{"id":"https://openalex.org/W2023067667","doi":"https://doi.org/10.1017/s0269888910000329","title":"Discretization as the enabling technique for the Na\u00efve Bayes and semi-Na\u00efve Bayes-based classification","display_name":"Discretization as the enabling technique for the Na\u00efve Bayes and semi-Na\u00efve Bayes-based classification","publication_year":2010,"publication_date":"2010-11-26","ids":{"openalex":"https://openalex.org/W2023067667","doi":"https://doi.org/10.1017/s0269888910000329","mag":"2023067667"},"language":"en","primary_location":{"id":"doi:10.1017/s0269888910000329","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0269888910000329","pdf_url":null,"source":{"id":"https://openalex.org/S137506714","display_name":"The Knowledge Engineering Review","issn_l":"0269-8889","issn":["0269-8889","1469-8005"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Knowledge Engineering Review","raw_type":"journal-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/A5040777177","display_name":"Marcin J. Mizianty","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Marcin J. Mizianty","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada; e-mail:","e-mail:","Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada; e-mail:","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"e-mail:","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088423732","display_name":"Lukasz Kurgan","orcid":"https://orcid.org/0000-0002-7749-0314"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Lukasz A. Kurgan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada; e-mail:","Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada","e-mail:"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada; e-mail:","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"e-mail:","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081181492","display_name":"Marek R. Ogiela","orcid":"https://orcid.org/0000-0002-8298-8627"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Marek R. Ogiela","raw_affiliation_strings":["Bio-cybernetics Laboratory, Institute of Automatics, AGH University of Science and Technology, Krakow, Poland; e-mail:","Bio-cybernetics Laboratory, Institute of Automatics, AGH University of Science and Technology, Krakow, Poland","e-mail:"],"affiliations":[{"raw_affiliation_string":"Bio-cybernetics Laboratory, Institute of Automatics, AGH University of Science and Technology, Krakow, Poland; e-mail:","institution_ids":["https://openalex.org/I686019"]},{"raw_affiliation_string":"Bio-cybernetics Laboratory, Institute of Automatics, AGH University of Science and Technology, Krakow, Poland","institution_ids":["https://openalex.org/I686019"]},{"raw_affiliation_string":"e-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040777177","https://openalex.org/A5081181492","https://openalex.org/A5088423732"],"corresponding_institution_ids":["https://openalex.org/I154425047","https://openalex.org/I686019"],"apc_list":null,"apc_paid":null,"fwci":3.1573,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.91923504,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"25","issue":"4","first_page":"421","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.998199999332428,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.998199999332428,"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":0.9962000250816345,"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"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9926000237464905,"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/discretization","display_name":"Discretization","score":0.8379093408584595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6934988498687744},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5845614075660706},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.580689013004303},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5673764944076538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49354612827301025},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4874996840953827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48143455386161804},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48090243339538574},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4714202284812927},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4272093176841736},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3669058084487915},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24317827820777893},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.20528468489646912},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.19231882691383362},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13657891750335693},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.13091006875038147}],"concepts":[{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.8379093408584595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6934988498687744},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5845614075660706},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.580689013004303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5673764944076538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49354612827301025},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4874996840953827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48143455386161804},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48090243339538574},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4714202284812927},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4272093176841736},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3669058084487915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24317827820777893},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.20528468489646912},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.19231882691383362},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13657891750335693},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.13091006875038147},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s0269888910000329","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0269888910000329","pdf_url":null,"source":{"id":"https://openalex.org/S137506714","display_name":"The Knowledge Engineering Review","issn_l":"0269-8889","issn":["0269-8889","1469-8005"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Knowledge Engineering Review","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322337","display_name":"Killam