{"id":"https://openalex.org/W3109522940","doi":"https://doi.org/10.1109/icca51439.2020.9264517","title":"Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset","display_name":"Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset","publication_year":2020,"publication_date":"2020-10-09","ids":{"openalex":"https://openalex.org/W3109522940","doi":"https://doi.org/10.1109/icca51439.2020.9264517","mag":"3109522940"},"language":"en","primary_location":{"id":"doi:10.1109/icca51439.2020.9264517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca51439.2020.9264517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Control & Automation (ICCA)","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/A5065185843","display_name":"Haziqah Shamsudin","orcid":"https://orcid.org/0000-0003-3199-5752"},"institutions":[{"id":"https://openalex.org/I2800727921","display_name":"Hospital Pulau Pinang","ror":"https://ror.org/024g0n729","country_code":"MY","type":"healthcare","lineage":["https://openalex.org/I2800727921"]},{"id":"https://openalex.org/I139322472","display_name":"Universiti Sains Malaysia","ror":"https://ror.org/02rgb2k63","country_code":"MY","type":"education","lineage":["https://openalex.org/I139322472"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Haziqah Shamsudin","raw_affiliation_strings":["School of Computer Sciences, University of Science Malaysia, Georgetown, Pulau Pinang, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Computer Sciences, University of Science Malaysia, Georgetown, Pulau Pinang, Malaysia","institution_ids":["https://openalex.org/I2800727921","https://openalex.org/I139322472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006630819","display_name":"Umi Kalsom Yusof","orcid":"https://orcid.org/0000-0003-4358-7430"},"institutions":[{"id":"https://openalex.org/I139322472","display_name":"Universiti Sains Malaysia","ror":"https://ror.org/02rgb2k63","country_code":"MY","type":"education","lineage":["https://openalex.org/I139322472"]},{"id":"https://openalex.org/I2800727921","display_name":"Hospital Pulau Pinang","ror":"https://ror.org/024g0n729","country_code":"MY","type":"healthcare","lineage":["https://openalex.org/I2800727921"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Umi Kalsom Yusof","raw_affiliation_strings":["School of Computer Sciences, University of Science Malaysia, Georgetown, Pulau Pinang, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Computer Sciences, University of Science Malaysia, Georgetown, Pulau Pinang, Malaysia","institution_ids":["https://openalex.org/I2800727921","https://openalex.org/I139322472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046843082","display_name":"Andal Jayalakshmi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140655","display_name":"Jabatan Perkhidmatan Awam Malaysia","ror":"https://ror.org/04kpqhb39","country_code":"MY","type":"government","lineage":["https://openalex.org/I4210140655"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Andal Jayalakshmi","raw_affiliation_strings":["SanDisk Storage Malaysia Sdn. Bhd., Selatan, Penang"],"affiliations":[{"raw_affiliation_string":"SanDisk Storage Malaysia Sdn. Bhd., Selatan, Penang","institution_ids":["https://openalex.org/I4210140655"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018121324","display_name":"Mohd Nor Akmal Khalid","orcid":"https://orcid.org/0000-0002-7909-8869"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mohd Nor Akmal Khalid","raw_affiliation_strings":["School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan","institution_ids":["https://openalex.org/I177738480"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065185843"],"corresponding_institution_ids":["https://openalex.org/I139322472","https://openalex.org/I2800727921"],"apc_list":null,"apc_paid":null,"fwci":4.801,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.95880937,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"803","last_page":"808"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9787999987602234,"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"}},{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9571999907493591,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.9957236647605896},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.9694123268127441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7717527747154236},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6533269286155701},{"id":"https://openalex.org/keywords/credit-card-fraud","display_name":"Credit card