{"id":"https://openalex.org/W2102174899","doi":"https://doi.org/10.1109/iri.2011.6009578","title":"Clustering-based binary-class classification for imbalanced data sets","display_name":"Clustering-based binary-class classification for imbalanced data sets","publication_year":2011,"publication_date":"2011-08-01","ids":{"openalex":"https://openalex.org/W2102174899","doi":"https://doi.org/10.1109/iri.2011.6009578","mag":"2102174899"},"language":"en","primary_location":{"id":"doi:10.1109/iri.2011.6009578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2011.6009578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Information Reuse & Integration","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114911427","display_name":"Chao Chen","orcid":"https://orcid.org/0000-0003-4649-4061"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA","Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036221136","display_name":"Mei\u2010Ling Shyu","orcid":"https://orcid.org/0000-0003-0902-0844"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei-Ling Shyu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA","Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145608581"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"384","last_page":"389"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9904000163078308,"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/T10057","display_name":"Face and Expression Recognition","score":0.9782999753952026,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7736921310424805},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6237016916275024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5904812812805176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5684553384780884},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5167726278305054},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49556219577789307},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.48863106966018677},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47153908014297485},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4678512215614319},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45725148916244507},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4536161422729492},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4427708387374878},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4241305887699127},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2645052969455719},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.20976737141609192}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7736921310424805},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6237016916275024},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5904812812805176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5684553384780884},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5167726278305054},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49556219577789307},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.48863106966018677},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47153908014297485},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4678512215614319},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45725148916244507},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4536161422729492},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4427708387374878},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4241305887699127},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2645052969455719},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.20976737141609192},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iri.2011.6009578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2011.6009578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Information Reuse & Integration","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W9305809","https://openalex.org/W1570448133","https://openalex.org/W1941659294","https://openalex.org/W1993220166","https://openalex.org/W2023240376","https://openalex.org/W2062903088","https://openalex.org/W2080919181","https://openalex.org/W2096945460","https://openalex.org/W2112076978","https://openalex.org/W2118978333","https://openalex.org/W2136903812","https://openalex.org/W2148143831","https://openalex.org/W2148661353","https://openalex.org/W2153677638","https://openalex.org/W6600378069","https://openalex.org/W6676769703","https://openalex.org/W6680202767","https://openalex.org/W6682783484"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W2149583853","https://openalex.org/W2143002539","https://openalex.org/W4293472652","https://openalex.org/W1120847856","https://openalex.org/W2130386332"],"abstract_inverted_index":{"In":[0,89],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,17,34,61,73,101,124],"new":[6],"clustering-based":[7],"binary-class":[8,18,28,126,136],"classification":[9,19,156,164,171],"framework":[10,165],"that":[11,161],"integrates":[12],"the":[13,23,43,47,64,68,77,80,107,142,147,154,169,176,182],"clustering":[14,44,62],"technique":[15,45],"into":[16,39,50,100],"approach":[20],"to":[21,32,53,56,122,152],"handle":[22],"imbalanced":[24,149],"data":[25,37,48,65,81,95,109,120,127,137,150,184],"sets.":[26],"A":[27],"classifier":[29],"is":[30],"designed":[31],"classify":[33],"set":[35,102,151,185],"of":[36,103],"instances":[38,49,66,82,96,110,121],"two":[40],"classes;":[41],"while":[42],"partitions":[46],"groups":[51,85],"according":[52],"their":[54],"similarity":[55],"each":[57,112],"other.":[58],"After":[59],"applying":[60],"algorithm,":[63],"within":[67],"same":[69],"group":[70,114],"usually":[71],"have":[72],"higher":[74],"similarity,":[75],"and":[76],"differences":[78],"among":[79],"between":[83],"different":[84],"should":[86],"be":[87],"larger.":[88],"our":[90,162],"proposed":[91,155,163],"framework,":[92],"all":[93,118],"negative":[94,104,108,113],"are":[97,115,139],"first":[98],"clustered":[99],"groups.":[105],"Next,":[106],"in":[111],"combined":[116],"with":[117,141],"positive":[119],"construct":[123],"balanced":[125,135],"set.":[128],"Finally,":[129],"subspace":[130,143,177],"models":[131],"trained":[132,145,180],"on":[133,146,181],"these":[134],"sets":[138],"integrated":[140],"model":[144],"original":[148,183],"form":[153],"model.":[157],"Experimental":[158],"results":[159],"demonstrate":[160],"performs":[166],"better":[167],"than":[168],"comparative":[170],"approaches":[172],"as":[173,175],"well":[174],"modeling":[178],"method":[179],"alone.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}