{"id":"https://openalex.org/W4386895220","doi":"https://doi.org/10.3390/a16090447","title":"Carousel Greedy Algorithms for Feature Selection in Linear Regression","display_name":"Carousel Greedy Algorithms for Feature Selection in Linear Regression","publication_year":2023,"publication_date":"2023-09-19","ids":{"openalex":"https://openalex.org/W4386895220","doi":"https://doi.org/10.3390/a16090447"},"language":"en","primary_location":{"id":"doi:10.3390/a16090447","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16090447","pdf_url":"https://www.mdpi.com/1999-4893/16/9/447/pdf?version=1695172385","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/16/9/447/pdf?version=1695172385","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035071227","display_name":"Jiaqi Wang","orcid":"https://orcid.org/0009-0001-9427-3776"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiaqi Wang","raw_affiliation_strings":["Department of Mathematics, University of Maryland, College Park, MD 20742, USA"],"raw_orcid":"https://orcid.org/0009-0001-9427-3776","affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Maryland, College Park, MD 20742, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022968381","display_name":"Bruce Golden","orcid":"https://orcid.org/0000-0002-5270-6094"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bruce Golden","raw_affiliation_strings":["Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA"],"raw_orcid":"https://orcid.org/0000-0002-5270-6094","affiliations":[{"raw_affiliation_string":"Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072433066","display_name":"Carmine Cerrone","orcid":"https://orcid.org/0000-0002-6243-4512"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Carmine Cerrone","raw_affiliation_strings":["Department of Economics and Business Studies, University of Genoa, 16126 Genoa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6243-4512","affiliations":[{"raw_affiliation_string":"Department of Economics and Business Studies, University of Genoa, 16126 Genoa, Italy","institution_ids":["https://openalex.org/I83816512"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022968381","https://openalex.org/A5035071227"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.1952,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44274416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"16","issue":"9","first_page":"447","last_page":"447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9969000220298767,"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":0.9969000220298767,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9865999817848206,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9850000143051147,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.7301675081253052},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.7232059836387634},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7111911773681641},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5903140902519226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5730116367340088},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5611713528633118},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.529129147529602},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5287237763404846},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5228688716888428},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.5220919847488403},{"id":"https://openalex.org/keywords/stepwise-regression","display_name":"Stepwise regression","score":0.515438437461853},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4914017915725708},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.45463672280311584},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.42663976550102234},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40836453437805176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35659849643707275},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3338140547275543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2772539258003235},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20237210392951965},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1330098807811737}],"concepts":[{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.7301675081253052},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.7232059836387634},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7111911773681641},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5903140902519226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730116367340088},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5611713528633118},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.529129147529602},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5287237763404846},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5228688716888428},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.5220919847488403},{"id":"https://openalex.org/C170964787","wikidata":"https://www.wikidata.org/wiki/Q7611170","display_name":"Stepwise regression","level":2,"score":0.515438437461853},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4914017915725708},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.45463672280311584},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.42663976550102234},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40836453437805176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35659849643707275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3338140547275543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2772539258003235},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20237210392951965},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1330098807811737},{"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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/a16090447","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16090447","pdf_url":"https://www.mdpi.com/1999-4893/16/9/447/pdf?version=1695172385","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:iris.unige.it:11567/1153135","is_oa":true,"landing_page_url":"https://hdl.handle.net/11567/1153135","pdf_url":"https://iris.unige.it/bitstream/11567/1153135/1/algorithms-16-00447-v2.pdf","source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:3c723228ba4f410c99e0c734d1a9dc98","is_oa":true,"landing_page_url":"https://doaj.org/article/3c723228ba4f410c99e0c734d1a9dc98","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 16, Iss 9, p 447 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a16090447","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16090447","pdf_url":"https://www.mdpi.com/1999-4893/16/9/447/pdf?version=1695172385","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386895220.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1965125844","https://openalex.org/W1965169081","https://openalex.org/W1986783130","https://openalex.org/W2020925091","https://openalex.org/W2037842665","https://openalex.org/W2122825543","https://openalex.org/W2135046866","https://openalex.org/W2146688665","https://openalex.org/W2167840144","https://openalex.org/W2168175751","https://openalex.org/W2168893847","https://openalex.org/W2199135087","https://openalex.org/W2604863078","https://openalex.org/W2765086890","https://openalex.org/W2919730811","https://openalex.org/W2963351303","https://openalex.org/W2972299290","https://openalex.org/W3006889477","https://openalex.org/W3042489717","https://openalex.org/W3044201904","https://openalex.org/W3048822613","https://openalex.org/W3084898662","https://openalex.org/W3098004101","https://openalex.org/W3098306969","https://openalex.org/W3111016709","https://openalex.org/W3116426517","https://openalex.org/W3170234566","https://openalex.org/W3171575465","https://openalex.org/W3183564890","https://openalex.org/W3209142418","https://openalex.org/W4210643453","https://openalex.org/W4229873072","https://openalex.org/W4290649352","https://openalex.org/W4309825491","https://openalex.org/W6755923013","https://openalex.org/W6782522005","https://openalex.org/W6807917166","https://openalex.org/W7010325721"],"related_works":["https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W1986806918","https://openalex.org/W4285278887","https://openalex.org/W2995925505","https://openalex.org/W134783735","https://openalex.org/W2365237642","https://openalex.org/W3116484972","https://openalex.org/W2941986668","https://openalex.org/W4232431455"],"abstract_inverted_index":{"The":[0],"carousel":[1],"greedy":[2,13],"algorithm":[3],"(CG)":[4],"was":[5],"proposed":[6],"several":[7,46,107],"years":[8],"ago":[9],"as":[10],"a":[11,27,39],"generalized":[12],"algorithm.":[14],"In":[15],"this":[16],"paper,":[17],"we":[18,37,79,99],"implement":[19],"CG":[20,43,70,82],"to":[21,106],"solve":[22],"linear":[23],"regression":[24,55,74,86],"problems":[25],"with":[26],"cardinality":[28],"constraint":[29],"on":[30],"the":[31,64,102],"number":[32],"of":[33,42,89],"features.":[34,48],"More":[35],"specifically,":[36],"introduce":[38],"default":[40],"version":[41],"that":[44,81,101],"has":[45],"novel":[47],"We":[49],"compare":[50],"its":[51],"performance":[52],"against":[53],"stepwise":[54,73,85],"and":[56,63],"more":[57,108],"sophisticated":[58],"approaches":[59],"using":[60],"integer":[61],"programming,":[62],"results":[65],"are":[66],"encouraging.":[67],"For":[68],"example,":[69],"consistently":[71],"outperforms":[72],"(from":[75],"our":[76],"preliminary":[77],"experiments,":[78],"see":[80],"improves":[83],"upon":[84],"in":[87],"10":[88],"12":[90],"cases),":[91],"but":[92],"it":[93],"is":[94,104],"still":[95],"computationally":[96],"inexpensive.":[97],"Furthermore,":[98],"show":[100],"approach":[103],"applicable":[105],"general":[109],"feature":[110],"selection":[111],"problems.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}