{"id":"https://openalex.org/W2058420708","doi":"https://doi.org/10.1080/713827176","title":"A feature selection bayesian approach for extracting classification rules with a clustering genetic algorithm","display_name":"A feature selection bayesian approach for extracting classification rules with a clustering genetic algorithm","publication_year":2003,"publication_date":"2003-05-01","ids":{"openalex":"https://openalex.org/W2058420708","doi":"https://doi.org/10.1080/713827176","mag":"2058420708"},"language":"en","primary_location":{"id":"doi:10.1080/713827176","is_oa":true,"landing_page_url":"https://doi.org/10.1080/713827176","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/713827176?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/713827176?needAccess=true&role=button","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056213327","display_name":"Estevam Hruschka","orcid":"https://orcid.org/0000-0003-1499-2808"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]},{"id":"https://openalex.org/I4210094372","display_name":"Universidade Tuiuti do Paran\u00e1","ror":"https://ror.org/00te64c61","country_code":"BR","type":"education","lineage":["https://openalex.org/I4210094372"]},{"id":"https://openalex.org/I75619284","display_name":"Universidade Positivo","ror":"https://ror.org/02d09a271","country_code":"BR","type":"education","lineage":["https://openalex.org/I75619284"]},{"id":"https://openalex.org/I83648350","display_name":"Universidade Federal do Estado do Rio de Janeiro","ror":"https://ror.org/04tec8z30","country_code":"BR","type":"education","lineage":["https://openalex.org/I83648350"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Estevam R. Hruschka","raw_affiliation_strings":["Centro Universit\u00e1rio, Positivo, Brazil ; Universidade Tuiuli do Paran\u00e1, Brazil","Universidade Federal do Rio de Janeiro, Brazil ; Centro Universit\u00e1rio, Positivo, Brazil","Centro Universit\u00e1rio , Positivo, Brazil","Universidade Federal do Rio de Janeiro , Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centro Universit\u00e1rio, Positivo, Brazil ; Universidade Tuiuli do Paran\u00e1, Brazil","institution_ids":["https://openalex.org/I4210094372","https://openalex.org/I75619284"]},{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro, Brazil ; Centro Universit\u00e1rio, Positivo, Brazil","institution_ids":["https://openalex.org/I75619284","https://openalex.org/I83648350"]},{"raw_affiliation_string":"Centro Universit\u00e1rio , Positivo, Brazil","institution_ids":["https://openalex.org/I75619284"]},{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro , Brazil","institution_ids":["https://openalex.org/I122140584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021283579","display_name":"Eduardo R. Hruschka","orcid":"https://orcid.org/0000-0002-9529-8916"},"institutions":[{"id":"https://openalex.org/I4210094372","display_name":"Universidade Tuiuti do Paran\u00e1","ror":"https://ror.org/00te64c61","country_code":"BR","type":"education","lineage":["https://openalex.org/I4210094372"]},{"id":"https://openalex.org/I75619284","display_name":"Universidade Positivo","ror":"https://ror.org/02d09a271","country_code":"BR","type":"education","lineage":["https://openalex.org/I75619284"]},{"id":"https://openalex.org/I83648350","display_name":"Universidade Federal do Estado do Rio de Janeiro","ror":"https://ror.org/04tec8z30","country_code":"BR","type":"education","lineage":["https://openalex.org/I83648350"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo R. Hruschka","raw_affiliation_strings":["Centro Universit\u00e1rio, Positivo, Brazil ; Universidade Tuiuli do Paran\u00e1, Brazil","Universidade Federal do Rio de Janeiro, Brazil ; Centro Universit\u00e1rio, Positivo, Brazil","Centro Universit\u00e1rio , Positivo, Brazil","Universidade Tuiuli do Paran\u00e1 , Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centro Universit\u00e1rio, Positivo, Brazil ; Universidade Tuiuli do Paran\u00e1, Brazil","institution_ids":["https://openalex.org/I4210094372","https://openalex.org/I75619284"]},{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro, Brazil ; Centro Universit\u00e1rio, Positivo, Brazil","institution_ids":["https://openalex.org/I75619284","https://openalex.org/I83648350"]},{"raw_affiliation_string":"Centro Universit\u00e1rio , Positivo, Brazil","institution_ids":["https://openalex.org/I75619284"]},{"raw_affiliation_string":"Universidade Tuiuli do Paran\u00e1 , Brazil","institution_ids":["https://openalex.org/I4210094372"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021766596","display_name":"Nelson F. F. Ebecken","orcid":"https://orcid.org/0000-0003-4928-0966"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Nelson F. F. Ebecken","raw_affiliation_strings":["Universidade Federal do Rio de Janeiro, Brazil","Universidade Federal do Rio de Janeiro , Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro, Brazil","institution_ids":["https://openalex.org/I122140584"]},{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro , Brazil","institution_ids":["https://openalex.org/I122140584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":1.1028,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.8970559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"17","issue":"5-6","first_page":"489","last_page":"506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9706000089645386,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9706000089645386,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9537000060081482,"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/computer-science","display_name":"Computer science","score":0.7756799459457397},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7238818407058716},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6457757353782654},{"id":"https://openalex.org/keywords/markov-blanket","display_name":"Markov blanket","score":0.5630255937576294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4926198124885559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4687595069408417},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.42795321345329285},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38427969813346863},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.2880767583847046},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.2501547932624817},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.08561548590660095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7756799459457397},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7238818407058716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6457757353782654},{"id":"https://openalex.org/C123867240","wikidata":"https://www.wikidata.org/wiki/Q3001792","display_name":"Markov blanket","level":5,"score":0.5630255937576294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4926198124885559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4687595069408417},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.42795321345329285},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38427969813346863},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2880767583847046},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.2501547932624817},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.08561548590660095}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/713827176","is_oa":true,"landing_page_url":"https://doi.org/10.1080/713827176","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/713827176?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/713827176","is_oa":true,"landing_page_url":"https://doi.org/10.1080/713827176","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/713827176?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2058420708.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2123587139","https://openalex.org/W2797721853","https://openalex.org/W2510548579","https://openalex.org/W2161642932","https://openalex.org/W1146760960","https://openalex.org/W49111948","https://openalex.org/W4206306045","https://openalex.org/W2307705085","https://openalex.org/W3186106104","https://openalex.org/W4312178962"],"abstract_inverted_index":{"This":[0],"work":[1],"describes":[2],"a":[3,7,13,30,133],"method":[4,53,205],"that":[5,164,202],"combines":[6],"Bayesian":[8,25],"feature":[9,45],"selection":[10,47],"approach":[11],"with":[12,180,189],"clustering":[14,61,131],"genetic":[15],"algorithm":[16],"to":[17,43,137,147,186,193],"get":[18],"classification":[19,108,149],"rules":[20,109,178],"in":[21,63,132,160],"data-mining":[22,168],"applications.":[23],"A":[24],"network":[26],"is":[27,41,54,154,206],"generated":[28],"from":[29],"data":[31,134,162],"set":[32],"and":[33,56,89,143,173,197],"the":[34,38,44,60,64,100,104,114,118,129,138,182,190,194,198,203],"Markov":[35,195],"blanket":[36,196],"of":[37,58,66,74,102,107,116,121,158],"class":[39,68],"variable":[40],"applied":[42,146],"subset":[46],"task.":[48],"The":[49,123,151,177],"general":[50],"rule":[51],"extraction":[52],"simple":[55],"consists":[57],"employing":[59],"process":[62],"examples":[65,76],"each":[67,80],"separately.":[69],"In":[70,97],"this":[71,98],"way,":[72],"clusters":[73,83],"similar":[75],"are":[77,165,184],"found":[78],"for":[79,167],"class.":[81],"These":[82],"can":[84,110,127],"be":[85,92,111],"viewed":[86,112],"as":[87,113],"subclasses":[88],"can,":[90],"consequently,":[91],"modeled":[93],"into":[94],"logical":[95],"rules.":[96,150],"context,":[99],"problem":[101,115],"finding":[103,117],"optimal":[105],"number":[106,120],"best":[119,130],"clusters.":[122],"Clustering":[124],"Genetic":[125],"Algorithm":[126],"find":[128],"set,":[135],"according":[136],"Average":[139],"Silhouette":[140],"Width":[141],"criterion,":[142],"it":[144],"was":[145],"extract":[148],"proposed":[152,204],"methodology":[153],"illustrated":[155],"by":[156],"means":[157],"simulations":[159],"three":[161],"sets":[163],"benchmarks":[166],"methods--Wisconsin":[169],"Breast":[170],"Cancer,":[171],"Mushroom,":[172],"Congressional":[174],"Voting":[175],"Records.":[176],"extracted":[179,188],"all":[181],"attributes":[183],"compared":[185],"those":[187],"features":[191],"belonging":[192],"obtained":[199],"results":[200],"show":[201],"very":[207],"promising.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}