{"id":"https://openalex.org/W3108313614","doi":"https://doi.org/10.3390/info11120557","title":"DTO-SMOTE: Delaunay Tessellation Oversampling for Imbalanced Data Sets","display_name":"DTO-SMOTE: Delaunay Tessellation Oversampling for Imbalanced Data Sets","publication_year":2020,"publication_date":"2020-11-28","ids":{"openalex":"https://openalex.org/W3108313614","doi":"https://doi.org/10.3390/info11120557","mag":"3108313614"},"language":"en","primary_location":{"id":"doi:10.3390/info11120557","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11120557","pdf_url":"https://www.mdpi.com/2078-2489/11/12/557/pdf?version=1606878571","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/11/12/557/pdf?version=1606878571","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083114464","display_name":"A. M. Carvalho","orcid":"https://orcid.org/0000-0002-8801-4321"},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alexandre M. de Carvalho","raw_affiliation_strings":["Center of Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), Santo Andr\u00e9, SP 09210-580, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-8801-4321","affiliations":[{"raw_affiliation_string":"Center of Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), Santo Andr\u00e9, SP 09210-580, Brazil","institution_ids":["https://openalex.org/I71715416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005717519","display_name":"Ronaldo C. Prati","orcid":"https://orcid.org/0000-0001-8597-4987"},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Ronaldo C. Prati","raw_affiliation_strings":["Center of Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), Santo Andr\u00e9, SP 09210-580, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-8597-4987","affiliations":[{"raw_affiliation_string":"Center of Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), Santo Andr\u00e9, SP 09210-580, Brazil","institution_ids":["https://openalex.org/I71715416"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005717519"],"corresponding_institution_ids":["https://openalex.org/I71715416"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.8161,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79840486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"11","issue":"12","first_page":"557","last_page":"557"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9904999732971191,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9832000136375427,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/oversampling","display_name":"Oversampling","score":0.8231083154678345},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7112372517585754},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.607372522354126},{"id":"https://openalex.org/keywords/delaunay-triangulation","display_name":"Delaunay triangulation","score":0.5965284109115601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5619454979896545},{"id":"https://openalex.org/keywords/tessellation","display_name":"Tessellation (computer graphics)","score":0.4463271498680115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44205331802368164},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4332560896873474},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4299710988998413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38483357429504395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37182846665382385},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3399844765663147},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.07042434811592102}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.8231083154678345},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7112372517585754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.607372522354126},{"id":"https://openalex.org/C68010082","wikidata":"https://www.wikidata.org/wiki/Q192445","display_name":"Delaunay triangulation","level":2,"score":0.5965284109115601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5619454979896545},{"id":"https://openalex.org/C43817857","wikidata":"https://www.wikidata.org/wiki/Q9357547","display_name":"Tessellation (computer graphics)","level":2,"score":0.4463271498680115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44205331802368164},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4332560896873474},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4299710988998413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38483357429504395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37182846665382385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3399844765663147},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.07042434811592102},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"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":3,"locations":[{"id":"doi:10.3390/info11120557","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11120557","pdf_url":"https://www.mdpi.com/2078-2489/11/12/557/pdf?version=1606878571","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:49142328fcd3475980fc28efde770c32","is_oa":true,"landing_page_url":"https://doaj.org/article/49142328fcd3475980fc28efde770c32","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":"Information, Vol 11, Iss 12, p 557 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2078-2489/11/12/557/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/info11120557","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information; Volume 11; Issue 12; Pages: 557","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/info11120557","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11120557","pdf_url":"https://www.mdpi.com/2078-2489/11/12/557/pdf?version=1606878571","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3108313614.