{"id":"https://openalex.org/W2196737797","doi":"https://doi.org/10.1109/besc.2015.7365964","title":"Discriminative feature combination selection for enhancing multiclass classification","display_name":"Discriminative feature combination selection for enhancing multiclass classification","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2196737797","doi":"https://doi.org/10.1109/besc.2015.7365964","mag":"2196737797"},"language":"en","primary_location":{"id":"doi:10.1109/besc.2015.7365964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc.2015.7365964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5084604918","display_name":"Aibo Song","orcid":"https://orcid.org/0000-0003-4447-7305"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aibo Song","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114223509","display_name":"Wei Qian","orcid":"https://orcid.org/0000-0003-1556-4071"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Qian","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063565261","display_name":"Zhiang Wu","orcid":"https://orcid.org/0000-0002-0591-1861"},"institutions":[{"id":"https://openalex.org/I137056471","display_name":"Nanjing University of Finance and Economics","ror":"https://ror.org/031y8am81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137056471"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiang Wu","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, China","institution_ids":["https://openalex.org/I137056471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086538947","display_name":"Jinghua Zhao","orcid":"https://orcid.org/0000-0001-5501-9233"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghua Zhao","raw_affiliation_strings":["College of Information Science and Engineering, Shandong University of Science and Technology, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Shandong University of Science and Technology, Shandong, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"89","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9961000084877014,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9883000254631042,"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/discriminative-model","display_name":"Discriminative model","score":0.9657965898513794},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7576199769973755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7284764051437378},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7105280756950378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6775425672531128},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.615727961063385},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5391780138015747},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46929270029067993},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.44378286600112915},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32620522379875183},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2428775429725647}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9657965898513794},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7576199769973755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7284764051437378},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7105280756950378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775425672531128},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.615727961063385},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5391780138015747},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46929270029067993},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.44378286600112915},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32620522379875183},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2428775429725647},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/besc.2015.7365964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc.2015.7365964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7799999713897705}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W9488309","https://openalex.org/W178392936","https://openalex.org/W240165176","https://openalex.org/W1487276429","https://openalex.org/W1515087027","https://openalex.org/W1528547644","https://openalex.org/W1570448133","https://openalex.org/W1800493452","https://openalex.org/W2001082095","https://openalex.org/W2038902401","https://openalex.org/W2070046067","https://openalex.org/W2113014179","https://openalex.org/W2115482638","https://openalex.org/W2117169652","https://openalex.org/W2121250409","https://openalex.org/W2122827825","https://openalex.org/W2145252566","https://openalex.org/W2145388307","https://openalex.org/W2154642793","https://openalex.org/W2161498199","https://openalex.org/W2164281374","https://openalex.org/W2167681385","https://openalex.org/W3120740533","https://openalex.org/W4297936137","https://openalex.org/W6630857599","https://openalex.org/W6631567630","https://openalex.org/W6637980283","https://openalex.org/W6678161993","https://openalex.org/W6684495928"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Frequent":[0],"pattern":[1],"mining":[2,63],"is":[3,60,96],"commonly":[4],"utilized":[5],"to":[6,27,35,49,81,98],"generate":[7],"combined-feature":[8],"candidates,":[9],"yet":[10],"many":[11],"are":[12,52],"non-discriminative":[13],"and":[14,64],"thus":[15],"might":[16],"be":[17],"useless":[18],"for":[19,62],"predictive":[20],"models.":[21,41],"In":[22],"this":[23],"paper,":[24],"we":[25,43],"propose":[26],"use":[28],"feature":[29,54,106],"combinations":[30],"derived":[31],"from":[32],"frequent":[33],"patterns":[34],"obtain":[36],"more":[37],"accurate":[38],"multiclass":[39],"classification":[40,84],"Specifically,":[42],"present":[44],"a":[45],"novel":[46],"mathematics":[47],"inference":[48],"show":[50],"what":[51],"discriminative":[53,66,102],"combinations.":[55,107],"Hence,":[56],"an":[57,93],"efficient":[58],"algorithm":[59],"proposed":[61,77],"selecting":[65],"patterns.":[67],"Experimental":[68],"results":[69],"on":[70],"twenty":[71],"UCI":[72],"datasets":[73],"demonstrate":[74],"that":[75],"the":[76,83,100],"method":[78],"can":[79],"help":[80],"improve":[82],"performance":[85],"remarkably,":[86],"compared":[87],"with":[88],"other":[89],"baseline":[90],"methods.":[91],"Moreover,":[92],"internal":[94],"evaluation":[95],"employed":[97],"validate":[99],"strong":[101],"power":[103],"of":[104],"our":[105]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}