fraud","score":0.621529221534729},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.556071400642395},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5177661180496216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4783439338207245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46227961778640747},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.43593716621398926},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.4336736798286438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3515338897705078},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.22649815678596497}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.9957236647605896},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.9694123268127441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7717527747154236},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6533269286155701},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.621529221534729},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.556071400642395},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5177661180496216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4783439338207245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46227961778640747},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.43593716621398926},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.4336736798286438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3515338897705078},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.22649815678596497},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icca51439.2020.9264517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca51439.2020.9264517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Control & Automation (ICCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W752888290","https://openalex.org/W1993220166","https://openalex.org/W2023639956","https://openalex.org/W2045049630","https://openalex.org/W2091007025","https://openalex.org/W2097521902","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2234492624","https://openalex.org/W2772947247","https://openalex.org/W2778227677","https://openalex.org/W2883528737","https://openalex.org/W2886330306","https://openalex.org/W2911964244","https://openalex.org/W2974243782","https://openalex.org/W2990772077","https://openalex.org/W2999086996","https://openalex.org/W3000055169","https://openalex.org/W3004756619","https://openalex.org/W3100774601","https://openalex.org/W6622294026","https://openalex.org/W6679745481","https://openalex.org/W6767152887","https://openalex.org/W6772968125"],"related_works":["https://openalex.org/W32988189","https://openalex.org/W4308469503","https://openalex.org/W2904737874","https://openalex.org/W80466363","https://openalex.org/W4389233021","https://openalex.org/W2399571531","https://openalex.org/W2947132063","https://openalex.org/W4390415670","https://openalex.org/W4288337828","https://openalex.org/W4312449311"],"abstract_inverted_index":{"Credit":[0],"card":[1],"fraud":[2,124,128],"is":[3,10,66,85,94,134,152,163],"a":[4,188],"serious":[5],"and":[6,49,92,119,146,158,184,192],"growing":[7],"problem.":[8,168],"It":[9],"becoming":[11],"more":[12],"challenging":[13],"with":[14,138,174],"an":[15],"issues":[16],"of":[17,24,46,76,80,110,117,149,182,197],"highly":[18],"imbalanced":[19,101,166],"class.":[20],"In":[21,88],"the":[22,74,81,95,108,115,123,127,144,147,150,178,180],"field":[23],"data":[25,32],"mining,":[26],"prediction":[27],"or":[28],"typically":[29],"known":[30],"as":[31],"classification":[33,111],"problem":[34],"involved":[35],"detecting":[36,122],"events.":[37],"Uncommon":[38],"events":[39,54],"are":[40],"hard":[41],"to":[42,61,71,106,136,142],"identify":[43],"on":[44],"account":[45],"their":[47],"inconsistency":[48],"casualness,":[50],"however,":[51],"misclassifying":[52],"rare":[53],"can":[55],"result":[56],"in":[57,100,121,195],"heavy":[58],"costs.":[59],"Thus,":[60],"overcome":[62,72],"this":[63],"issues,":[64],"it":[65],"suggested":[67],"by":[68],"few":[69],"researches":[70],"at":[73],"stage":[75],"pre-processing":[77,82],"itself.":[78],"One":[79],"methods":[83],"available":[84],"sampling":[86,89],"methods.":[87],"methods,":[90],"oversampling":[91,132,183],"undersampling":[93,120,140,185],"most":[96],"widely":[97],"used":[98],"techniques":[99,133,141,186],"data.":[102],"This":[103],"paper":[104],"try":[105],"investigate":[107],"performance":[109,148,159],"model":[112,151],"when":[113],"combining":[114],"method":[116],"oversamplings":[118],"cases":[125],"from":[126],"detection":[129],"dataset.":[130],"Few":[131],"selected":[135,161],"combine":[137],"random":[139,155],"undergo":[143],"process":[145],"evaluate":[153],"using":[154],"forest":[156],"classifier":[157],"measure":[160],"that":[162],"suitable":[164],"for":[165],"class":[167],"The":[169],"results":[170],"obtained":[171],"then":[172],"compared":[173],"previous":[175],"literature.":[176],"From":[177],"results,":[179],"combination":[181],"gives":[187],"better":[189],"precision,":[190],"recall":[191],"F1-Measure":[193],"value":[194],"average":[196],"0.80%.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":8}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}