{"id":"https://openalex.org/W4312784194","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892181","title":"Parallel feature selection based on the trace ratio criterion","display_name":"Parallel feature selection based on the trace ratio criterion","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312784194","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892181"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892181","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100695332","display_name":"Thi Thu Hien Nguyen","orcid":"https://orcid.org/0000-0001-7726-3034"},"institutions":[{"id":"https://openalex.org/I4210153474","display_name":"Simula Metropolitan Center for Digital Engineering","ror":"https://ror.org/04xtarr15","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I184531372","https://openalex.org/I2799829267","https://openalex.org/I4210153474"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Thu Nguyen","raw_affiliation_strings":["Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway"],"affiliations":[{"raw_affiliation_string":"Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","institution_ids":["https://openalex.org/I4210153474"]},{"raw_affiliation_string":"Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway","institution_ids":["https://openalex.org/I4210153474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008622","display_name":"Nhan Lu-Chinh Phan","orcid":"https://orcid.org/0000-0002-7029-1232"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Nhan Phan","raw_affiliation_strings":["University of Science Vietnam National University in Ho Chi Minh City,Dept. of Mathematics and Computer Science,Ho Chi Minh city,Vietnam","Dept. of Mathematics and Computer Science, University of Science Vietnam National University in Ho Chi Minh City, Ho Chi Minh city, Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Science Vietnam National University in Ho Chi Minh City,Dept. of Mathematics and Computer Science,Ho Chi Minh city,Vietnam","institution_ids":["https://openalex.org/I123565023"]},{"raw_affiliation_string":"Dept. of Mathematics and Computer Science, University of Science Vietnam National University in Ho Chi Minh City, Ho Chi Minh city, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005701424","display_name":"Nhuong V. Nguyen","orcid":"https://orcid.org/0000-0003-4152-5113"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nhuong Nguyen","raw_affiliation_strings":["University of Connecticut,Dept. Computer Science and Engineering,Connecticut,USA","Dept. Computer Science and Engineering, University of Connecticut, Connecticut, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut,Dept. Computer Science and Engineering,Connecticut,USA","institution_ids":["https://openalex.org/I140172145"]},{"raw_affiliation_string":"Dept. Computer Science and Engineering, University of Connecticut, Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102903061","display_name":"Binh T. Nguyen","orcid":"https://orcid.org/0009-0009-9527-1957"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Binh T. Nguyen","raw_affiliation_strings":["University Of Science Vietnam National University in Ho Chi Minh City,AISIA Research Lab,Dept. of Computer Science,Ho Chi Minh city,Vietnam","Dept. of Computer Science, AISIA Research Lab, University Of Science Vietnam National University in Ho Chi Minh City, Ho Chi Minh city, Vietnam"],"affiliations":[{"raw_affiliation_string":"University Of Science Vietnam National University in Ho Chi Minh City,AISIA Research Lab,Dept. of Computer Science,Ho Chi Minh city,Vietnam","institution_ids":["https://openalex.org/I123565023"]},{"raw_affiliation_string":"Dept. of Computer Science, AISIA Research Lab, University Of Science Vietnam National University in Ho Chi Minh City, Ho Chi Minh city, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088962741","display_name":"P\u00e5l Halvorsen","orcid":"https://orcid.org/0000-0003-2073-7029"},"institutions":[{"id":"https://openalex.org/I4210153474","display_name":"Simula Metropolitan Center for Digital Engineering","ror":"https://ror.org/04xtarr15","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I184531372","https://openalex.org/I2799829267","https://openalex.org/I4210153474"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Pal Halvorsen","raw_affiliation_strings":["Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway"],"affiliations":[{"raw_affiliation_string":"Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","institution_ids":["https://openalex.org/I4210153474"]},{"raw_affiliation_string":"Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway","institution_ids":["https://openalex.org/I4210153474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102968267","display_name":"Michael A. Riegler","orcid":"https://orcid.org/0000-0002-3153-2064"},"institutions":[{"id":"https://openalex.org/I4210153474","display_name":"Simula Metropolitan Center for Digital Engineering","ror":"https://ror.org/04xtarr15","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I184531372","https://openalex.org/I2799829267","https://openalex.org/I4210153474"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Michael A. Riegler","raw_affiliation_strings":["Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway"],"affiliations":[{"raw_affiliation_string":"Simula Metropolitan,Dept. of Holistic Systems,Oslo,Norway","institution_ids":["https://openalex.org/I4210153474"]},{"raw_affiliation_string":"Dept. of Holistic Systems, Simula Metropolitan, Oslo, Norway","institution_ids":["https://openalex.org/I4210153474"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100695332"],"corresponding_institution_ids":["https://openalex.org/I4210153474"],"apc_list":null,"apc_paid":null,"fwci":0.1199,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44531584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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/computer-science","display_name":"Computer