{"id":"https://openalex.org/W7124766723","doi":"https://doi.org/10.3390/make8010024","title":"COVAS: Highlighting the Importance of Outliers in Classification Through Explainable AI","display_name":"COVAS: Highlighting the Importance of Outliers in Classification Through Explainable AI","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7124766723","doi":"https://doi.org/10.3390/make8010024"},"language":"en","primary_location":{"id":"doi:10.3390/make8010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8010024","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/make8010024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123345042","display_name":"Sebastian Roth","orcid":null},"institutions":[{"id":"https://openalex.org/I16264642","display_name":"Koblenz University of Applied Sciences","ror":"https://ror.org/04j351e79","country_code":"DE","type":"education","lineage":["https://openalex.org/I16264642"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Roth","raw_affiliation_strings":["Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany"],"raw_orcid":"https://orcid.org/0009-0008-3717-6559","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","institution_ids":["https://openalex.org/I16264642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021807391","display_name":"Adrien Cerrito","orcid":"https://orcid.org/0000-0001-6119-533X"},"institutions":[{"id":"https://openalex.org/I173439891","display_name":"HES-SO University of Applied Sciences and Arts Western Switzerland","ror":"https://ror.org/01xkakk17","country_code":"CH","type":"education","lineage":["https://openalex.org/I173439891"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Adrien Cerrito","raw_affiliation_strings":["Haute-Ecole Arc Sant\u00e9, HES-SO University of Applied Sciences and Arts Western Switzerland, 2800 Del\u00e9mont, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-6119-533X","affiliations":[{"raw_affiliation_string":"Haute-Ecole Arc Sant\u00e9, HES-SO University of Applied Sciences and Arts Western Switzerland, 2800 Del\u00e9mont, Switzerland","institution_ids":["https://openalex.org/I173439891"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120465708","display_name":"Samuel Orth","orcid":"https://orcid.org/0009-0003-3828-8214"},"institutions":[{"id":"https://openalex.org/I16264642","display_name":"Koblenz University of Applied Sciences","ror":"https://ror.org/04j351e79","country_code":"DE","type":"education","lineage":["https://openalex.org/I16264642"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Samuel Orth","raw_affiliation_strings":["Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany"],"raw_orcid":"https://orcid.org/0009-0003-3828-8214","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","institution_ids":["https://openalex.org/I16264642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041234986","display_name":"Ulrich Hartmann","orcid":null},"institutions":[{"id":"https://openalex.org/I16264642","display_name":"Koblenz University of Applied Sciences","ror":"https://ror.org/04j351e79","country_code":"DE","type":"education","lineage":["https://openalex.org/I16264642"]},{"id":"https://openalex.org/I4210088543","display_name":"Institut f\u00fcr Informationsverarbeitung","ror":"https://ror.org/0047j9t38","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210088543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulrich Hartmann","raw_affiliation_strings":["Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","Institut f\u00fcr Medizintechnik und Informationsverarbeitung, 56070 Koblenz, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9625-7075","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","institution_ids":["https://openalex.org/I16264642"]},{"raw_affiliation_string":"Institut f\u00fcr Medizintechnik und Informationsverarbeitung, 56070 Koblenz, Germany","institution_ids":["https://openalex.org/I4210088543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011930160","display_name":"Daniel Friemert","orcid":"https://orcid.org/0000-0002-5035-6473"},"institutions":[{"id":"https://openalex.org/I16264642","display_name":"Koblenz University of Applied Sciences","ror":"https://ror.org/04j351e79","country_code":"DE","type":"education","lineage":["https://openalex.org/I16264642"]},{"id":"https://openalex.org/I4210088543","display_name":"Institut f\u00fcr Informationsverarbeitung","ror":"https://ror.org/0047j9t38","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210088543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Friemert","raw_affiliation_strings":["Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","Institut f\u00fcr Medizintechnik und Informationsverarbeitung, 56070 Koblenz, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5035-6473","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics, Informatics, Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany","institution_ids":["https://openalex.org/I16264642"]},{"raw_affiliation_string":"Institut f\u00fcr Medizintechnik und Informationsverarbeitung, 56070 