{"id":"https://openalex.org/W2112527204","doi":"https://doi.org/10.1109/ijcnn.2009.5178752","title":"Evaluating classifiers: Relation between area under the receiver operator characteristic curve and overall accuracy","display_name":"Evaluating classifiers: Relation between area under the receiver operator characteristic curve and overall accuracy","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2112527204","doi":"https://doi.org/10.1109/ijcnn.2009.5178752","mag":"2112527204"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001300575","display_name":"Maciej A. Mazurowski","orcid":"https://orcid.org/0000-0003-4202-8602"},"institutions":[{"id":"https://openalex.org/I4210126298","display_name":"Duke Medical Center","ror":"https://ror.org/03njmea73","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210126298","https://openalex.org/I4210144876"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maciej A. Mazurowski","raw_affiliation_strings":["Department of Radiology, Duke University Medical Center, Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Duke University Medical Center, Durham, NC, USA","institution_ids":["https://openalex.org/I4210126298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014968146","display_name":"Georgia D. Tourassi","orcid":"https://orcid.org/0000-0002-9418-9638"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]},{"id":"https://openalex.org/I4210126298","display_name":"Duke Medical Center","ror":"https://ror.org/03njmea73","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210126298","https://openalex.org/I4210144876"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgia D. Tourassi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA","Department of Radiology, Duke University Medical Center, Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA","institution_ids":["https://openalex.org/I142740786"]},{"raw_affiliation_string":"Department of Radiology, Duke University Medical Center, Durham, NC, USA","institution_ids":["https://openalex.org/I4210126298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2185,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79814854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2045","last_page":"2049"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996399998664856,"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":0.9757999777793884,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6629334688186646},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6307662129402161},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.6156061291694641},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5870541930198669},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5703974962234497},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5405371189117432},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5352811217308044},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5001411437988281},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49703362584114075},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47769027948379517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4760743975639343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4462342858314514},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.423541396856308},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3825596868991852},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3799448609352112},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.31004366278648376}],"concepts":[{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6629334688186646},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6307662129402161},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.6156061291694641},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5870541930198669},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5703974962234497},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5405371189117432},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5352811217308044},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5001411437988281},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49703362584114075},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47769027948379517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4760743975639343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4462342858314514},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.423541396856308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3825596868991852},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3799448609352112},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31004366278648376},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1524761913","https://openalex.org/W1531857721","https://openalex.org/W2002645541","https://openalex.org/W2015056255","https://openalex.org/W2026981875","https://openalex.org/W2070340558","https://openalex.org/W2089114844","https://openalex.org/W2089918690","https://openalex.org/W2090197876","https://openalex.org/W2106479238","https://openalex.org/W2119821739","https://openalex.org/W2133191367","https://openalex.org/W2153595774","https://openalex.org/W2155653793","https://openalex.org/W2158698691","https://openalex.org/W2164783505","https://openalex.org/W2799061466","https://openalex.org/W2920943913","https://openalex.org/W4239510810","https://openalex.org/W4244494905","https://openalex.org/W6631546530"],"related_works":["https://openalex.org/W4385649027","https://openalex.org/W4400094315","https://openalex.org/W2970784617","https://openalex.org/W2126639667","https://openalex.org/W2217963778","https://openalex.org/W2474554762","https://openalex.org/W2129882004","https://openalex.org/W4303685026","https://openalex.org/W1980276147","https://openalex.org/W2266938806"],"abstract_inverted_index":{"In":[0],"this":[1,39,132],"study,":[2],"we":[3,49],"investigated":[4],"the":[5,15,26,87,92,99,106,109,118,124],"relation":[6],"between":[7,108],"two":[8,110],"popular":[9],"classifier":[10],"performance":[11,77],"measures:":[12],"area":[13],"under":[14],"receiver":[16],"operator":[17],"characteristic":[18],"curve":[19],"and":[20,31,54,70],"overall":[21],"accuracy.":[22],"We":[23,41],"also":[24,114],"evaluated":[25],"impact":[27],"of":[28,33,45,84,95,120],"class":[29,101,121],"imbalance":[30,122],"number":[32,94],"examples":[34],"in":[35,47,57,75,86,123],"test":[36,55,72,125],"set":[37,44,126],"on":[38,131],"relation.":[40],"perform":[42],"a":[43,68,80,128],"experiments":[46],"which":[48],"train":[50],"multiple":[51],"neural":[52],"networks":[53],"them":[56],"various,":[58],"well":[59],"controlled":[60],"conditions.":[61],"The":[62],"experimental":[63],"results":[64,113],"show":[65],"that":[66,116],"given":[67],"large":[69],"balanced":[71],"set,":[73],"increase":[74,85],"one":[76],"measure":[78],"is":[79],"very":[81],"good":[82],"indicator":[83],"other":[88],"measure.":[89],"Furthermore":[90],"increasing":[91,117],"total":[93],"examples,":[96],"while":[97],"keeping":[98],"positive":[100],"prevalence":[102],"constant":[103],"generally":[104],"increases":[105],"correlation":[107],"measures.":[111],"Our":[112],"indicate":[115],"extent":[119],"has":[127],"detrimental":[129],"effect":[130],"correlation.":[133]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}