{"id":"https://openalex.org/W4387878092","doi":"https://doi.org/10.3233/faia230671","title":"A Bayesian Network Framework to Study Class Noise: Exploring the Filtering of Completely Random Noise","display_name":"A Bayesian Network Framework to Study Class Noise: Exploring the Filtering of Completely Random Noise","publication_year":2023,"publication_date":"2023-10-19","ids":{"openalex":"https://openalex.org/W4387878092","doi":"https://doi.org/10.3233/faia230671"},"language":"en","primary_location":{"id":"doi:10.3233/faia230671","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia230671","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230671","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230671","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004726579","display_name":"David Mart\u00ednez-Galicia","orcid":"https://orcid.org/0000-0003-3198-2177"},"institutions":[{"id":"https://openalex.org/I147280213","display_name":"Universidad Veracruzana","ror":"https://ror.org/03efxn362","country_code":"MX","type":"education","lineage":["https://openalex.org/I147280213"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"David Mart\u00ednez-Galicia","raw_affiliation_strings":["Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico","institution_ids":["https://openalex.org/I147280213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017164973","display_name":"Alejandro Guerra\u2010Hern\u00e1ndez","orcid":"https://orcid.org/0000-0002-4856-4011"},"institutions":[{"id":"https://openalex.org/I147280213","display_name":"Universidad Veracruzana","ror":"https://ror.org/03efxn362","country_code":"MX","type":"education","lineage":["https://openalex.org/I147280213"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Alejandro Guerra-Hern\u00e1ndez","raw_affiliation_strings":["Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico","institution_ids":["https://openalex.org/I147280213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072216056","display_name":"Xavier Lim\u00f3n","orcid":"https://orcid.org/0000-0003-4654-636X"},"institutions":[{"id":"https://openalex.org/I147280213","display_name":"Universidad Veracruzana","ror":"https://ror.org/03efxn362","country_code":"MX","type":"education","lineage":["https://openalex.org/I147280213"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Xavier Lim\u00f3n","raw_affiliation_strings":["Facultad de Estad\u00edstica e Inform\u00e1tica, Universidad Veracruzana, Xalapa, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facultad de Estad\u00edstica e Inform\u00e1tica, Universidad Veracruzana, Xalapa, M\u00e9xico","institution_ids":["https://openalex.org/I147280213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076339803","display_name":"Nicandro Cruz-Ram\u00edrez","orcid":"https://orcid.org/0000-0002-0708-9875"},"institutions":[{"id":"https://openalex.org/I147280213","display_name":"Universidad Veracruzana","ror":"https://ror.org/03efxn362","country_code":"MX","type":"education","lineage":["https://openalex.org/I147280213"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Nicandro Cruz-Ram\u00edrez","raw_affiliation_strings":["Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inst. de Invest. en Inteligencia Artificial, Universidad Veracruzana, Xalapa, M\u00e9xico","institution_ids":["https://openalex.org/I147280213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050653653","display_name":"Francisco Grimaldo","orcid":"https://orcid.org/0000-0002-1357-7170"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Francisco Grimaldo","raw_affiliation_strings":["Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Val\u00e8ncia, Espa\u00f1a"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Val\u00e8ncia, Espa\u00f1a","institution_ids":["https://openalex.org/I16097986"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5004726579"],"corresponding_institution_ids":["https://openalex.org/I147280213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48784577,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9575999975204468,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9575999975204468,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9477999806404114,"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":0.9473000168800354,"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/noise","display_name":"Noise (video)","score":0.7522648572921753},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6605137586593628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.559256911277771},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.49155935645103455},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.480044960975647},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.45031148195266724},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.440945029258728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43328607082366943},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40294769406318665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39395707845687866},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38389164209365845},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2825419306755066}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7522648572921753},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6605137586593628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559256911277771},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.49155935645103455},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.480044960975647},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.45031148195266724},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.440945029258728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43328607082366943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40294769406318665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39395707845687866},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38389164209365845},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2825419306755066},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia230671","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia230671","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230671","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia230671","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia230671","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230671","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387878092.pdf","grobid_xml":"https://content.openalex.org/works/W4387878092.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1570448133","https://openalex.org/W2034841618","https://openalex.org/W2079788575","https://openalex.org/W2089939190","https://openalex.org/W2167460663","https://openalex.org/W3100570787","https://openalex.org/W4399591393","https://openalex.org/W6600062588"],"related_works":["https://openalex.org/W2171117985","https://openalex.org/W1526760723","https://openalex.org/W2126659863","https://openalex.org/W2012356576","https://openalex.org/W4385670989","https://openalex.org/W3112120395","https://openalex.org/W2102487628","https://openalex.org/W2436588531","https://openalex.org/W2009680848","https://openalex.org/W2150465873"],"abstract_inverted_index":{"Although":[0],"the":[1,16,43,56,62,97],"negative":[2],"consequences":[3],"of":[4,18,47,55,64,79,107],"noise":[5,36,49,65,80,108],"during":[6],"induction":[7],"have":[8],"been":[9],"widely":[10],"studied,":[11],"previous":[12],"work":[13],"often":[14],"lacks":[15],"use":[17],"validated":[19],"data":[20,40],"to":[21,103],"measure":[22],"its":[23],"impact.":[24],"We":[25],"propose":[26],"a":[27,82,88],"framework":[28,95],"based":[29],"on":[30,85,91],"Bayesian":[31],"Networks":[32],"for":[33],"modeling":[34],"class":[35,48,70,110],"and":[37,45,87,96],"generating":[38],"synthetic":[39],"sets":[41],"where":[42],"kind":[44,78],"amount":[46],"are":[50,59],"under":[51],"control.":[52],"The":[53,94],"benefits":[54],"proposed":[57],"approach":[58],"illustrated":[60],"evaluating":[61],"filtering":[63],"completely":[66],"at":[67],"random":[68],"in":[69,109],"labels":[71],"when":[72],"inducing":[73],"decision":[74],"trees.":[75],"Unexpectedly,":[76],"this":[77],"showed":[81],"low":[83,89],"effect":[84],"accuracy":[86],"occurrence":[90],"real":[92],"datasets.":[93],"methodology":[98],"developed":[99],"here":[100],"seem":[101],"promising":[102],"study":[104],"other":[105],"kinds":[106],"labels.":[111]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
