{"id":"https://openalex.org/W4414114835","doi":"https://doi.org/10.1177/1088467x241301694","title":"Weighted Bonferroni mean-based classifiers with factorization machines for binary classification","display_name":"Weighted Bonferroni mean-based classifiers with factorization machines for binary classification","publication_year":2024,"publication_date":"2024-12-25","ids":{"openalex":"https://openalex.org/W4414114835","doi":"https://doi.org/10.1177/1088467x241301694"},"language":"en","primary_location":{"id":"doi:10.1177/1088467x241301694","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1088467x241301694","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis: An International Journal","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":null,"display_name":"Yong Qiao Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Qiao Zhou","raw_affiliation_strings":["School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100738389","display_name":"Wei Yang","orcid":"https://orcid.org/0000-0001-5101-5745"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China"],"raw_orcid":"https://orcid.org/0000-0001-5101-5745","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069247310","display_name":"Zhen Ming","orcid":"https://orcid.org/0000-0003-3666-1188"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Ming Ma","raw_affiliation_strings":["School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Linyi University, Linyi, Shandong, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109131793","display_name":"Zeshui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeshui Xu","raw_affiliation_strings":["Business School, Sichuan University, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business School, Sichuan University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100738389"],"corresponding_institution_ids":["https://openalex.org/I15823474"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27456336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"29","issue":"5","first_page":"1085","last_page":"1105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9947999715805054,"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/T10320","display_name":"Neural Networks and Applications","score":0.9947999715805054,"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/T10057","display_name":"Face and Expression Recognition","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/feature","display_name":"Feature (linguistics)","score":0.6852999925613403},{"id":"https://openalex.org/keywords/bonferroni-correction","display_name":"Bonferroni correction","score":0.6381999850273132},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6355000138282776},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6043999791145325},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5867999792098999},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.5687999725341797},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4749999940395355}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6852999925613403},{"id":"https://openalex.org/C127808970","wikidata":"https://www.wikidata.org/wiki/Q385989","display_name":"Bonferroni correction","level":2,"score":0.6381999850273132},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6355000138282776},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6043999791145325},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5774999856948853},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5141000151634216},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.46959999203681946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4462999999523163},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3257000148296356},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25119999051094055},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/1088467x241301694","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1088467x241301694","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis: An International Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1855255219","display_name":null,"funder_award_id":"ZR2024MA087","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G4675805541","display_name":null,"funder_award_id":"ZR2023MA071","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1905771608","https://openalex.org/W1967753042","https://openalex.org/W1970781361","https://openalex.org/W1971875039","https://openalex.org/W2058024711","https://openalex.org/W2060907774","https://openalex.org/W2074605814","https://openalex.org/W2094286023","https://openalex.org/W2116231621","https://openalex.org/W2127377873","https://openalex.org/W2143570267","https://openalex.org/W2295739661","https://openalex.org/W2443960221","https://openalex.org/W2486460720","https://openalex.org/W2509235963","https://openalex.org/W2530680027","https://openalex.org/W2604662567","https://openalex.org/W2793768763","https://openalex.org/W2903950532","https://openalex.org/W2963323306","https://openalex.org/W2964052347","https://openalex.org/W3045423535","https://openalex.org/W3104030692","https://openalex.org/W3150492821","https://openalex.org/W3212575886"],"related_works":["https://openalex.org/W2390064908","https://openalex.org/W2917228042","https://openalex.org/W2564440352","https://openalex.org/W2239990209","https://openalex.org/W4253992846","https://openalex.org/W2461483947","https://openalex.org/W2026314750","https://openalex.org/W2106834122","https://openalex.org/W2028804942","https://openalex.org/W2095567388"],"abstract_inverted_index":{"Feature":[0],"interaction":[1],"plays":[2],"a":[3,72],"very":[4],"significant":[5],"role":[6],"in":[7,35],"binary":[8,15],"classification.":[9],"In":[10],"this":[11],"paper,":[12],"we":[13,52],"study":[14],"classification":[16],"with":[17],"weighted":[18,24,63,127],"feature":[19,64,128],"interactions":[20,34,65],"by":[21],"means":[22],"of":[23,33,62,75,84,126,145],"Bonferroni":[25,39],"mean":[26,40],"(WBM)":[27],"operators.":[28],"After":[29],"analyzing":[30],"the":[31,36,43,48,54,59,76,81,85,91,99,104,123,134,143],"characteristics":[32],"(dependently":[37],"weighted)":[38],"(BM)":[41],"operators,":[42],"quadratic-polynomial":[44],"(POLY2)-based":[45],"classifier,":[46,51],"and":[47,80,87,94,137],"factorization-machine":[49],"(FM)-based":[50],"introduce":[53],"WBM":[55],"operators":[56,70,79],"to":[57,121],"capture":[58],"independent":[60],"importance":[61,125],"among":[66],"input":[67],"arguments.":[68],"These":[69],"are":[71,119],"general":[73],"generalization":[74],"existing":[77],"BM":[78],"crossover":[82],"parts":[83],"POLY2-based":[86],"FM-based":[88],"classifiers.":[89,148],"Then,":[90],"WBM-based":[92,100,117],"classifiers":[93,101],"their":[95],"special":[96],"cases,":[97],"namely":[98],"based":[102],"on":[103,133],"factorization":[105],"machines":[106],"(abbreiated":[107],"as":[108],"FM":[109],"<mml:math":[110],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[111],"display=\"inline\"":[112],"overflow=\"scroll\">":[113],"<mml:mi":[114],"mathvariant=\"normal\">_</mml:mi>":[115],"</mml:math>":[116],"classifiers),":[118],"constructed":[120],"handle":[122],"(in)dependent":[124],"interactions.":[129],"Extensive":[130],"experimental":[131],"results":[132],"synthetic":[135],"datasets":[136,141],"four":[138],"UCI":[139],"machine-learning":[140],"verify":[142],"effectiveness":[144],"these":[146],"proposed":[147]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}