Trusts","ror":"https://ror.org/021cbtn85"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W69783631","https://openalex.org/W91469012","https://openalex.org/W190725693","https://openalex.org/W209492218","https://openalex.org/W1503498577","https://openalex.org/W1513133520","https://openalex.org/W1513366687","https://openalex.org/W1551066950","https://openalex.org/W1565746575","https://openalex.org/W1570448133","https://openalex.org/W1585743408","https://openalex.org/W1596278050","https://openalex.org/W1597910678","https://openalex.org/W1608815176","https://openalex.org/W1625504505","https://openalex.org/W1678889691","https://openalex.org/W1817561967","https://openalex.org/W1822580350","https://openalex.org/W1902572552","https://openalex.org/W1906182963","https://openalex.org/W1912123407","https://openalex.org/W1993246951","https://openalex.org/W2000613518","https://openalex.org/W2000950277","https://openalex.org/W2001592424","https://openalex.org/W2032427901","https://openalex.org/W2054658115","https://openalex.org/W2074924176","https://openalex.org/W2086460959","https://openalex.org/W2091299760","https://openalex.org/W2097569937","https://openalex.org/W2102652939","https://openalex.org/W2102935258","https://openalex.org/W2111574971","https://openalex.org/W2121053863","https://openalex.org/W2122175496","https://openalex.org/W2125055259","https://openalex.org/W2131626681","https://openalex.org/W2133121564","https://openalex.org/W2135511047","https://openalex.org/W2136000097","https://openalex.org/W2142827986","https://openalex.org/W2143317258","https://openalex.org/W2150706391","https://openalex.org/W2153188249","https://openalex.org/W2160671582","https://openalex.org/W2161919332","https://openalex.org/W2170306141","https://openalex.org/W2170595610","https://openalex.org/W2550120957","https://openalex.org/W2798815563","https://openalex.org/W2966207845","https://openalex.org/W3120740533","https://openalex.org/W4234760406","https://openalex.org/W4249215961","https://openalex.org/W6608434954","https://openalex.org/W6636859864"],"related_works":["https://openalex.org/W1538041071","https://openalex.org/W4205958290","https://openalex.org/W2115870505","https://openalex.org/W1470425429","https://openalex.org/W4306742369","https://openalex.org/W2610616641","https://openalex.org/W3107602296","https://openalex.org/W3014815208","https://openalex.org/W2171665309","https://openalex.org/W2086147528"],"abstract_inverted_index":{"Abstract":[0],"Current":[1],"classification":[2,15,155,213,311,345],"problems":[3],"that":[4,28,74,122,151,270,329],"concern":[5],"data":[6,36,111,235],"sets":[7],"of":[8,31,53,72,80,85,117,177,184,291,312],"large":[9],"and":[10,42,78,98,106,109,120,136,165,190,204,227,240,262,301,343,353],"increasing":[11],"size":[12],"require":[13],"scalable":[14],"algorithms.":[16,355],"In":[17],"this":[18],"study,":[19],"we":[20],"concentrate":[21],"on":[22,171,234,340],"several":[23,43],"scalable,":[24],"linear":[25],"complexity":[26],"classifiers":[27,102],"include":[29],"one":[30],"the":[32,54,70,76,83,86,115,118,123,145,154,160,172,178,182,185,198,218,249,259,272,276,283,287,289,292,299,309,313,319,341,344,350],"top":[33],"10":[34,99],"voted":[35],"mining":[37],"methods,":[38,163],"Na\u00efve":[39,167,230],"Bayes":[40,168,265],"(NB),":[41],"recently":[44],"proposed":[45],"semi-NB":[46],"classifiers.":[47,267],"These":[48],"algorithms":[49],"perform":[50],"front-end":[51],"discretization":[52,81,142,152,179,277],"continuous":[55,314],"features":[56],"since":[57],"by":[58,217,225,333],"design":[59],"they":[60],"work":[61],"only":[62],"with":[63,144,237,258,349],"nominal":[64],"or":[65],"discrete":[66],"features.":[67],"We":[68,113,149,268],"address":[69],"lack":[71],"studies":[73],"investigate":[75,114],"benefits":[77],"drawbacks":[79],"in":[82],"context":[84],"subsequent":[87],"classification.":[88],"Our":[89],"comprehensive":[90],"empirical":[91],"study":[92],"considers":[93],"12":[94],"discretizers":[95,119,126,206],"(two":[96,103],"unsupervised":[97],"supervised),":[100],"seven":[101],"classical":[104,162,250],"NB":[105,164,251],"five":[107],"semi-NB),":[108],"16":[110],"sets.":[112],"scalability":[116],"show":[121,150,269],"fastest":[124],"supervised":[125],"fast":[127],"class-attribute":[128,132],"interdependency":[129,133],"maximization":[130,134,139],"(FCAIM),":[131],"(CAIM),":[135],"information":[137],"entropy":[138],"(IEM)":[140],"provide":[141,193,207],"schemes":[143],"highest":[146],"overall":[147],"quality.":[148],"improves":[153],"accuracy":[156,342],"when":[157],"compared":[158],"against":[159],"two":[161],"Flexible":[166],"(FNB),":[169],"executed":[170],"raw":[173],"data.":[174],"The":[175,187,210,253,335],"choice":[176],"algorithm":[180],"impacts":[181],"significance":[183],"improvements.":[186,209],"MODL,":[188,238,351],"FCAIM,":[189,239,352],"CAIM":[191,241,354],"methods":[192],"statistically":[194,243],"significant":[195],"improvements,":[196],"while":[197],"IEM,":[199],"Class-attribute":[200],"contingency":[201],"coefficient":[202],"(CACC),":[203],"Khiops":[205],"moderate":[208],"most":[211],"accurate":[212],"models":[214],"are":[215,256],"generated":[216],"Averaged":[219],"one-dependence":[220],"estimators":[221],"(AODEsr)":[222],"classifier":[223],"followed":[224],"AODE":[226],"HNB":[228],"(Hidden":[229],"Bayes).":[231],"AODEsr":[232],"run":[233],"discretized":[236],"provides":[242],"significantly":[244],"better":[245],"accuracies":[246],"than":[247,282,308],"both":[248,339],"methods.":[252],"worst":[254],"results":[255],"obtained":[257],"NB,":[260],"FNB,":[261],"LBR":[263],"(Lazy":[264],"rule)":[266],"although":[271],"time":[273,284,320],"to":[274,285,321],"build":[275],"scheme":[278],"could":[279],"be":[280],"longer":[281],"train":[286],"classifier,":[288,300],"completion":[290],"entire":[293],"process":[294],"(to":[295],"discretize":[296],"data,":[297],"compute":[298],"predict":[302],"test":[303,323],"instances)":[304],"is":[305,317,325,330,347],"often":[306],"faster":[307],"NB-based":[310],"instances.":[315],"This":[316],"because":[318],"classify":[322],"instances":[324],"an":[326],"important":[327],"factor":[328],"positively":[331],"influenced":[332],"discretization.":[334],"biggest":[336],"positive":[337],"influence,":[338],"time,":[346],"associated":[348]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-01-08T20:05:33.558190","created_date":"2025-10-10T00:00:00"}
