{"id":"https://openalex.org/W4410052034","doi":"https://doi.org/10.1186/s40537-025-01171-0","title":"Evaluating techniques from low-shot learning on traditional imbalanced classification tasks","display_name":"Evaluating techniques from low-shot learning on traditional imbalanced classification tasks","publication_year":2025,"publication_date":"2025-05-03","ids":{"openalex":"https://openalex.org/W4410052034","doi":"https://doi.org/10.1186/s40537-025-01171-0"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-025-01171-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01171-0","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01171-0","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","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/s40537-025-01171-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116057760","display_name":"Preston Billion\u2013Polak","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":true,"raw_author_name":"Preston Billion-Polak","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA"],"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"],"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":2,"corresponding_author_ids":["https://openalex.org/A5116057760"],"corresponding_institution_ids":["https://openalex.org/I63772739"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":5.3159,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94894835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"12","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":0.9991999864578247,"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":0.9991999864578247,"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":0.9926999807357788,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9478999972343445,"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":0.8558857440948486},{"id":"https://openalex.org/keywords/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.7158743739128113},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6397587060928345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5895366072654724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5883423089981079},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32019639015197754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8558857440948486},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.7158743739128113},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6397587060928345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5895366072654724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5883423089981079},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32019639015197754},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-025-01171-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01171-0","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01171-0","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","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:9a579da336f348fba96c5218cb98fe1c","is_oa":true,"landing_page_url":"https://doaj.org/article/9a579da336f348fba96c5218cb98fe1c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 12, Iss 1, Pp 1-21 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-025-01171-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01171-0","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01171-0","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"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/W4410052034.pdf","grobid_xml":"https://content.openalex.org/works/W4410052034.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1966716734","https://openalex.org/W2056132907","https://openalex.org/W2107686700","https://openalex.org/W2118978333","https://openalex.org/W2148143831","https://openalex.org/W2295598076","https://openalex.org/W2612634114","https://openalex.org/W2612690371","https://openalex.org/W2782767340","https://openalex.org/W2899434936","https://openalex.org/W2911964244","https://openalex.org/W2936503027","https://openalex.org/W2962200422","https://openalex.org/W3006090163","https://openalex.org/W3086638135","https://openalex.org/W3100100256","https://openalex.org/W3120940860","https://openalex.org/W3156894194","https://openalex.org/W3163087324","https://openalex.org/W3172761455","https://openalex.org/W3201933410","https://openalex.org/W4235456164","https://openalex.org/W4283827192","https://openalex.org/W4297900628","https://openalex.org/W4312674672","https://openalex.org/W4366308790","https://openalex.org/W4376129227","https://openalex.org/W4380685430","https://openalex.org/W4385195679","https://openalex.org/W4388788959","https://openalex.org/W4390511453","https://openalex.org/W4390547629","https://openalex.org/W4392617925","https://openalex.org/W4393161202"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,7,12,26,85,148],"machine":[3],"learning":[4,29,171],"have":[5,40],"resulted":[6],"techniques":[8],"that":[9,45,168],"are":[10],"effective":[11],"complex":[13],"scenarios,":[14],"such":[15,71],"as":[16,72],"those":[17],"with":[18,23,179],"many":[19],"rare":[20],"classes":[21],"or":[22],"multimodal":[24],"data;":[25],"particular,":[27],"low-shot":[28],"(LSL)":[30],"is":[31,138],"a":[32,126,162],"challenging":[33],"task":[34],"for":[35,184,195],"which":[36,82],"multiple":[37],"strong":[38],"approaches":[39,108,147,160],"been":[41,78],"developed.":[42],"We":[43,166],"hypothesize":[44],"these":[46,86,159],"techniques\u2019":[47],"effectiveness":[48,58],"against":[49,59],"the":[50,60,131,139,152,169],"data":[51,61],"scarcity":[52,62],"within":[53,63],"LSL":[54,100],"may":[55],"translate":[56],"to":[57,93,109,141,155],"more":[64],"\u201ctraditional\u201d":[65],"supervised,":[66],"imbalanced,":[67],"binary":[68],"classification":[69],"tasks":[70],"fraud":[73,122],"detection;":[74],"however,":[75],"there":[76],"has":[77],"relatively":[79],"little":[80],"research":[81],"applies":[83],"them":[84,194],"contexts.":[87],"In":[88],"this":[89,95],"paper,":[90],"we":[91,173],"aim":[92],"fill":[94],"gap":[96],"by":[97],"selecting":[98],"two":[99,106,119],"papers":[101],"from":[102],"prior":[103],"literature":[104],"(representing":[105],"major":[107],"LSL,":[110],"optimization-based":[111,144],"and":[112,114,145,151,187,191,197],"contrastive),":[113],"reevaluate":[115],"their":[116],"models":[117],"on":[118,161,177],"highly-imbalanced":[120],"tabular":[121,163],"detection":[123],"datasets,":[124],"including":[125],"\u201cbig-data\u201d":[127],"Medicare":[128],"dataset.":[129],"To":[130],"best":[132],"of":[133,158],"our":[134,136],"knowledge,":[135],"work":[137,154],"first":[140,153],"directly":[142],"compare":[143],"contrastive":[146,170],"any":[149],"setting,":[150],"examine":[156],"either":[157],"big-data":[164],"task.":[165],"find":[167],"method":[172],"test,":[174],"Siamese-RNN,":[175],"performs":[176],"par":[178],"state-of-the-art":[180],"non-LSL":[181],"baseline":[182],"learners":[183],"especially":[185],"big":[186],"severely":[188,199],"imbalanced":[189,200],"data,":[190],"significantly":[192],"outperforms":[193],"smaller":[196],"less":[198],"data.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}