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1530490667","https://openalex.org/W1754612754","https://openalex.org/W1969732712","https://openalex.org/W1974079881","https://openalex.org/W1986959058","https://openalex.org/W1993220166","https://openalex.org/W2006903949","https://openalex.org/W2032867948","https://openalex.org/W2040181375","https://openalex.org/W2056132907","https://openalex.org/W2059423053","https://openalex.org/W2067407532","https://openalex.org/W2090135786","https://openalex.org/W2092452774","https://openalex.org/W2099454382","https://openalex.org/W2099942883","https://openalex.org/W2104933073","https://openalex.org/W2107138773","https://openalex.org/W2120194796","https://openalex.org/W2124246957","https://openalex.org/W2132791018","https://openalex.org/W2146819312","https://openalex.org/W2148143831","https://openalex.org/W2153635508","https://openalex.org/W2165370158","https://openalex.org/W2168508521","https://openalex.org/W2477734150","https://openalex.org/W2512691369","https://openalex.org/W2521200999","https://openalex.org/W2562319768","https://openalex.org/W2609430174","https://openalex.org/W2760799532","https://openalex.org/W2765177294","https://openalex.org/W2768859775","https://openalex.org/W2774453127","https://openalex.org/W2800788706","https://openalex.org/W2883500076","https://openalex.org/W2889470580","https://openalex.org/W2891857749","https://openalex.org/W2896236534","https://openalex.org/W2896336565","https://openalex.org/W2948219206","https://openalex.org/W2963613787","https://openalex.org/W2989943665","https://openalex.org/W3011722050","https://openalex.org/W3016106031","https://openalex.org/W3017050370","https://openalex.org/W3034598515","https://openalex.org/W3042932150","https://openalex.org/W3095525721","https://openalex.org/W3120421331","https://openalex.org/W4212883601","https://openalex.org/W4243367342","https://openalex.org/W4245055982","https://openalex.org/W4285719527","https://openalex.org/W4292083457","https://openalex.org/W4293713156","https://openalex.org/W4297957988","https://openalex.org/W6675187287","https://openalex.org/W6681832838","https://openalex.org/W6686355519","https://openalex.org/W6773842061","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W4206637278","https://openalex.org/W2781247653","https://openalex.org/W4386005305","https://openalex.org/W3082051559","https://openalex.org/W1682621979","https://openalex.org/W4386214543","https://openalex.org/W2012117566","https://openalex.org/W1981856929","https://openalex.org/W2035847161"],"abstract_inverted_index":{"One":[0],"of":[1,11,78,122,135],"the":[2,9,28,58,125],"significant":[3],"challenges":[4],"in":[5,120],"machine":[6],"learning":[7],"is":[8],"classification":[10,104],"imbalanced":[12],"data.":[13],"In":[14],"many":[15,31],"situations,":[16],"standard":[17],"classifiers":[18],"cannot":[19],"learn":[20],"how":[21],"to":[22],"distinguish":[23],"minority":[24],"class":[25],"examples":[26],"from":[27],"others.":[29],"Since":[30],"real":[32],"problems":[33],"are":[34],"unbalanced,":[35],"this":[36,81],"problem":[37],"has":[38,115],"become":[39],"very":[40],"relevant":[41],"and":[42,57,101,106,132],"deeply":[43],"studied":[44],"today.":[45],"This":[46],"paper":[47],"presents":[48],"a":[49,76],"new":[50],"preprocessing":[51,59,95],"method":[52],"based":[53],"on":[54],"Delaunay":[55],"tessellation":[56],"algorithm":[60],"SMOTE":[61],"(Synthetic":[62],"Minority":[63],"Over-sampling":[64],"Technique),":[65],"which":[66],"we":[67,83],"call":[68],"DTO-SMOTE":[69,74,114],"(Delaunay":[70],"Tessellation":[71],"Oversampling":[72],"SMOTE).":[73],"constructs":[75],"mesh":[77],"simplices":[79],"(in":[80],"paper,":[82],"use":[84],"tetrahedrons)":[85],"for":[86],"creating":[87],"synthetic":[88],"examples.":[89],"We":[90],"compare":[91],"results":[92],"with":[93],"five":[94],"algorithms":[96],"(GEOMETRIC-SMOTE,":[97],"SVM-SMOTE,":[98],"SMOTE-BORDERLINE-1,":[99],"SMOTE-BORDERLINE-2,":[100],"SMOTE),":[102],"eight":[103],"algorithms,":[105],"61":[107],"binary-class":[108],"data":[109],"sets.":[110],"For":[111],"some":[112],"classifiers,":[113],"higher":[116],"performance":[117],"than":[118],"others":[119],"terms":[121],"Area":[123],"Under":[124],"ROC":[126],"curve":[127],"(AUC),":[128],"Geometric":[129],"Mean":[130],"(GEO),":[131],"Generalized":[133],"Index":[134],"Balanced":[136],"Accuracy":[137],"(IBA).":[138]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2020-12-07T00:00:00"}