{"id":"https://openalex.org/W3040201768","doi":"https://doi.org/10.1002/sam.11473","title":"Weighted linear programming discriminant analysis for\u00a0high\u2010dimensional binary classification","display_name":"Weighted linear programming discriminant analysis for\u00a0high\u2010dimensional binary classification","publication_year":2020,"publication_date":"2020-07-04","ids":{"openalex":"https://openalex.org/W3040201768","doi":"https://doi.org/10.1002/sam.11473","mag":"3040201768"},"language":"en","primary_location":{"id":"doi:10.1002/sam.11473","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sam.11473","pdf_url":null,"source":{"id":"https://openalex.org/S40788348","display_name":"Statistical Analysis and Data Mining The ASA Data Science Journal","issn_l":"1932-1864","issn":["1932-1864","1932-1872"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistical Analysis and Data Mining: The ASA Data Science 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":"https://openalex.org/A5101642837","display_name":"Yufei Wu","orcid":"https://orcid.org/0000-0003-0605-3595"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yufei Wu","raw_affiliation_strings":["Department of Biostatistics University at Buffalo, The State University of New York  Buffalo New York USA","Department of Biostatistics, University at Buffalo, The State University of New York, Buffalo, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics University at Buffalo, The State University of New York  Buffalo New York USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Biostatistics, University at Buffalo, The State University of New York, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084397928","display_name":"Yu Guan","orcid":"https://orcid.org/0000-0002-7833-9755"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guan Yu","raw_affiliation_strings":["Department of Biostatistics University at Buffalo, The State University of New York  Buffalo New York USA","Department of Biostatistics, University at Buffalo, The State University of New York, Buffalo, New York, USA"],"raw_orcid":"https://orcid.org/0000-0002-7833-9755","affiliations":[{"raw_affiliation_string":"Department of Biostatistics University at Buffalo, The State University of New York  Buffalo New York USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Biostatistics, University at Buffalo, The State University of New York, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084397928"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":{"value":3760,"currency":"USD","value_usd":3760},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07614227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"5","first_page":"437","last_page":"450"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9955999851226807,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.820539116859436},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6483545899391174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5902841091156006},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5428767800331116},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5393860340118408},{"id":"https://openalex.org/keywords/optimal-discriminant-analysis","display_name":"Optimal discriminant analysis","score":0.5209487676620483},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5171574950218201},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.5118933916091919},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4929201602935791},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.47155070304870605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4054935872554779},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31797701120376587},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2889620363712311},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.26574984192848206},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22659504413604736},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.18913891911506653}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.820539116859436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6483545899391174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5902841091156006},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5428767800331116},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5393860340118408},{"id":"https://openalex.org/C104500394","wikidata":"https://www.wikidata.org/wiki/Q17104912","display_name":"Optimal discriminant