{"id":"https://openalex.org/W2561049857","doi":"https://doi.org/10.3233/fi-2016-1422","title":"Post-processing of BRACID Rules Induced from Imbalanced Data","display_name":"Post-processing of BRACID Rules Induced from Imbalanced Data","publication_year":2016,"publication_date":"2016-12-24","ids":{"openalex":"https://openalex.org/W2561049857","doi":"https://doi.org/10.3233/fi-2016-1422","mag":"2561049857"},"language":"en","primary_location":{"id":"doi:10.3233/fi-2016-1422","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2016-1422","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","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/A5074073168","display_name":"Krystyna Napiera\u0142a","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krystyna Napierala","raw_affiliation_strings":["DATAX sp. z o.o., 53-609 Wroclaw, Poland. krystyna.napierala@datax.pl"],"affiliations":[{"raw_affiliation_string":"DATAX sp. z o.o., 53-609 Wroclaw, Poland. krystyna.napierala@datax.pl","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053315898","display_name":"Jerzy Stefanowski","orcid":"https://orcid.org/0000-0002-4949-8271"},"institutions":[{"id":"https://openalex.org/I46597724","display_name":"Pozna\u0144 University of Technology","ror":"https://ror.org/00p7p3302","country_code":"PL","type":"education","lineage":["https://openalex.org/I46597724"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Jerzy Stefanowski","raw_affiliation_strings":["Institute of Computing Sciences, Poznan University of Technology, 60-965 Poznan, Poland. Jerzy.Stefanowski@cs.put.poznan.pl"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Sciences, Poznan University of Technology, 60-965 Poznan, Poland. Jerzy.Stefanowski@cs.put.poznan.pl","institution_ids":["https://openalex.org/I46597724"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053315898"],"corresponding_institution_ids":["https://openalex.org/I46597724"],"apc_list":null,"apc_paid":null,"fwci":0.4285,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.79943339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"148","issue":"1-2","first_page":"51","last_page":"64"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9778000116348267,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.7060578465461731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.674465000629425},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.562984049320221},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5480473637580872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44922935962677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44062933325767517},{"id":"https://openalex.org/keywords/classification-rule","display_name":"Classification rule","score":0.42165881395339966}],"concepts":[{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.7060578465461731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.674465000629425},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.562984049320221},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5480473637580872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44922935962677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44062933325767517},{"id":"https://openalex.org/C104317236","wikidata":"https://www.wikidata.org/wiki/Q4330126","display_name":"Classification rule","level":2,"score":0.42165881395339966},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/fi-2016-1422","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2016-1422","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W68536248","https://openalex.org/W148954985","https://openalex.org/W752888290","https://openalex.org/W1103060529","https://openalex.org/W1528025004","https://openalex.org/W1561613409","https://openalex.org/W1566527164","https://openalex.org/W1599972685","https://openalex.org/W1798570018","https://openalex.org/W1965895350","https://openalex.org/W2014995154","https://openalex.org/W2024223694","https://openalex.org/W2061649716","https://openalex.org/W2114968414","https://openalex.org/W2137822999","https://openalex.org/W2148143831","https://openalex.org/W2160024688","https://openalex.org/W2161642325","https://openalex.org/W2161937800","https://openalex.org/W2163952039","https://openalex.org/W2164330572","https://openalex.org/W2172186225","https://openalex.org/W2212741395","https://openalex.org/W3110972171"],"related_works":["https://openalex.org/W3183204001","https://openalex.org/W4327743144","https://openalex.org/W4388567440","https://openalex.org/W4386782890","https://openalex.org/W4313320911","https://openalex.org/W2607424049","https://openalex.org/W4245077728","https://openalex.org/W4390922876","https://openalex.org/W2185941092","https://openalex.org/W2353085322"],"abstract_inverted_index":{"Rule-based":[0],"classifiers":[1],"constructed":[2],"from":[3,11],"imbalanced":[4,58],"data":[5,22],"fail":[6],"to":[7,16],"correctly":[8],"classify":[9],"instances":[10],"the":[12,72,76,80,101],"minority":[13,102],"class.":[14],"Solutions":[15],"this":[17],"problem":[18],"should":[19],"deal":[20],"with":[21],"and":[23,104],"algorithmic":[24],"difficulty":[25],"factors.":[26],"The":[27,39],"new":[28],"algorithm":[29],"BRACID":[30,47,85],"addresses":[31],"these":[32],"factors":[33],"more":[34],"comprehensively":[35],"than":[36],"other":[37,53],"proposals.":[38],"e":[40],"xperimental":[41],"evaluation":[42],"of":[43,46,68,75,84,108],"classification":[44],"abilities":[45],"shows":[48],"that":[49],"it":[50,61],"significantly":[51],"outperforms":[52],"rule":[54],"approaches":[55],"specialized":[56],"for":[57,82,100],"data.":[59],"However,":[60],"may":[62],"generate":[63],"too":[64],"high":[65,96],"a":[66],"number":[67],"rules,":[69],"which":[70],"hinder":[71],"human":[73],"interpretation":[74],"discovered":[77],"rules.":[78],"Thus,":[79],"method":[81],"post-processing":[83],"rules":[86,93],"is":[87],"presented.":[88],"It":[89],"aims":[90],"at":[91],"selecting":[92],"characterized":[94],"by":[95],"supports,":[97],"in":[98],"particular":[99],"class,":[103],"covering":[105],"diversified":[106],"subsets":[107],"examples.":[109],"Experimental":[110],"studies":[111],"confirm":[112],"its":[113],"usefulness.":[114]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
