{"id":"https://openalex.org/W4390903252","doi":"https://doi.org/10.1007/s41060-023-00494-6","title":"A stable model for maximizing the number of significant features","display_name":"A stable model for maximizing the number of significant features","publication_year":2024,"publication_date":"2024-01-16","ids":{"openalex":"https://openalex.org/W4390903252","doi":"https://doi.org/10.1007/s41060-023-00494-6"},"language":"en","primary_location":{"id":"doi:10.1007/s41060-023-00494-6","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s41060-023-00494-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-023-00494-6.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s41060-023-00494-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046986752","display_name":"E. K. Park","orcid":"https://orcid.org/0000-0002-3153-1109"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Eunkyung Park","raw_affiliation_strings":["Computer Science and Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0002-3153-1109","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015158455","display_name":"Raymond K. Wong","orcid":"https://orcid.org/0000-0002-9814-6029"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Raymond K. Wong","raw_affiliation_strings":["Computer Science and Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052534331","display_name":"Junbum Kwon","orcid":"https://orcid.org/0000-0002-1017-6849"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junbum Kwon","raw_affiliation_strings":["School of Marketing, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Marketing, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021022882","display_name":"Victor W. Chu","orcid":"https://orcid.org/0000-0002-5853-5820"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Victor W. Chu","raw_affiliation_strings":["Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046986752"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0049425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"4","first_page":"443","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9957000017166138,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9957000017166138,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9908999800682068,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9843999743461609,"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/regularization","display_name":"Regularization (linguistics)","score":0.8045698404312134},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7463654279708862},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6600176692008972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6110535860061646},{"id":"https://openalex.org/keywords/multicollinearity","display_name":"Multicollinearity","score":0.5582385659217834},{"id":"https://openalex.org/keywords/rounding","display_name":"Rounding","score":0.4886660873889923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47342565655708313},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.4329589605331421},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4161984622478485},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39877796173095703},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37648677825927734},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37452414631843567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3392469882965088},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33771422505378723},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.1997832953929901}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.8045698404312134},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7463654279708862},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6600176692008972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110535860061646},{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.5582385659217834},{"id":"https://openalex.org/C136625980","wikidata":"https://www.wikidata.org/wiki/Q663208","display_name":"Rounding","level":2,"score":0.4886660873889923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47342565655708313},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4329589605331421},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4161984622478485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39877796173095703},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37648677825927734},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37452414631843567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3392469882965088},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33771422505378723},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.1997832953929901},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41060-023-00494-6","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s41060-023-00494-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-023-00494-6.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/179999","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-023-00494-6","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1007/s41060-023-00494-6","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s41060-023-00494-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-023-00494-6.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"},{"id":"https://openalex.org/F4320320965","display_name":"University of New South Wales","ror":"https://ror.org/03r8z3t63"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390903252.pdf"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1523985187","https://openalex.org/W1535995764","https://openalex.org/W2122825543","https://openalex.org/W2135046866","https://openalex.org/W2487770199","https://openalex.org/W2605213558","https://openalex.org/W2798859316","https://openalex.org/W2803992240","https://openalex.org/W2889270078","https://openalex.org/W2962877661","https://openalex.org/W2963847595","https://openalex.org/W2997759614","https://openalex.org/W2998142440","https://openalex.org/W3001620258","https://openalex.org/W3037000643","https://openalex.org/W3099470970","https://openalex.org/W3103221895","https://openalex.org/W3125657517","https://openalex.org/W3161462564","https://openalex.org/W4234698323","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W4317475364","https://openalex.org/W2136196209","https://openalex.org/W4283715790"],"abstract_inverted_index":{"Abstract":[0],"Identifying":[1],"significant":[2],"features":[3,25],"(SFs)":[4],"is":[5,18],"important":[6],"because":[7],"they":[8,21],"are":[9,35],"driving":[10],"factors":[11],"of":[12,71,100,106,114,130],"a":[13,64],"target":[14],"outcome.":[15],"However,":[16],"it":[17,95],"difficult":[19],"when":[20,33],"have":[22],"much":[23],"more":[24,31],"than":[26],"observations.":[27],"The":[28],"problem":[29],"becomes":[30],"challenging":[32],"there":[34],"multicollinearity":[36],"and":[37,50,119],"infrequent":[38],"common":[39],"features.":[40],"In":[41],"such":[42,47],"case,":[43],"standard":[44],"explainable":[45],"methods":[46],"as":[48,137],"OLS":[49],"Lasso":[51],"often":[52],"fail":[53],"to":[54,67],"identify":[55],"many":[56],"SF.":[57],"To":[58],"tackle":[59],"these":[60],"problems,":[61],"we":[62],"propose":[63],"stable":[65],"model":[66],"maximize":[68],"the":[69,83,97,104,127,138],"number":[70,105,129],"SFs":[72,131],"using":[73],"selective":[74,88],"inference":[75,89],"called":[76],"SFLasso-SI.":[77],"First,":[78],"in":[79,82],"each":[80],"point":[81],"regularization":[84,101],"path,":[85],"SFLasso-SI":[86,124],"conducts":[87],"for":[90],"conservative":[91],"significance":[92],"test.":[93],"Then,":[94],"chooses":[96],"optimum":[98],"value":[99],"that":[102,122],"maximizes":[103],"SFs.":[107],"Our":[108],"extensive":[109],"experiments":[110],"across":[111],"different":[112],"types":[113],"data":[115],"-":[116],"text,":[117],"image,":[118],"video":[120],"show":[121],"our":[123],"can":[125],"find":[126],"biggest":[128],"while":[132],"maintaining":[133],"similar":[134],"prediction":[135],"accuracy":[136],"benchmarking":[139],"methods.":[140]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}