{"id":"https://openalex.org/W4226270096","doi":"https://doi.org/10.1145/3507548.3507612","title":"Distribution Consistency Penalty in the Quadratic Kappa Loss for Ordinal Regression of Imbalanced Datasets","display_name":"Distribution Consistency Penalty in the Quadratic Kappa Loss for Ordinal Regression of Imbalanced Datasets","publication_year":2021,"publication_date":"2021-12-04","ids":{"openalex":"https://openalex.org/W4226270096","doi":"https://doi.org/10.1145/3507548.3507612"},"language":"en","primary_location":{"id":"doi:10.1145/3507548.3507612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3507548.3507612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","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/A5112993893","display_name":"Bingjie Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingjie Yang","raw_affiliation_strings":["Tongji University, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035948567","display_name":"Shengjie Zhao","orcid":"https://orcid.org/0000-0002-6109-2522"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjie Zhao","raw_affiliation_strings":["Tongji University, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072704501","display_name":"Kenan Ye","orcid":"https://orcid.org/0009-0005-6696-6259"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kenan Ye","raw_affiliation_strings":["Tongji University, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100695813","display_name":"Rongqing Zhang","orcid":"https://orcid.org/0000-0003-3774-6247"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongqing Zhang","raw_affiliation_strings":["Tongji University, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112993893"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58359158,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"415","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9930999875068665,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/consistency","display_name":"Consistency (knowledge bases)","score":0.6463583707809448},{"id":"https://openalex.org/keywords/ordinal-regression","display_name":"Ordinal regression","score":0.6020103693008423},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5310025215148926},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5306614637374878},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5249409675598145},{"id":"https://openalex.org/keywords/penalty-method","display_name":"Penalty method","score":0.519001841545105},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4812488257884979},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4566371738910675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43300601840019226},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41825225949287415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38586995005607605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38521453738212585},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36660170555114746},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3205624222755432},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13965287804603577}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6463583707809448},{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.6020103693008423},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5310025215148926},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5306614637374878},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5249409675598145},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.519001841545105},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4812488257884979},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4566371738910675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43300601840019226},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41825225949287415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38586995005607605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38521453738212585},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36660170555114746},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3205624222755432},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13965287804603577},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3507548.3507612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3507548.3507612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W114375244","https://openalex.org/W1505609544","https://openalex.org/W1905153633","https://openalex.org/W1965804146","https://openalex.org/W1983897914","https://openalex.org/W2037789405","https://openalex.org/W2115531174","https://openalex.org/W2132852291","https://openalex.org/W2344912502","https://openalex.org/W2502390809","https://openalex.org/W2510725918","https://openalex.org/W2553576544","https://openalex.org/W2560046091","https://openalex.org/W2616031720","https://openalex.org/W2616591008","https://openalex.org/W2765362756","https://openalex.org/W2765518339","https://openalex.org/W2798410215","https://openalex.org/W2798655965","https://openalex.org/W2806251809","https://openalex.org/W2894781902","https://openalex.org/W2913282330","https://openalex.org/W2949208911","https://openalex.org/W2963488291","https://openalex.org/W2990759908","https://openalex.org/W3000959322","https://openalex.org/W3012560784","https://openalex.org/W3035369545","https://openalex.org/W3037164804","https://openalex.org/W3080149518","https://openalex.org/W3080272905","https://openalex.org/W3098794096","https://openalex.org/W3150272974","https://openalex.org/W3187838195","https://openalex.org/W3191914652","https://openalex.org/W4287597851","https://openalex.org/W4288018401","https://openalex.org/W4293579865","https://openalex.org/W6604611180","https://openalex.org/W6663855623","https://openalex.org/W6763699814"],"related_works":["https://openalex.org/W3210452439","https://openalex.org/W2018662469","https://openalex.org/W2062802260","https://openalex.org/W2107628111","https://openalex.org/W1977335770","https://openalex.org/W2175677697","https://openalex.org/W3180934676","https://openalex.org/W2394004323","https://openalex.org/W2766314973","https://openalex.org/W2942464417"],"abstract_inverted_index":{"Ordinal":[0],"regression":[1],"is":[2,43,131],"a":[3,103,125],"typical":[4],"deep":[5],"learning":[6],"problem,":[7],"which":[8,111],"involves":[9],"inherently":[10],"ordered":[11,29],"labels":[12],"that":[13,65,159,203],"are":[14],"common":[15],"in":[16,20,48,88,102],"practical":[17],"applications,":[18],"especially":[19],"medical":[21],"diagnosis":[22],"tasks.":[23],"To":[24,121],"overcome":[25],"the":[26,49,63,76,82,89,96,117,134,140,150,155,198],"neglect":[27],"of":[28,119,128,142,149],"or":[30,37],"non-stationary":[31],"property":[32],"by":[33,138],"merely":[34],"exploiting":[35],"classification":[36],"regression,":[38],"quadratic":[39],"weighted":[40],"kappa":[41,66],"(QWK)":[42],"proposed":[44,132],"to":[45,80,145],"be":[46,68],"employed":[47],"QWK":[50,77,135],"loss":[51,78,136],"function":[52,79,137],"design":[53],"as":[54],"an":[55,71],"efficient":[56],"evaluation":[57],"metric":[58],"for":[59,116,133],"ordinal":[60],"regression.":[61],"However,":[62],"paradox":[64],"will":[67,100],"higher":[69],"with":[70,86],"asymmetrical":[72],"marginal":[73,143],"histogram":[74,144],"leads":[75],"get":[81],"local":[83],"optimal":[84],"solution":[85],"all-zero-column":[87,148,164],"confusion":[90],"matrices":[91],"during":[92],"training.":[93],"In":[94],"practice,":[95],"all-zero":[97],"column":[98],"problem":[99],"result":[101],"certain":[104],"category":[105],"not":[106],"being":[107],"detected":[108],"at":[109],"all,":[110],"can":[112],"have":[113],"serious":[114],"consequences":[115],"exclusion":[118],"pathology.":[120],"address":[122],"this":[123],"limitation,":[124],"new":[126],"form":[127],"penalty":[129,161,170,185,205],"term":[130],"penalizing":[139],"distance":[141],"effectively":[146],"avoid":[147],"models.":[151],"The":[152],"experiments":[153,196],"on":[154,181,197],"category-imbalanced":[156],"datasets":[157,200],"demonstrate":[158],"our":[160,169,184,204],"terms":[162,171,186,206],"solve":[163],"problem.":[165],"On":[166],"Adience":[167],"dataset":[168,183],"achieve":[172,187,207],"0.915":[173],"QWK,":[174,189,209],"0.446":[175],"MAE":[176,191,211],"and":[177,192,212],"0.612":[178],"accuracy,":[179],"while":[180],"DR":[182],"0.744":[188],"0.281":[190],"0.810":[193,208],"accuracy.":[194,214],"Besides,":[195],"category-balanced":[199],"HCI":[201],"show":[202],"0.499":[210],"0.610":[213]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}