{"id":"https://openalex.org/W3195008180","doi":"https://doi.org/10.1109/tem.2021.3098463","title":"Analysis of Subfeature for Classification in Data Mining","display_name":"Analysis of Subfeature for Classification in Data Mining","publication_year":2021,"publication_date":"2021-08-04","ids":{"openalex":"https://openalex.org/W3195008180","doi":"https://doi.org/10.1109/tem.2021.3098463","mag":"3195008180"},"language":"en","primary_location":{"id":"doi:10.1109/tem.2021.3098463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2021.3098463","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Engineering Management","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/A5056701836","display_name":"Hemanta Kumar Bhuyan","orcid":"https://orcid.org/0000-0002-9712-7280"},"institutions":[{"id":"https://openalex.org/I149313025","display_name":"Vignan's Foundation for Science, Technology & Research","ror":"https://ror.org/03bzf1g85","country_code":"IN","type":"education","lineage":["https://openalex.org/I149313025"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Hemanta Kumar Bhuyan","raw_affiliation_strings":["Department of Information Technology, Vignan's Foundation for Science, Technology and Research (Deemed to be University), Guntur, India"],"raw_orcid":"https://orcid.org/0000-0002-9712-7280","affiliations":[{"raw_affiliation_string":"Department of Information Technology, Vignan's Foundation for Science, Technology and Research (Deemed to be University), Guntur, India","institution_ids":["https://openalex.org/I149313025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040100735","display_name":"Vinayakumar Ravi","orcid":"https://orcid.org/0000-0001-6873-6469"},"institutions":[{"id":"https://openalex.org/I138564716","display_name":"Prince Mohammad bin Fahd University","ror":"https://ror.org/03d64na34","country_code":"SA","type":"education","lineage":["https://openalex.org/I138564716"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Vinayakumar Ravi","raw_affiliation_strings":["Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-6873-6469","affiliations":[{"raw_affiliation_string":"Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia","institution_ids":["https://openalex.org/I138564716"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056701836"],"corresponding_institution_ids":["https://openalex.org/I149313025"],"apc_list":null,"apc_paid":null,"fwci":2.3797,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.90608635,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"70","issue":"8","first_page":"2732","last_page":"2746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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":0.9955000281333923,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9937999844551086,"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/feature-selection","display_name":"Feature selection","score":0.7112873792648315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6847496628761292},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6384871006011963},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5695470571517944},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5294898152351379},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4704743027687073},{"id":"https://openalex.org/keywords/data-classification","display_name":"Data classification","score":0.42324894666671753},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4052043855190277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3922993242740631}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7112873792648315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6847496628761292},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6384871006011963},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5695470571517944},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5294898152351379},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4704743027687073},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.42324894666671753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4052043855190277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3922993242740631},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tem.2021.3098463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2021.3098463","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Engineering Management","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":44,"referenced_works":["https://openalex.org/W1040979544","https://openalex.org/W1480911578","https://openalex.org/W1575192016","https://openalex.org/W1922404199","https://openalex.org/W1988068519","https://openalex.org/W2010787746","https://openalex.org/W2020652789","https://openalex.org/W2060542593","https://openalex.org/W2080420136","https://openalex.org/W2084028080","https://openalex.org/W2101820646","https://openalex.org/W2103105037","https://openalex.org/W2109363337","https://openalex.org/W2128873747","https://openalex.org/W2140703956","https://openalex.org/W2143426320","https://openalex.org/W2148541040","https://openalex.org/W2149620660","https://openalex.org/W2153678774","https://openalex.org/W2160430743","https://openalex.org/W2183445908","https://openalex.org/W2321337859","https://openalex.org/W2343420905","https://openalex.org/W2523693978","https://openalex.org/W2546562960","https://openalex.org/W2885041036","https://openalex.org/W2886256216","https://openalex.org/W2887814203","https://openalex.org/W2894461463","https://openalex.org/W2897524496","https://openalex.org/W2898230917","https://openalex.org/W2899642931","https://openalex.org/W2903000008","https://openalex.org/W2910328857","https://openalex.org/W2921677257","https://openalex.org/W2923860144","https://openalex.org/W2963157523","https://openalex.org/W2963963190","https://openalex.org/W3130982961","https://openalex.org/W3155131285","https://openalex.org/W3165274303","https://openalex.org/W6671914738","https://openalex.org/W6681822384","https://openalex.org/W6729527742"],"related_works":["https://openalex.org/W4293525103","https://openalex.org/W2374344280","https://openalex.org/W2345184372","https://openalex.org/W3200179079","https://openalex.org/W2546942002","https://openalex.org/W3163334550","https://openalex.org/W2970216048","https://openalex.org/W2316780152","https://openalex.org/W2385233088","https://openalex.org/W2382607599"],"abstract_inverted_index":{"Feature":[0],"selection":[1,21,36],"is":[2,29,39,49,59,118,225],"a":[3,60,77,97,119,150,154],"crucial":[4],"part":[5],"of":[6,14,18,85,93,108,178,188],"data":[7,15,88,92,101,146],"mining":[8],"applications":[9],"in":[10,41,52,104,214],"the":[11,19,53,83,105,114,135,140,176,186,189,207,215,222],"diversity":[12],"area":[13],"analysis.":[16,57],"Most":[17],"feature":[20,35,46,65],"methods":[22,197,200],"issue":[23],"features":[24],"analysis":[25,66,84,213],"for":[26,32,55,149],"classification,":[27],"which":[28,48],"not":[30,50],"sufficient":[31],"classification":[33,208],"by":[34,67],"techniques.":[37],"Classification":[38],"involved":[40,103],"traditional":[42,98,155],"classes":[43,229],"with":[44,126,185,195],"redundant":[45],"data,":[47],"helpful":[51],"database":[54],"further":[56],"There":[58],"more":[61],"negligible":[62],"effect":[63],"on":[64,139,217,231],"taking":[68],"an":[69],"existing":[70],"class.":[71,99,116,156],"So,":[72],"it":[73,112],"proposed":[74,134,190,223],"to":[75,122,143,162,182],"obtain":[76],"new":[78,115,151],"class":[79,152],"or":[80],"subclass":[81],"using":[82],"feature's":[86],"tiny":[87],"named":[89],"subfeature":[90,164,179,210,233],"(SF)":[91],"corresponding":[94],"instances":[95,110,125],"from":[96,128,153],"These":[100],"are":[102,180],"limited":[106],"number":[107],"significant":[109],"where":[111],"generates":[113],"It":[117],"challenging":[120],"task":[121],"find":[123,144],"such":[124,145,169],"subfeatures":[127,174,184],"any":[129],"database.":[130],"Thus,":[131],"this":[132],"article":[133],"optimization":[136],"model":[137,224],"based":[138,230],"Lagrangian":[141],"multiplier":[142],"and":[147,172,175,198,203],"analyze":[148,206],"Several":[157],"algorithms":[158],"have":[159],"been":[160],"taken":[161],"explain":[163],"data.":[165,211,234],"The":[166],"theoretical":[167],"approaches":[168],"as":[170],"domain-":[171],"variance-based":[173],"convergence":[177],"used":[181],"select":[183],"effectiveness":[187],"model.":[191],"Furthermore,":[192],"several":[193],"classifiers":[194],"searching":[196],"statistical":[199],"(i.e.,":[201],"local":[202],"global":[204],"variances)":[205],"through":[209],"Result":[212],"experiment":[216],"different":[218],"datasets":[219],"shows":[220],"that":[221],"beneficial":[226],"toward":[227],"novel":[228],"selected":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}