{"id":"https://openalex.org/W7154582131","doi":"https://doi.org/10.14428/esann/2026.es2026-72","title":"SMOTE k-out: Enhancing Class Separability through Outer Synthetic Sampling","display_name":"SMOTE k-out: Enhancing Class Separability through Outer Synthetic Sampling","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7154582131","doi":"https://doi.org/10.14428/esann/2026.es2026-72"},"language":null,"primary_location":{"id":"doi:10.14428/esann/2026.es2026-72","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-72","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-72","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.14428/esann/2026.es2026-72","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133794859","display_name":"Ver\u00f3nica Bol\u00f3n-Canedo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ver\u00f3nica Bol\u00f3n-Canedo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053214830","display_name":"Jos\u00e9 Luis Morillo-Salas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Luis Morillo-Salas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075460760","display_name":"Laura Mor\u00e1n\u2010Fern\u00e1ndez","orcid":"https://orcid.org/0000-0001-6703-1846"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laura Mor\u00e1n-Fern\u00e1ndez","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048207145","display_name":"Amparo Alonso\u2010Betanzos","orcid":"https://orcid.org/0000-0003-0950-0012"},"institutions":[{"id":"https://openalex.org/I4210124246","display_name":"CITIC Group (China)","ror":"https://ror.org/037b6wy35","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210124246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Amparo Alonso-Betanzos","raw_affiliation_strings":["CITIC , Universidade da Corua , A Corua , Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CITIC , Universidade da Corua , A Corua , Spain","institution_ids":["https://openalex.org/I4210124246"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56186496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"399","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1573999971151352,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1573999971151352,"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/T11448","display_name":"Face recognition and analysis","score":0.03970000147819519,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.03610000014305115,"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/class","display_name":"Class (philosophy)","score":0.49790000915527344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41929998993873596},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.39899998903274536},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.32919999957084656},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.31200000643730164}],"concepts":[{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.491100013256073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4903999865055084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4138000011444092},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.39899998903274536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3856000006198883},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2906999886035919},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14428/esann/2026.es2026-72","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-72","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-72","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.14428/esann/2026.es2026-72","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-72","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-72","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1496055848","display_name":null,"funder_award_id":"ED431C","funder_id":"https://openalex.org/F4320326655","funder_display_name":"Xunta de Galicia"},{"id":"https://openalex.org/G2262748287","display_name":null,"funder_award_id":"501100011033","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G3480869486","display_name":null,"funder_award_id":"13039","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G3694284866","display_name":null,"funder_award_id":"ED431C","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G3862095296","display_name":null,"funder_award_id":"ED431G 2023/01","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G3876637791","display_name":null,"funder_award_id":"ED431G","funder_id":"https://openalex.org/F4320326655","funder_display_name":"Xunta de Galicia"},{"id":"https://openalex.org/G4449378558","display_name":null,"funder_award_id":"ED431C 2022/44","funder_id":"https://openalex.org/F4320326655","funder_display_name":"Xunta de Galicia"},{"id":"https://openalex.org/G451917667","display_name":null,"funder_award_id":"13039/501100011033","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G464105488","display_name":null,"funder_award_id":"PID2023","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G5373964547","display_name":null,"funder_award_id":"PID2023-147404OB-I00","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G5802163902","display_name":null,"funder_award_id":"PID2023-147404OB-I00","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G5967599077","display_name":null,"funder_award_id":"501100011033","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G5995924772","display_name":null,"funder_award_id":"2021-27","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G7084143925","display_name":null,"funder_award_id":"AEI/10","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G7086754869","display_name":null,"funder_award_id":"ED431G 2023/01","funder_id":"https://openalex.org/F4320326655","funder_display_name":"Xunta de Galicia"},{"id":"https://openalex.org/G7266728691","display_name":null,"funder_award_id":"13039/501100011033","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"}],"funders":[{"id":"https://openalex.org/F4320326655","display_name":"Xunta de Galicia","ror":"https://ror.org/0181xnw06"},{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320335598","display_name":"Agencia Estatal de Investigaci\u00f3n","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7154582131.pdf","grobid_xml":"https://content.openalex.org/works/W7154582131.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Oversampling":[0],"techniques":[1],"are":[2],"commonly":[3],"used":[4],"to":[5,50,56],"address":[6],"class":[7,36,53],"imbalance":[8],"in":[9],"supervised":[10],"classification,":[11],"with":[12,91],"SMOTE":[13,19,40,79],"being":[14],"a":[15],"popular":[16],"approach.However,":[17],"traditional":[18],"generates":[20],"synthetic":[21,44],"samples":[22,45],"within":[23],"the":[24,47,61,67,70],"neighbourhood":[25,49],"of":[26,63,69],"minority":[27,52],"instances,":[28],"which":[29,42],"can":[30],"increase":[31,51],"data":[32],"complexity":[33,83],"and":[34,59,84,88,93],"hinder":[35],"separability.This":[37],"work":[38],"proposes":[39],"k-out,":[41],"creates":[43],"outside":[46],"local":[48],"sparsity.This":[54],"aims":[55],"reduce":[57],"overfitting":[58],"mitigate":[60],"impact":[62],"noise,":[64],"thereby":[65],"improving":[66],"definition":[68],"decision":[71],"boundary.Experiments":[72],"on":[73],"multiple":[74],"imbalanced":[75],"datasets":[76],"demonstrate":[77],"that":[78],"k-out":[80],"consistently":[81],"reduces":[82],"achieves":[85],"higher":[86],"accuracy":[87],"F-measure,":[89],"particularly":[90],"SVM":[92],"LDA":[94],"classifiers.":[95]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-17T00:00:00"}