Koblenz, Germany","institution_ids":["https://openalex.org/I4210088543"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08142052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"1","first_page":"24","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9747999906539917,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9747999906539917,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.006099999882280827,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8138999938964844},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6794000267982483},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5371999740600586},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.40849998593330383},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.352400004863739},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.33649998903274536},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.30979999899864197}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8138999938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995999813079834},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6794000267982483},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6565999984741211},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5649999976158142},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5371999740600586},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3921999931335449},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make8010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8010024","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:285a0925dee34da19bf60fe43b7b6248","is_oa":true,"landing_page_url":"https://doaj.org/article/285a0925dee34da19bf60fe43b7b6248","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":"Machine Learning and Knowledge Extraction, Vol 8, Iss 1, p 24 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make8010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8010024","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7844101786613464,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1717486659","https://openalex.org/W1996118086","https://openalex.org/W2613463286","https://openalex.org/W2898607919","https://openalex.org/W2923722090","https://openalex.org/W2990283237","https://openalex.org/W3107975486","https://openalex.org/W4254182148","https://openalex.org/W4315701371","https://openalex.org/W4317103587","https://openalex.org/W4394818658","https://openalex.org/W4398223400","https://openalex.org/W4399433746","https://openalex.org/W4399919514","https://openalex.org/W4403048643","https://openalex.org/W4408047551","https://openalex.org/W4410328047","https://openalex.org/W4410851914","https://openalex.org/W4411297523"],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"the":[1,59,73,81,115,120,134,147],"decision-making":[2],"behavior":[3,41],"of":[4,75,117,125],"machine":[5],"learning":[6],"models":[7],"is":[8],"essential":[9],"in":[10,80],"domains":[11],"where":[12],"individual":[13,96],"predictions":[14],"matter,":[15],"such":[16,29],"as":[17,30],"medical":[18,148],"diagnosis":[19],"or":[20,166],"sports":[21,150],"analytics.":[22],"While":[23],"explainable":[24],"artificial":[25],"intelligence":[26],"(XAI)":[27],"methods":[28],"SHAP":[31,88,108],"provide":[32],"instance-level":[33,193],"feature":[34],"attributions,":[35],"they":[36],"mainly":[37],"summarize":[38],"typical":[39],"decision":[40],"and":[42,84,122,137,149,181,195],"offer":[43],"limited":[44],"support":[45,69],"for":[46,133],"systematically":[47],"exploring":[48],"atypical":[49],"yet":[50],"correctly":[51],"classified":[52],"cases.":[53],"In":[54],"this":[55],"work,":[56],"we":[57],"introduce":[58],"Classification":[60],"Outlier":[61],"Variability":[62],"Score":[63],"(COVAS),":[64],"a":[65,111],"framework":[66],"designed":[67],"to":[68],"hypothesis":[70,198],"generation":[71],"through":[72],"analysis":[74],"explanation":[76,82,99],"variability.":[77],"COVAS":[78,118,141,156,185],"operates":[79],"space":[83],"builds":[85],"directly":[86],"on":[87,142],"value":[89],"representations.":[90],"It":[91],"quantifies":[92],"how":[93],"strongly":[94],"an":[95],"instance\u2019s":[97],"SHAP-based":[98],"deviates":[100],"from":[101,146],"class-specific":[102],"attribution":[103],"patterns":[104],"by":[105,162,190],"aggregating":[106],"standardized":[107],"deviations":[109],"into":[110],"single":[112],"score.":[113],"Consequently,":[114],"applicability":[116],"inherits":[119],"model-":[121],"data-agnostic":[123],"properties":[124],"SHAP,":[126],"provided":[127],"that":[128,155],"explanations":[129],"can":[130],"be":[131],"computed":[132],"underlying":[135],"model":[136,179,182],"data.":[138],"We":[139],"evaluate":[140],"publicly":[143],"available":[144],"datasets":[145],"domains.":[151],"The":[152],"results":[153],"show":[154],"reveals":[157],"explanation-space":[158],"outliers":[159],"not":[160],"captured":[161],"feature-space":[163],"outlier":[164],"detection":[165],"prediction":[167],"uncertainty":[168],"measures.":[169],"Robustness":[170],"analyses":[171],"demonstrate":[172],"stability":[173],"across":[174],"parameter":[175],"choices,":[176],"class":[177],"imbalance,":[178],"initialization,":[180],"classes.":[183],"Overall,":[184],"complements":[186],"existing":[187],"XAI":[188],"techniques":[189],"enabling":[191],"targeted":[192],"inspection":[194],"facilitating":[196],"XAI-guided":[197],"formulation.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-20T00:00:00"}