_affiliation_strings":["Unitec Institute of Technology, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Unitec Institute of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I872614749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653125","display_name":"Shaoning Pang","orcid":"https://orcid.org/0000-0003-4651-4990"},"institutions":[{"id":"https://openalex.org/I872614749","display_name":"Unitec Institute of Technology","ror":"https://ror.org/01px84952","country_code":"NZ","type":"education","lineage":["https://openalex.org/I4387152882","https://openalex.org/I872614749"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Shaoning Pang","raw_affiliation_strings":["Unitec Institute of Technology, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Unitec Institute of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I872614749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389337","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0003-4970-2540"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105990176","display_name":"Abdolhossein Sarrafzadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I872614749","display_name":"Unitec Institute of Technology","ror":"https://ror.org/01px84952","country_code":"NZ","type":"education","lineage":["https://openalex.org/I4387152882","https://openalex.org/I872614749"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Abdolhossein Sarrafzadeh","raw_affiliation_strings":["Unitec Institute of Technology, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Unitec Institute of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I872614749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100394072"],"corresponding_institution_ids":["https://openalex.org/I872614749"],"apc_list":null,"apc_paid":null,"fwci":2.2737102,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90341446,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9986000061035156,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9986000061035156,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9980999827384949,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908000230789185,"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/computer-science","display_name":"Computer science","score":0.702063262462616},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6866862773895264},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.682936429977417},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6218486428260803},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.6203211545944214},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5905043482780457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5262638330459595},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49555790424346924},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48291704058647156},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48220503330230713},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.44282519817352295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4136374592781067}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702063262462616},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6866862773895264},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.682936429977417},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6218486428260803},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.6203211545944214},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5905043482780457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5262638330459595},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49555790424346924},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48291704058647156},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48220503330230713},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.44282519817352295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4136374592781067},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2012.6252836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1555269405","https://openalex.org/W1971542953","https://openalex.org/W2007160064","https://openalex.org/W2015800007","https://openalex.org/W2069231281","https://openalex.org/W2099435377","https://openalex.org/W2105531169","https://openalex.org/W2108807072","https://openalex.org/W2118978333","https://openalex.org/W2119191234","https://openalex.org/W2131163986","https://openalex.org/W2151833442","https://openalex.org/W2154299908","https://openalex.org/W2156415837","https://openalex.org/W2156909104","https://openalex.org/W2163381245","https://openalex.org/W2169937061","https://openalex.org/W2170487914","https://openalex.org/W2537717744","https://openalex.org/W6676485797"],"related_works":["https://openalex.org/W4307392573","https://openalex.org/W2802243998","https://openalex.org/W2736127210","https://openalex.org/W2329342202","https://openalex.org/W2574092225","https://openalex.org/W2161835057","https://openalex.org/W1521014365","https://openalex.org/W4200217704","https://openalex.org/W3208495060","https://openalex.org/W2740428142"],"abstract_inverted_index":{"Linear":[0],"Proximal":[1],"Support":[2],"Vector":[3],"Machines":[4],"(LPSVM),":[5],"like":[6],"decision":[7],"trees,":[8],"classic":[9,159],"SVM,":[10],"etc.":[11],"are":[12],"originally":[13],"not":[14,66],"equipped":[15],"to":[16,133,158],"handle":[17],"drifting":[18],"data":[19,34,78],"streams":[20,35],"that":[21,47,112,139],"exhibit":[22],"high":[23],"and":[24,94,119,127,163],"varying":[25],"degrees":[26],"of":[27,33,123,148],"class":[28,38,53,88,151],"imbalance.":[29,54],"For":[30],"online":[31,134],"classification":[32],"with":[36],"imbalanced":[37],"distribution,":[39],"we":[40,58],"propose":[41],"an":[42],"incremental":[43,160,164],"LPSVM":[44,120,165],"termed":[45],"DCIL-IncLPSVM":[46,85,115,142],"has":[48],"robust":[49],"learning":[50,105],"performance":[51],"under":[52],"In":[55],"doing":[56],"so,":[57],"simplify":[59],"a":[60,91],"weighted":[61],"LPSVM,":[62],"which":[63,153],"is":[64],"computationally":[65],"renewable,":[67],"as":[68],"several":[69],"core":[70],"matrices":[71],"multiplying":[72],"two":[73],"simple":[74,92],"weight":[75],"coefficients.":[76],"When":[77],"addition":[79],"and/or":[80],"retirement":[81],"occurs,":[82],"the":[83,104,113,140,146],"proposed":[84,114,141],"accommodates":[86],"current":[87],"imbalance":[89],"by":[90],"matrix":[93],"coefficient":[95],"updating,":[96],"meanwhile":[97],"ensures":[98],"no":[99],"discriminative":[100],"information":[101],"lost":[102],"throughout":[103],"process.":[106],"Experiments":[107],"on":[108],"benchmark":[109],"datasets":[110],"indicate":[111],"outperforms":[116],"batch":[117],"SVM":[118,161],"in":[121,145],"terms":[122],"F-measure,":[124],"relative":[125],"sensitivity":[126],"G-mean":[128],"metrics.":[129],"Moreover,":[130],"our":[131],"application":[132],"face":[135],"membership":[136],"authentication":[137],"shows":[138],"remains":[143],"effective":[144],"presence":[147],"highly":[149],"dynamic":[150],"imbalance,":[152],"usually":[154],"poses":[155],"serious":[156],"problems":[157],"(IncSVM)":[162],"(IncLPSVM).":[166]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}