{"id":"https://openalex.org/W4381542508","doi":"https://doi.org/10.1186/s40537-023-00738-z","title":"Threshold optimization and random undersampling for imbalanced credit card data","display_name":"Threshold optimization and random undersampling for imbalanced credit card data","publication_year":2023,"publication_date":"2023-05-06","ids":{"openalex":"https://openalex.org/W4381542508","doi":"https://doi.org/10.1186/s40537-023-00738-z"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-023-00738-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00738-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00738-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00738-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004094853","display_name":"Joffrey L. Leevy","orcid":"https://orcid.org/0000-0002-7079-7540"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joffrey L. Leevy","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018875253","display_name":"Justin Johnson","orcid":"https://orcid.org/0000-0003-3511-0624"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin M. Johnson","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047489766","display_name":"John Hancock","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Hancock","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089170562","display_name":"Taghi M. Khoshgoftaar","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taghi M. Khoshgoftaar","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004094853"],"corresponding_institution_ids":["https://openalex.org/I63772739"],"apc_list":{"value":2290,"currency":"USD","value_usd":2290},"apc_paid":{"value":2290,"currency":"USD","value_usd":2290},"fwci":6.4522,"has_fulltext":true,"cited_by_count":50,"citation_normalized_percentile":{"value":0.97444592,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"10","issue":"1","first_page":null,"last_page":null},"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9916999936103821,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9853000044822693,"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/undersampling","display_name":"Undersampling","score":0.9327086806297302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6953840851783752},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5646668076515198},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5110324621200562},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.45194318890571594},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4363337457180023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42310044169425964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4017806649208069},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3565930426120758},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3530593514442444},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22100421786308289}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.9327086806297302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953840851783752},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5646668076515198},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5110324621200562},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.45194318890571594},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4363337457180023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42310044169425964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4017806649208069},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3565930426120758},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3530593514442444},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22100421786308289},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-023-00738-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00738-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00738-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f8470606c8074b5ab96cacc7fd4e2643","is_oa":true,"landing_page_url":"https://doaj.org/article/f8470606c8074b5ab96cacc7fd4e2643","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 10, Iss 1, Pp 1-22 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-023-00738-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00738-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00738-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310801","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387"},{"id":"https://openalex.org/F4320317380","display_name":"Universidad del Atl\u00e1ntico","ror":"https://ror.org/05mm1w714"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381542508.pdf","grobid_xml":"https://content.openalex.org/works/W4381542508.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2163735391","https://openalex.org/W2230801863","https://openalex.org/W2295598076","https://openalex.org/W2521200999","https://openalex.org/W2594014086","https://openalex.org/W2618530766","https://openalex.org/W2734358244","https://openalex.org/W2767106145","https://openalex.org/W2800341536","https://openalex.org/W2899434936","https://openalex.org/W2911964244","https://openalex.org/W2990580840","https://openalex.org/W3001336289","https://openalex.org/W3005928523","https://openalex.org/W3006049599","https://openalex.org/W3024905798","https://openalex.org/W3044867970","https://openalex.org/W3094948551","https://openalex.org/W3164230923","https://openalex.org/W4200095224","https://openalex.org/W4200250298","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2109073422","https://openalex.org/W2887783772","https://openalex.org/W2101754595","https://openalex.org/W2534887053","https://openalex.org/W2026172757","https://openalex.org/W4249381695","https://openalex.org/W2080076470","https://openalex.org/W4389292014","https://openalex.org/W4293261997","https://openalex.org/W4312449311"],"abstract_inverted_index":{"Abstract":[0],"Output":[1],"thresholding":[2],"is":[3,75],"well-suited":[4],"for":[5,105],"addressing":[6],"class":[7,89,140],"imbalance,":[8],"since":[9],"the":[10,18,30,33,49,67,70,106,115,123,130,157],"technique":[11],"does":[12],"not":[13],"increase":[14,65,86],"dataset":[15],"size,":[16],"run":[17],"risk":[19],"of":[20,32,66,87,108,117,125,144,159],"discarding":[21],"important":[22],"instances,":[23],"or":[24],"modify":[25],"an":[26,64,78,85,109],"existing":[27],"learner.":[28],"Through":[29],"use":[31,116],"Credit":[34],"Card":[35],"Fraud":[36],"Detection":[37],"Dataset,":[38],"this":[39,160],"study":[40],"proposes":[41],"a":[42,138],"threshold":[43,111,132,146],"optimization":[44,147],"approach":[45],"that":[46,63,101,129],"factors":[47],"in":[48,80],"constraint":[50],"True":[51,56],"Positive":[52],"Rate":[53,58],"(TPR)":[54],"\u2265":[55],"Negative":[57],"(TNR).":[59],"Our":[60,142],"findings":[61],"indicate":[62],"Area":[68],"Under":[69],"Precision\u2013Recall":[71],"Curve":[72],"(AUPRC)":[73],"score":[74],"associated":[76],"with":[77,122],"improvement":[79],"threshold-based":[81],"classification":[82],"scores,":[83],"while":[84],"positive":[88],"prior":[90],"probability":[91],"causes":[92],"optimal":[93,110],"thresholds":[94],"to":[95],"increase.":[96],"In":[97],"addition,":[98],"we":[99,127],"discovered":[100],"best":[102],"overall":[103],"results":[104],"selection":[107],"are":[112],"obtained":[113],"without":[114],"Random":[118],"Undersampling":[119],"(RUS).":[120],"Furthermore,":[121],"exception":[124],"AUPRC,":[126],"established":[128],"default":[131],"yields":[133],"good":[134],"performance":[135],"scores":[136],"at":[137],"balanced":[139],"ratio.":[141],"evaluation":[143],"four":[145],"techniques,":[148],"eight":[149],"threshold-dependent":[150],"metrics,":[151],"and":[152],"two":[153],"threshold-agnostic":[154],"metrics":[155],"defines":[156],"uniqueness":[158],"research.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}