analysis","level":3,"score":0.5209487676620483},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5171574950218201},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.5118933916091919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4929201602935791},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.47155070304870605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4054935872554779},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31797701120376587},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2889620363712311},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26574984192848206},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22659504413604736},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.18913891911506653},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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:10.1002/sam.11473","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sam.11473","pdf_url":null,"source":{"id":"https://openalex.org/S40788348","display_name":"Statistical Analysis and Data Mining The ASA Data Science Journal","issn_l":"1932-1864","issn":["1932-1864","1932-1872"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistical Analysis and Data Mining: The ASA Data Science Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1768730780","https://openalex.org/W1915008591","https://openalex.org/W1992581342","https://openalex.org/W2016119924","https://openalex.org/W2020925091","https://openalex.org/W2027717478","https://openalex.org/W2028912451","https://openalex.org/W2049701820","https://openalex.org/W2051605894","https://openalex.org/W2093019316","https://openalex.org/W2097360283","https://openalex.org/W2118250684","https://openalex.org/W2135046866","https://openalex.org/W2143423446","https://openalex.org/W2154560360","https://openalex.org/W2159400887","https://openalex.org/W2330541013","https://openalex.org/W3089164792","https://openalex.org/W3098713891","https://openalex.org/W4292363360","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W2113920489","https://openalex.org/W1984472287","https://openalex.org/W2134569917","https://openalex.org/W2379730211","https://openalex.org/W2028359806","https://openalex.org/W2104382484","https://openalex.org/W2379288828","https://openalex.org/W2128211328","https://openalex.org/W2156856390","https://openalex.org/W2254323784"],"abstract_inverted_index":{"Abstract":[0],"Linear":[1],"discriminant":[2,38,110,126,187],"analysis":[3],"(LDA)":[4],"is":[5,147,164],"widely":[6],"used":[7,199,217],"for":[8,82,149,190,222],"various":[9],"binary":[10,64,193,271],"classification":[11,32,59,65,151,194,272],"problems.":[12,66],"In":[13,115,166],"contrast":[14],"to":[15,68,117,218,244],"the":[16,20,25,31,35,42,76,84,90,99,108,125,135,143,150,160,171,191,201,210,230,246],"LDA":[17],"that":[18,258],"estimates":[19,41,120],"precision":[21],"matrix":[22],"\u03a9":[23,44,73],"and":[24,106,124,174,209,266],"mean":[26],"difference":[27],"vector":[28],"\u03b4":[29,45,74],"in":[30,89,134,200],"rule":[33,40,55,78,173,189,262],"separately,":[34],"linear":[36,185,231],"programming":[37,186,232],"(LPD)":[39],"product":[43],"directly":[46],"through":[47],"a":[48,182,236],"constrained":[49,91,136,248],"\u2113":[50,92,137,249],"1":[51,93,138,250],"minimization.":[52,94],"The":[53,196],"LPD":[54,77,172,265],"has":[56],"very":[57],"good":[58],"performance":[60],"on":[61,170],"many":[62],"high\u2010dimensional":[63,192,247],"However,":[67],"estimate":[69,101],"\u03b2":[70,87,103,122,132,155,226],"*":[71,88,104,123,227],"=":[72],",":[75,105],"uses":[79],"equal":[80],"weights":[81,221],"all":[83],"elements":[85,224],"of":[86,102,121,225,241],"It":[95],"may":[96],"not":[97],"deliver":[98],"optimal":[100],"therefore":[107],"estimated":[109],"direction":[111,239],"can":[112,129,263],"be":[113,216],"suboptimal.":[114],"order":[116],"obtain":[118],"better":[119],"direction,":[127],"we":[128,141,158,180,234],"heavily":[130],"penalize":[131,154],"j":[133,144,156,161],"minimization":[139,251],"if":[140,157],"suspect":[142,159],"th":[145,162],"feature":[146,163,177],"useless":[148],"while":[152],"moderately":[153],"useful.":[165],"this":[167],"paper,":[168],"based":[169],"some":[175],"popular":[176],"screening":[178,197,214],"methods,":[179],"propose":[181],"new":[183,237],"weighted":[184],"(WLPD)":[188],"problem.":[195],"statistics":[198],"marginal":[202,212],"two\u2010sample":[203],"t":[204],"\u2010test":[205],"screening,":[206],"Kolmogorov\u2013Smirnov":[207],"filter,":[208],"maximum":[211],"likelihood":[213],"will":[215],"construct":[219],"appropriate":[220],"different":[223],"flexibly.":[228],"Besides":[229],"algorithm,":[233],"develop":[235],"alternating":[238],"method":[240],"multipliers":[242],"algorithm":[243],"solve":[245],"problem":[252],"efficiently.":[253],"Our":[254],"numerical":[255],"studies":[256],"show":[257],"our":[259],"proposed":[260],"WLPD":[261],"outperform":[264],"serve":[267],"as":[268],"an":[269],"effective":[270],"tool.":[273]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}