science","score":0.7347785234451294},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7144936323165894},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6519376039505005},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6436631679534912},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.609043538570404},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5982365608215332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5811752080917358},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5356748700141907},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5283761024475098},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5271826982498169},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.46498531103134155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4145951569080353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7347785234451294},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7144936323165894},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6519376039505005},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6436631679534912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.609043538570404},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5982365608215332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5811752080917358},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5356748700141907},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5283761024475098},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5271826982498169},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.46498531103134155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4145951569080353},{"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/ijcnn55064.2022.9892181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892181","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1480487340","https://openalex.org/W1496519456","https://openalex.org/W1525878169","https://openalex.org/W1527456780","https://openalex.org/W1570713908","https://openalex.org/W1994252348","https://openalex.org/W1995806857","https://openalex.org/W1998989894","https://openalex.org/W2005617509","https://openalex.org/W2008451765","https://openalex.org/W2097323375","https://openalex.org/W2101234009","https://openalex.org/W2116045745","https://openalex.org/W2116148865","https://openalex.org/W2119387367","https://openalex.org/W2128507168","https://openalex.org/W2135904200","https://openalex.org/W2143043751","https://openalex.org/W2143426320","https://openalex.org/W2162708633","https://openalex.org/W2166381300","https://openalex.org/W2293600471","https://openalex.org/W2344681634","https://openalex.org/W2397338210","https://openalex.org/W2474269906","https://openalex.org/W2487770199","https://openalex.org/W2552399396","https://openalex.org/W2887961823","https://openalex.org/W2971196067","https://openalex.org/W2991083008","https://openalex.org/W3120740533","https://openalex.org/W3132999519","https://openalex.org/W3157030441","https://openalex.org/W4246623349","https://openalex.org/W4289236186","https://openalex.org/W4298870207","https://openalex.org/W6675354045","https://openalex.org/W6729600607","https://openalex.org/W6738339794","https://openalex.org/W6770534319"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W2104382484","https://openalex.org/W3008559849"],"abstract_inverted_index":{"The":[0,204],"growth":[1],"of":[2,18,22,35,97,126,129,143,215,220,223],"data":[3,24,36],"today":[4],"poses":[5],"a":[6,67,95,127,137,174,212,218],"challenge":[7],"in":[8,31,56,60,101,155,217],"management":[9,62],"and":[10,50],"inference.":[11],"While":[12],"feature":[13,42,70,107],"extraction":[14],"methods":[15,190,228],"are":[16,153],"capable":[17],"reducing":[19,61],"the":[20,23,33,39,47,111,118,149,156,169,184,199,221,226,233,237,248,261],"size":[21],"for":[25,73,131,163],"inference,":[26],"they":[27],"do":[28],"not":[29,54,242],"help":[30],"minimizing":[32],"cost":[34],"storage.":[37],"On":[38],"other":[40,227,252],"hand,":[41],"selection":[43,71,139,176],"helps":[44],"to":[45,86,105,177],"remove":[46],"redundant":[48,145,181],"features":[49,124,130,146,152,216,238],"therefore":[51],"is":[52],"helpful":[53],"only":[55,243],"inference":[57],"but":[58,254],"also":[59,256],"costs.":[63],"This":[64],"work":[65],"presents":[66],"novel":[68],"parallel":[69],"approach":[72],"classification,":[74],"namely":[75],"Parallel":[76],"Feature":[77],"Selection":[78],"using":[79,194],"Trace":[80],"criterion":[81],"(PFST),":[82],"which":[83],"scales":[84],"up":[85],"very":[87],"large":[88],"datasets.":[89],"Our":[90],"method":[91,209],"uses":[92],"trace":[93],"criterion,":[94,119],"measure":[96],"class":[98],"separability":[99],"used":[100],"Fisher's":[102],"Discriminant":[103,196],"Analysis,":[104],"evaluate":[106,188],"usefulness.":[108],"We":[109,187],"analyzed":[110],"criterion's":[112],"desirable":[113],"properties":[114],"theoretically.":[115],"Based":[116],"on":[117,201,236,263],"PFST":[120,241],"rapidly":[121],"finds":[122],"important":[123,151],"out":[125],"set":[128,214],"big":[132],"datasets":[133],"by":[134,183,225,240,251],"first":[135],"making":[136],"forward":[138,185],"with":[140],"early":[141],"removal":[142],"seemingly":[144],"parallelly.":[147],"After":[148],"most":[150],"included":[154],"model,":[157],"we":[158,172],"check":[159,178],"back":[160,179],"their":[161],"contribution":[162],"possible":[164,180],"interaction":[165],"that":[166,207],"may":[167],"improve":[168],"fit.":[170],"Lastly,":[171],"make":[173],"backward":[175],"added":[182],"steps.":[186],"our":[189,208],"via":[191],"various":[192],"experiments":[193,205],"Linear":[195],"Analysis":[197],"as":[198],"classifier":[200,234],"selected":[202,239],"features.":[203,266],"show":[206],"can":[210,255],"produce":[211],"small":[213],"fraction":[219],"amount":[222],"time":[224],"under":[229],"comparison.":[230],"In":[231],"addition,":[232],"trained":[235],"achieves":[244],"better":[245,258],"accuracy":[246,259],"than":[247,260],"ones":[249],"chosen":[250],"approaches,":[253],"achieve":[257],"classification":[262],"all":[264],"available":[265]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}